Les KPIs clés pour mesurer la performance d’un venture studio

Les venture studios gagnent du terrain dans l’écosystème entrepreneurial, en créant des startups de manière itérative et structurée. Contrairement aux fonds d’investissement ou aux incubateurs, leur modèle repose sur la création interne d’entreprises. Un studio n’est pas qu’une machine à startups, c’est aussi un acteur de transformation. Mais comment mesurer leur réussite ? Quels indicateurs permettent d’évaluer leur performance au-delà des simples sorties financières ?

Dans cet article, nous explorons les principaux KPIs (indicateurs clés de performance) qui permettent de suivre et d’analyser l’efficacité d’un venture studio.

Le taux de création de startups est un indicateur fondamental

Un premier KPI essentiel est le nombre de startups créées sur une période donnée (souvent annuelle). Ce chiffre reflète la capacité du studio à générer, valider et transformer des idées en projets réels.

Il ne s’agit pas seulement de quantité. Le ratio entre idées explorées et startups réellement lancées permet de mesurer l'efficacité du processus de validation en amont.

Le taux de survie des startups montre la solidité du modèle

Créer une startup, c’est bien. Mais assurer sa survie dans les 12 à 36 mois, c’est mieux. Le taux de survie mesure le pourcentage de startups du studio toujours actives après une période définie. Il témoigne de la qualité de l’accompagnement, de la pertinence du produit, et de l’adéquation au marché.

Un bon venture studio ne se contente pas de lancer des projets : il les structure pour qu’ils tiennent la route.

La vitesse de mise sur le marché reflète l’agilité du studio

L’un des grands atouts des venture studios est leur capacité à aller vite. Le time-to-market — soit le temps entre l’idéation et le lancement public du produit — est un KPI clé.

Un cycle de développement court indique que le studio sait mobiliser ses ressources (design, produit, développement, juridique) pour accélérer la croissance des projets.

Les levées de fonds externes mesurent l’attractivité des projets

Lorsque les startups issues d’un studio réussissent à lever des fonds externes, cela valide non seulement leur potentiel, mais aussi la crédibilité du studio aux yeux des investisseurs.

Le montant levé, le nombre de tours de financement réussis, et la qualité des investisseurs impliqués sont autant d’indicateurs de la valeur créée par le studio.

Le retour sur investissement global reste un KPI incontournable

Même si les studios ne fonctionnent pas comme des fonds VC classiques, ils doivent générer un retour sur investissement (ROI) à long terme. Cela peut inclure les exits (reventes), les dividendes perçus, ou encore l’augmentation de la valorisation du portefeuille global.

Ce KPI est souvent analysé sur un horizon de 5 à 10 ans, le temps que les startups atteignent leur maturité.

L’efficacité opérationnelle interne fait aussi la différence

Au-delà des performances des startups, la productivité de l’équipe du studio est aussi un KPI à suivre. Combien de projets un chef de produit ou un développeur peut-il gérer par an ? Le coût moyen par startup créée est-il optimisé ? Ces données permettent de piloter le modèle comme une entreprise à part entière.

Le réseau d’experts et de talents est un levier stratégique

Enfin, un KPI souvent sous-estimé concerne le réseau activé par le studio. Cela inclut les fondateurs recrutés, les experts impliqués, les partenariats industriels ou commerciaux. La richesse et la diversité de cet écosystème renforcent l’effet de levier du studio.

Un studio performant attire des talents de qualité, mobilise des mentors engagés et crée des synergies entre les startups.

L’impact sectoriel ou thématique : un KPI à considérer

Certains venture studios choisissent de se spécialiser dans des secteurs clés comme la santé, le climat, ou la tech sociale. Dans ce cas, il peut être pertinent de mesurer leur influence spécifique sur ces écosystèmes, par exemple à travers le nombre de brevets déposés, les partenariats noués avec des grands groupes industriels, ou encore leur contribution à la transition numérique ou écologique. 

Conclusion : mesurer, c’est piloter

La performance d’un venture studio ne se mesure pas uniquement à travers les succès visibles. Derrière chaque startup lancée, il y a des processus, des paris, des ajustements. En suivant des KPIs adaptés, à la fois quantitatifs et qualitatifs — les studios peuvent affiner leur stratégie, prouver leur impact, et construire un modèle durable.

Dans un écosystème en constante évolution, les venture studios qui savent se mesurer sont ceux qui savent durer.

Major Insurtech Trends: AI, Personalization, Automation

The global insurance sector is undergoing a seismic shift. As customer expectations evolve and digital technologies mature, insurtech companies are leading the charge in transforming how insurance is designed, delivered, and experienced.

At the heart of this revolution are three powerful forces: Artificial Intelligence (AI), hyper-personalization, and automation. These trends are not just buzzwords, they are redefining the insurance landscape in 2025 and beyond.

AI takes over risk assessment and claims processing

Artificial intelligence is becoming a core enabler for smarter, faster, and more scalable insurance operations. Insurtechs are using AI to:

• Analyze real-time customer data to generate more accurate risk profiles

• Detect fraudulent claims through pattern recognition and anomaly detection

• Automate underwriting with machine learning models trained on massive datasets

• Power chatbots that handle routine claims and customer service with minimal human intervention

By 2025, AI will no longer be a “nice-to-have”, it will be a competitive necessity for both startups and incumbents.

Hyper-personalization is the new standard

The age of one-size-fits-all insurance products is over. Today’s consumers expect coverage tailored to their lifestyle, behavior, and needs - and insurtechs are delivering.

Using data from connected devices, social platforms, wearables, and spending habits, insurtech platforms can:

• Offer usage-based insurance (e.g., pay-as-you-drive car insurance)

• Tailor recommendations in real time, such as micro-policies for short-term travel or freelance work

• Adapt coverage dynamically as a customer’s circumstances evolve

This level of personalization leads to higher customer retention, lower churn, and better alignment between risk and premium.

Automation streamlines the entire insurance lifecycle

Insurtechs are pushing automation across the board, from customer onboarding to claims disbursement. Key developments include:

• Instant quotes generated by digital platforms using AI-powered rules engines

• Self-service portals where users can buy, manage, and renew policies online

• Automated claims payouts, sometimes settled within minutes using smart contracts or pre-validated data

Automation reduces operational costs, eliminates friction, and frees up human agents to focus on high-value interactions.

Embedded insurance gains ground

Closely tied to automation is the rise of embedded insurance; coverage seamlessly offered at the point of need, integrated into platforms like e-commerce checkouts, car rental apps, or fintech services.

This trend is set to reshape distribution models, enabling insurtechs to reach customers who may never have actively sought out a policy.

Data-driven innovation fuels inclusive growth

With AI and automation unlocking new types of data, insurtechs can serve previously “uninsurable” populations, especially in emerging markets. Behavioral data and alternative credit scoring models are helping design inclusive insurance products for gig workers, rural communities, or informal sectors.

This shift represents not only a business opportunity but also a social innovation frontier.

Conclusion: Insurtech is redefining the rules of the game

As we move further into 2025, the most successful insurtechs will be those that blend AI intelligence, customer-centric personalization, and end-to-end automation into a seamless experience.

Traditional insurers that fail to adapt will struggle to stay relevant, while agile, tech-savvy players will set the standard for what modern insurance looks like: proactive, digital-first, and deeply human in impact.

The Most VC-Funded Sectors in Europe

The Most VC-Funded Sectors in Europe

Europe’s startup ecosystem has grown rapidly over the past decade, attracting billions in venture capital (VC) from both local and global investors. While overall funding levels fluctuate with macroeconomic conditions, certain sectors consistently draw strong VC attention. From climate tech and deep tech to fintech, health innovations, and enterprise software, the continent’s innovation landscape is increasingly diverse and resilient.

Climate Tech Leads the Pack

Climate tech and energy transition startups are now Europe’s single largest VC-funded sector, accounting for approximately 27–30% of total venture capital investment in 2023 (Dealroom/Sifted). This surge reflects the EU’s ambitious carbon neutrality targets, supportive policy frameworks, and the growing appetite among investors for climate-positive solutions.

Startups tackling renewable energy, sustainable mobility, carbon capture, and circular economy solutions are driving the trend. Countries like the Netherlands, Germany, and the Nordics are at the forefront, combining strong cleantech ecosystems with dedicated climate funds.

AI & Deep Tech Keep Rising

AI and deep tech (which includes frontier technologies like advanced hardware, quantum computing, and automation) accounted for about 17% of Europe’s VC funding in 2023. The rise of generative AI and automation tools is accelerating investor interest, with large rounds for companies like Mistral AI, DeepL, and Aleph Alpha showing the strength of the ecosystem.

Key hubs for AI and deep tech include Berlin, Paris, and London, all benefiting from talent density and supportive research institutions.

Fintech Remains a Pillar

Fintech remains a major draw, attracting roughly 15–19% of total VC investment, down slightly from its peak but still firmly in the top three sectors. From digital banks to blockchain platforms and payments solutions, European fintech leaders like Revolut (UK), N26 (Germany), and Lydia (France) continue to scale, supported by consumers’ shift away from traditional banking.

London remains Europe’s fintech capital, thanks to its mature regulatory environment and deep investor pools.

Healthtech & Enterprise Software Stay Solid

While harder to split precisely, healthtech and enterprise software together continue to be pillars of European VC activity. Over the last 20 years, they have consistently accounted for a combined ~40% of total VC funding (Dealroom). Healthtech startups in telemedicine, AI diagnostics, and mental health are still seeing healthy long-term growth, while B2B SaaS and cloud solutions remain attractive bets for their scalability and recurring revenues.

Companies like Doctolib (France), Kry (Sweden), and Celonis (Germany) show how Europe’s healthtech and enterprise software scenes remain globally competitive.

Emerging Sectors to Watch

Beyond these leading sectors, several emerging areas are gaining momentum:

• AgriTech: With food security and regenerative farming in focus, AgriTech is steadily attracting more funding.

• Cybersecurity: Increasing digital threats are driving larger rounds for European security startups.

• Edtech: While post-pandemic growth slowed, niches like corporate training and AI-driven learning are evolving.

• Space Tech: Once US-dominated, Europe’s space tech sector is quietly expanding, supported by national programs and private capital.

How Does Europe Compare Globally?

According to Dealroom’s 2023 and early 2024 data, Europe’s top-funded sectors now mirror global trends in the US and East Asia. In the US, the top sectors by VC investment are:

1. Health & Biotech

2. Enterprise Software / AI

3. Fintech

East Asia follows a similar pattern, with deep tech, fintech, and industrial tech attracting the biggest rounds. Notably, Europe’s climate tech stands out: its share of total VC funding is higher than in North America or Asia, thanks to EU policy incentives and investor demand for sustainable growth.

Final Thoughts

The European VC landscape is dynamic, but certain sectors continue to stand out for their scale, impact, and resilience. Climate tech, deep tech, fintech, healthtech, and enterprise software together account for the lion’s share of VC investment, while emerging verticals like AgriTech and space tech hint at the next wave of innovation.

For founders, understanding which sectors attract capital and why can shape how you position your startup. For investors, the current trends reflect where both opportunity and responsibility intersect in the next era of European innovation.

Predictive Insurance Through AI: Myth or Reality?

Methodology: Exploring AI’s Role in Insurance Forecasting

This article draws on industry reports, case studies, and current use cases from insurers applying artificial intelligence to predictive modeling. It examines how AI is reshaping underwriting, claims management, and customer engagement and where the promise may be ahead of the current reality.

In Brief: Where We Stand Today

• AI is already delivering predictive insights in claims detection, risk scoring, and fraud prevention.

• Adoption remains uneven, with most impact in large carriers and insurtech startups.

• Challenges include data privacy concerns, regulatory hurdles, and model transparency.

• The future of predictive insurance lies in combining AI with human judgment and ethical frameworks.

How AI Is Changing Insurance Predictions

The idea of predictive insurance is no longer science fiction. With vast amounts of customer data, real-time IoT inputs (such as from vehicles or smart homes), and advanced machine learning models, insurers can now:

• Identify high-risk customers or properties proactively

• Anticipate claim likelihood based on behavioral and environmental factors

• Tailor pricing more accurately for individual policyholders

• Detect fraud before payouts are made

AI models can process data at a scale and speed that human teams simply can’t match, making predictive insurance a growing reality in modern underwriting.

The Challenges That Make It Feel Like a Myth

Despite these advancements, predictive insurance powered by AI isn’t universal yet. Key challenges include:

Data Quality and Access

Insurers need clean, consistent, and ethically sourced data. Many legacy systems were not built for this level of data integration, slowing adoption.

Regulatory Landscape

Predictive pricing and claims forecasting raise complex compliance questions. Regulators demand transparency on how models make decisions, particularly in sensitive areas like health or auto insurance.

Trust and Transparency

Consumers and sometimes underwriters want to understand why a price or decision was made. AI models can feel like a “black box,” making it harder to build trust without proper explainability measures.

Where AI Predictive Models Are Already Delivering

Despite these challenges, AI-driven prediction is already reshaping certain insurance segments: 

• Auto insurance: Predictive telematics models score driver safety in real time, impacting pricing.

• Property insurance: Climate and weather models anticipate loss patterns to adjust coverage proactively.

• Health insurance: Behavioral data informs wellness incentives and early intervention programs.

• Fraud detection: AI flags anomalies faster than traditional methods, cutting loss ratios.

These are no longer pilot projects; they're live tools helping insurers reduce costs, improve customer experience, and drive smarter decisions.

Final Thought: Myth or Reality? A Bit of Both For Now

Predictive insurance through AI is very real but it’s not evenly applied across the industry. For many carriers, true AI-driven prediction is still aspirational, hampered by legacy infrastructure, governance complexity, and talent gaps.

However, where AI is deployed well, it’s transforming how risk is assessed, priced, and managed. The future will belong to insurers who combine AI’s predictive power with human insight, transparency, and a focus on ethical impact.

Comment l’IA personnalise l’expérience bancaire ?

Les attentes des clients envers leur banque ont profondément changé. Ils recherchent aujourd’hui simplicité, rapidité et services sur mesure. L’intelligence artificielle permet désormais aux banques d’offrir une expérience client personnalisée, comparable à celle des géants du numérique.

Mais comment cette transformation se concrétise-t-elle ? Voici un tour d’horizon de l’impact de l’IA sur l’expérience bancaire.

Des conseils financiers adaptés à chaque profil

L’IA peut analyser en temps réel les habitudes de dépenses, les revenus et les comportements financiers pour proposer des recommandations personnalisées : conseils d’épargne, alertes sur les dépenses, suggestions de budget, ou encore anticipation des découverts.

La banque devient ainsi un véritable assistant personnel, disponible à toute heure pour aider les clients à mieux gérer leur argent.

Une segmentation plus fine et plus pertinente

Grâce à l’IA, les banques dépassent les segmentations traditionnelles (âge, revenu, statut) et s’appuient sur des données comportementales. Elles peuvent ainsi proposer des offres adaptées au style de vie de chaque utilisateur, qu’il s’agisse de produits de crédit, d’assurance ou d’investissement.

Cette personnalisation améliore la pertinence des services et renforce la fidélité des clients.

Un service client plus fluide avec des assistants virtuels

Les chatbots intelligents permettent aux clients de poser des questions, consulter leurs comptes ou effectuer des opérations simples, sans passer par un conseiller. Ces assistants virtuels évoluent avec l’usage, comprennent les préférences des utilisateurs, et savent transférer la demande à un humain si nécessaire.

Le résultat : un service plus rapide et moins contraignant.

Une anticipation proactive des besoins

L’intelligence artificielle peut détecter de nouvelles habitudes (comme un changement de statut professionnel) et proposer des solutions financières adaptées : compte professionnel, assurance dédiée, options d’épargne ou d’investissement.

Cette capacité à anticiper renforce la position de la banque comme partenaire de confiance, au-delà de son rôle traditionnel.

Une sécurité renforcée, personnalisée pour chaque client

L’IA apprend à connaître les comportements habituels des utilisateurs et peut détecter immédiatement une activité suspecte. Ce niveau de vigilance personnalisé réduit les risques de fraude tout en évitant les alertes inutiles.

Les clients bénéficient ainsi d’une sécurité renforcée, sans perte de fluidité dans leur expérience.

Vers une relation bancaire plus empathique

Certaines banques testent des technologies d’analyse d’émotions dans les interactions client, pour adapter leur ton et mieux répondre aux situations sensibles. Même si ces approches sont encore en développement, elles ouvrent la voie à une relation plus humaine, même à distance.

Conclusion

L’intelligence artificielle transforme en profondeur la manière dont les banques interagissent avec leurs clients. Elle rend les services plus personnalisés, plus efficaces et plus sûrs.

Pour les établissements bancaires, cette transformation est une opportunité stratégique. Pour les clients, c’est la promesse d’une expérience plus fluide, plus utile, et centrée sur leurs besoins réels. 

Les tendances Insurtech à suivre en 2025

Le secteur de l’assurance vit une transformation profonde portée par la technologie. En 2025, les insurtechs ne se contenteront plus de numériser les processus existants : elles réinventeront l’ensemble de la chaîne de valeur, de la souscription à la gestion des sinistres.

Voici les 6 grandes tendances à surveiller pour comprendre où va l’innovation dans l’assurance.

1. L’intelligence artificielle devient le moteur principal de l’automatisation

L’IA est désormais au cœur des modèles insurtech. En 2025, elle sera utilisée à toutes les étapes : évaluation des risques, détection de fraude, gestion des sinistres, tarification dynamique.

Par exemple, AXA France a développé, avec Microsoft, une plateforme interne baptisée AXA Secure GPT. Basée sur l’IA générative, elle permet d’ajuster les offres aux antécédents médicaux ou au mode de vie : services de prévention personnalisés ou offres santé ciblées.

De leur côté, des startups comme Shift Technology utilisent l’IA pour détecter des fraudes en analysant des millions de transactions.

Les assistants conversationnels intelligents réduisent aussi les délais de traitement, offrent un support 24h/24, et améliorent l’expérience client de bout en bout.

2. L’assurance embarquée s’impose comme nouveau standard

L’assurance ne se vend plus, elle s’intègre. En 2025, le modèle de l’assurance embarquée ("embedded insurance") devient la norme, proposée automatiquement au bon moment — lors de l’achat d’un téléphone, d’un voyage ou d’un service.

Exemples notables :

• AppleCare propose une couverture dès l’achat d’un appareil Apple.

• Booking.com intègre des options d’assurance voyage au moment du paiement.

• Stripe propose aux commerçants d’offrir une assurance à leurs clients via son API.

Cette intégration contextuelle permet d’atteindre des clients qui n’auraient pas souscrit à une assurance classique.

3. Des modèles d’abonnement plus flexibles pour répondre aux nouveaux usages

Avec l’évolution des modes de vie (freelance, mobilité, économie à la demande), les clients attendent plus de flexibilité. En 2025, les insurtechs proposent des formules à la carte ou par abonnement, facilement activables ou désactivables via une app.

La startup française Luko permet par exemple de suspendre son assurance habitation quand on est en déplacement prolongé.

Ces offres s’inspirent des standards de consommation modernes (Netflix, Spotify), et séduisent particulièrement les générations Z et milléniales.

4. Une assurance plus inclusive, portée par la donnée alternative

Les données alternatives issues des objets connectés, réseaux sociaux ou plateformes de mobilité ouvrent de nouvelles perspectives.

La startup Pula, active en Afrique, utilise les données météo et agricoles satellitaires pour assurer les petits agriculteurs, jusque-là exclus des produits classiques.

Autre exemple : Zego, au Royaume-Uni, propose des assurances flexibles pour les livreurs ou chauffeurs VTC, en s’appuyant sur des données d’usage en temps réel (heures de conduite, distance parcourue).

Ces modèles permettent une inclusion assurantielle plus large, notamment dans les économies émergentes.

5. Un écosystème de partenariats plus stratégique

Les insurtechs ne visent plus à remplacer les assureurs traditionnels, mais à collaborer avec eux. En 2025, les partenariats stratégiques deviennent un levier clé : startups agiles + acteurs établis + géants technologiques.

Par exemple :

• Swiss Re collabore avec des insurtechs pour co-développer des produits.

• Generali noue des alliances avec des acteurs de la healthtech pour enrichir ses offres santé.

• Des acteurs cloud comme AWS ou Azure fournissent l’infrastructure sécurisée des nouvelles plateformes insurtech.

Ces synergies favorisent l’innovation tout en garantissant la solidité réglementaire et financière.

6. La blockchain gagne du terrain dans la gestion des sinistres

En matière de transparence et d’automatisation, la blockchain apporte des solutions puissantes.

Des startups comme Etherisc ou Chainlink expérimentent les smart contracts pour des assurances paramétriques : retard de vol, aléa météo, hospitalisation… L’indemnisation est automatique dès qu’un événement validé est détecté.

Bien que cette technologie reste marginale, elle se développe notamment dans les micro-assurances et les marchés émergents, où la rapidité et la confiance sont essentielles.

Conclusion : une assurance plus intégrée, intelligente et centrée sur l’utilisateur

En 2025, les insurtechs redéfinissent les règles du jeu. IA, personnalisation, intégration fluide, inclusion… l’assurance devient proactive, flexible et contextuelle.

Les compagnies traditionnelles devront s’adapter à ces standards ou risquer de perdre en compétitivité. Car plus que la technologie elle-même, c’est l’expérience utilisateur qui devient le nouvel avantage concurrentiel.

AI in WealthTech: Where the Next Wave of Innovation Lies

Artificial intelligence is not just a feature in WealthTech—it’s the foundation of the next generation of solutions. 

Our methodology involved gathering numerous venture maps from around the world to identify recurring categories and sources of innovation in AI. From this extensive research, we developed the Mandalore AI in WealthTech Venture Map 2025, which captures the current state of the art in AI technology and innovation. Using these insights, we analyzed how innovation is driven across different sectors and crafted this article to highlight the key trends and opportunities shaping the future of AI.

AI enables dynamic portfolio optimization

AI is redefining portfolio construction through hyper-personalization and continuous optimization. Algorithms can ingest investor goals, risk tolerance, and real-time market data to dynamically rebalance portfolios. This enables scalable, advisor-like services delivered automatically, with less human intervention and greater adaptability.

While unlocking private markets through automated sourcing and valuation

Access to private assets is being democratized and de-risked through AI-powered deal sourcing, valuation modeling, and scenario simulation. Machine learning models uncover hidden opportunities and automate diligence processes, creating a competitive edge in an opaque and fragmented landscape.

And turning financial planning into adaptive guidance

AI transforms static financial plans into living, breathing systems that adjust to life changes in real time. By integrating behavioral data and predictive analytics, platforms can guide users proactively—recommending decisions, anticipating shortfalls, and making planning feel less like a spreadsheet and more like a conversation.

As well as modernizing compliance with intelligent monitoring

Legacy compliance processes are being replaced by intelligent monitoring systems that learn from data and flag risks before they materialize. AI enhances transparency and reduces manual workloads, making it possible for firms to scale governance and stay ahead of evolving regulations with minimal friction.

While also enhancing market insight through unstructured data analysis

AI mines unstructured data—from news to social feeds—to generate real-time insights and sentiment indicators. This empowers investors to make faster, more informed decisions and unlocks new alpha from sources that traditional models overlook.

And finally personalizing client experience with predictive interfaces

AI personalizes the advisor-client relationship at scale. From conversational interfaces to predictive nudges, AI enables firms to deliver tailored advice, anticipate needs, and build trust—making digital wealth platforms feel human, even when no one is on the other end.

How is AI reshaping InsurTech ?

AI unlocks unprecedented underwriting value through non-traditional data processing, while simultaneously enabling substantial margin improvements via automated claims handling and fraud detection. Furthermore, behavioral prediction engines dramatically reduce acquisition costs, just as sector-specific applications improve loss ratios and create new premium pools. Finally, dynamic pricing optimization delivers defensible advantages through improved ratios and conversion rates.

Our methodology involved gathering numerous venture maps from around the world to identify recurring categories and sources of innovation in AI. From this extensive research, we developed the Mandalore AI in InsurTech Venture Map 2025, which captures the current state of the art in AI technology and innovation. Using these insights, we analyzed how innovation is driven across different sectors and crafted this article to highlight the key trends and opportunities shaping the future of AI.

AI unlocks unprecedented underwriting value through non-traditional data processing

The most promising AI investments in underwriting target the opportunity in reducing mispriced risk. Algorithms now process thousands of non-traditional variables that traditional actuarial models miss completely. The emerging gold rush is in proprietary data acquisition strategies that feed these models with unique signals beyond standard industry datasets. We're particularly bullish on computer vision applications that can extract property characteristics remotely, eliminating the need for costly physical inspections while dramatically improving accuracy of risk assessment.

While enabling margin improvements via automated claims handling and fraud detection

Claims processing represents perhaps the largest near-term ROI opportunity in insurtech, with potential margin improvements through AI automation. The value creation formula is straightforward: each percentage point of fraud detection improvement could translate to annual savings industry-wide. We see immediate traction for solutions combining computer vision for damage assessment with natural language processing for claims documentation analysis. The most investable opportunities are emerging at the intersection of these technologies, where end-to-end claims automation platforms can deliver increasing processing rates.

Behavioral prediction engines dramatically reduce acquisition costs

With customer acquisition costs in insurance being high, AI-powered distribution efficiency represents a massive opportunity. The most compelling investment cases are platforms that leverage behavioral prediction engines to identify high-conversion prospects before competitors. The next frontier will be conversational AI that can handle complex insurance consultations with human-like understanding of coverage nuances, effectively democratizing expert-level insurance guidance.

Just as sector-specific applications improve loss ratios and create new premium pools

Sector-specific AI applications are producing the fastest path to market leadership. In auto insurance, companies deploying telematics with behavioral analysis algorithms are decreasing loss ratios below industry averages. Life insurers leveraging continuous underwriting models through wearable data are expanding their addressable market by making coverage accessible to previously uninsurable populations. The cyber insurance sector presents the most asymmetric return profile, where AI that can quantify previously unmodeled risks creates entirely new premium pools..

Finally, dynamic pricing optimization delivers defensible advantages

AI-driven pricing represents the most defensible competitive advantage in insurance. The investment opportunity lies in platforms that balance pricing optimization with regulatory compliance through explainable AI. Dynamic pricing engines that can continuously adjust to market conditions without human intervention are a big opportunity. The next wave of innovation will come from causal inference algorithms that simulate customer responses to price changes, allowing insurers to optimize elasticity at the individual level.

The Future of AI: Key Technologies and Breakthrough Opportunities Transforming Industries

This article explores the major AI technology categories reshaping industries today. From foundational language models to generative content creation, computer vision, robotics, and cybersecurity, it highlights the core innovations driving new use cases and efficiencies. It also emphasizes the growing importance of ethical AI governance to ensure responsible adoption across sectors.

Our methodology involved gathering numerous venture maps from around the world to identify recurring categories and sources of innovation in AI. From this extensive research, we developed the Mandalore AI Techno Venture Map 2025, which captures the current state of the art in AI technology and innovation. Using these insights, we analyzed how innovation is driven across different sectors and crafted this article to highlight the key trends and opportunities shaping the future of AI.

Foundation models and LLMs are transforming language understanding

Foundation models and large language models (LLMs) are revolutionizing machine understanding and generation of natural language. These models serve as the backbone of modern AI, capable of performing a wide range of tasks with minimal supervision. Innovation is happening at multiple levels: from developing new, more efficient architectures, to fine-tuning models for domain-specific applications. Open-source ecosystems and infrastructure tools are expanding access, while autonomous agents and AI copilots are beginning to act independently across productivity tools and enterprise workflows.

Meanwhile, generative AI powers content creation

Generative AI enables machines to create original content across text, images, video, code, audio, and even 3D models. In creative industries, this means automated content production, real-time media editing, and synthetic design. For developers, new AI coding assistants accelerate software development and testing. Audio and music generation platforms provide personalized media experiences, while generative 3D tools transform asset creation in gaming, digital twins, and immersive environments.

At the same time, computer vision interprets visual data

Computer vision allows machines to interpret and act on visual information, unlocking a broad range of applications. In industrial contexts, AI can detect manufacturing defects, monitor quality, and optimize production lines. In healthcare, it assists in analyzing medical imaging to support diagnostics. Vision-based surveillance systems are transforming security operations, while autonomous driving relies on real-time image processing to navigate dynamic environments. Facial recognition and biometrics further extend vision’s reach into authentication and identity verification.

While NLP drives language recognition

NLP technologies extract meaning from unstructured language data. Machine translation tools bridge language barriers across global organizations. Text summarization and information extraction streamline document processing, legal analysis, and research. Augmented search capabilities combine retrieval and generation to provide accurate, context-aware responses in enterprise knowledge systems. In voice, real-time transcription and synthetic voice cloning enable more natural and scalable human-machine interaction.

Additionally, robotics and automation enhance efficiency

AI-driven robotics is reshaping physical work across sectors. Humanoid and task-specific robots are being deployed in manufacturing, retail, and service industries. Warehouses are increasingly automated through intelligent systems that move, sort, and package goods with minimal human input. Edge computing enables real-time decision-making in low-latency environments like vehicles or sensors. Smart city infrastructure leverages AI to manage traffic flow, safety, and urban logistics.

Also, AI in science speeds up drug discovery and materials innovation.

AI is fast becoming a core tool in scientific discovery. In life sciences, it accelerates drug discovery by modeling molecule interactions and predicting treatment outcomes. In material science and chemistry, AI models generate new compounds with specific properties, drastically reducing the time required for R&D. These technologies not only enhance research productivity but also open new possibilities across medicine, energy, and sustainability.

Meanwhile, AI for cybersecurity improves threat detection and protection

Cybersecurity is evolving with AI on both sides of the threat landscape. Security operations are becoming more autonomous, with AI systems detecting and responding to incidents in real time. Deepfake detection and malicious content identification help combat new forms of digital fraud. AI-specific guardrails are emerging to monitor prompt injection, data leakage, and model misuse—ensuring safer deployment of large-scale AI systems.

Still promoting AI Ethics & Governance

As AI becomes more powerful and pervasive, governance frameworks are essential to ensure transparency, fairness, and accountability. Tools that audit model behavior, track data provenance, and enforce compliance standards are being embedded across industries. AI monitoring systems detect drift, bias, and anomalies, while governance platforms help organizations align model development with ethical principles and regulatory requirements.

Corporate Venture Building : un levier stratégique pour les conseils d’administration

À l’ère du digital, la survie des grandes entreprises dépend de leur capacité à innover rapidement. Alors que l'espérance de vie moyenne d'une entreprise est passée de 90 ans en 1935 à un peu plus de 10 ans aujourd’hui, les conseils d’administration doivent désormais jouer un rôle actif dans la transformation de leurs organisations.

Le Corporate Venture Building : une réponse stratégique

Le Corporate Venture Building (CVB) s’impose comme un levier stratégique puissant pour créer de nouvelles sources de revenus tout en renforçant la résilience de l’entreprise. Ce modèle hybride permet de :

• Tirer parti des actifs internes (clients, données, expertise sectorielle…)

• Reproduire l’agilité des start-ups

• Réduire les risques tout en accélérant l’innovation

Selon les experts, les entreprises qui adoptent ce modèle peuvent multiplier par 14 leurs chances de bâtir un business à forte croissance par rapport aux start-ups classiques.

🎯 4 leviers clés pour réussir un programme de Corporate Venture Building

Fixer des objectifs clairs et ambitieux

Définir une vision long terme, des axes de développement prioritaires, et des indicateurs de performance (OKR) est essentiel. Le conseil d’administration doit aussi statuer tôt sur la stratégie : spin-in (intégration au cœur de l’entreprise) ou spin-out (filiale autonome).

Adopter une logique de portefeuille et de financement progressif

Plutôt que de miser sur un seul projet, les entreprises les plus performantes adoptent une approche portefeuille, avec des décisions d’investissement basées sur des étapes clés (stage-gates). Cela permet d'optimiser le capital investi tout en réduisant les risques.

Mettre en place une gouvernance agile

L’un des freins majeurs à l’innovation est la lenteur des processus décisionnels. Pour réussir, il faut donner aux équipes une réelle autonomie, instaurer un cadre clair, et s’inspirer des meilleures pratiques des fonds de capital-risque.

Attirer et fidéliser les meilleurs talents entrepreneuriaux

Le succès d’un corporate venture repose sur ses fondateurs. Il faut savoir attirer des profils entrepreneurs/intrapreneurs et mettre en place des systèmes d’incentives inspirés des start-ups (participations, phantom shares, autonomie stratégique…).

📌 Leçons du terrain : le cas Axiata Digital

Le groupe télécom Axiata a lancé son programme de CVB en 2014. Résultat : des filiales comme Boost (wallet), ADA (data & marketing) ou Aspirasi (micro-financement) ont levé plus de 100 millions de dollars et généré des relais de croissance majeurs.

Leur recette du succès ?
👉 Une gouvernance claire, un capital dédié, des équipes autonomes, et une approche rigoureuse du portefeuille.

✅Pourquoi les conseils d’administration doivent s’impliquer dès aujourd’hui

Dans un monde où l’innovation est une question de survie, les conseils d’administration doivent :

• Challenger la vision long terme

• Soutenir l’investissement dans des projets disruptifs

• Créer un environnement favorable à l’expérimentation et à la prise de risque contrôlée

Le Corporate Venture Building est bien plus qu’un buzzword. C’est une stratégie d’innovation structurée, mesurable et scalable, capable de transformer en profondeur les modèles économiques.

What Are the Characteristics of a Unicorn Founder?

Unicorn founders possess distinct traits and strategies that set them apart in the entrepreneurial landscape. Contrary to the belief that technological innovation is the primary driver of success, evidence shows that effective strategy, leadership, and timing are crucial for building billion-dollar companies. Here are the key characteristics of successful unicorn founders:

1. Strategic Vision

Unicorn founders excel at identifying and capitalizing on emerging trends. They have a keen ability to spot opportunities in the market and navigate their ventures with a strategic mindset. This skill allows them to lead their companies effectively, even in competitive environments.

Example:

• Steve Jobs improved existing technology rather than creating it from scratch, demonstrating that strategic enhancement can lead to substantial success.

2. Focus on Execution Over Innovation

While innovation is important, it is not the sole factor for success. Many billion-dollar entrepreneurs succeed by imitating and refining existing ideas rather than relying on breakthrough technology. They understand that execution and strategy often outweigh raw innovation.

Notable Founders:

• Bill Gates purchased software and enhanced it.

• Jeff Bezos imitated online booksellers and revolutionized e-commerce infrastructure.

3. Independence from Venture Capital

A significant percentage of billion-dollar entrepreneurs—94%—build their businesses without heavy reliance on venture capital (VC). They prioritize maintaining control over their companies, often delaying or avoiding VC funding until they are in a position of strength.

Key Cases:

• Mark Zuckerberg delayed VC involvement to retain control of Facebook.

• Jan Koum bootstrapped WhatsApp before its acquisition for $19 billion.

4. Leadership Skills

Unicorn founders possess strong leadership capabilities that enable them to guide their companies through various stages of growth. They are adept at rallying teams, making pivotal decisions, and executing their vision effectively.

Leadership Insights:

• Founders who remain in control often retain 2x to 7x more wealth compared to those who hand over leadership to professional CEOs after receiving VC funding.

5. Ability to Adapt and Scale

Successful unicorn founders can adapt their strategies to changing market conditions and scale their businesses efficiently. They leverage their understanding of the industry to navigate challenges and capitalize on new opportunities.

Examples of Adaptation:

• Brian Chesky (Airbnb) took the concept of online rentals and significantly improved it, helping landlords maximize their rental potential.

6. Emphasis on Wealth Creation and Impact

Unicorn founders focus not just on building successful companies but also on creating lasting impact and wealth for themselves and their stakeholders. They understand that true success encompasses both financial rewards and positive societal contributions.

Conclusion

The characteristics of unicorn founders challenge the conventional narrative that technology alone drives success. Instead, it is the combination of strategic vision, execution, independence from VC, leadership skills, adaptability, and a focus on impact that defines these exceptional entrepreneurs. As we rethink entrepreneurship education, it is essential to emphasize these traits to cultivate the next generation of successful founders.

How Bending Spoons is Rebuilding Digital Classics: A Blueprint for European Innovation Powerhouses

Case Study: Exploration into Bending Spoons’ Acquisition Strategy and Product-Led Growth Model

This case study draws from verified public sources, press coverage, product updates, and leadership statements surrounding Bending Spoons’ acquisition of Evernote and other well-known consumer apps. The analysis highlights strategic patterns, core principles, and actionable insights for ecosystem builders, founders, and digital product operators exploring innovation through acquisition.

In Brief: What You’ll Learn

• Bending Spoons is a Milan-based tech company building world-class digital products through strategic acquisitions and operational excellence.

• In 2023, it acquired Evernote, one of the most recognizable productivity apps, and has since rebuilt it from the ground up.

• Its model combines deep product expertise with centralized operational infrastructure.

• The company manages a portfolio of widely-used apps like Remini and Splice, reaching over 200 million monthly users.

• This case offers a proven roadmap for scaling software companies through bold acquisitions and thoughtful integration.

---

Bending Spoons quietly built one of Europe’s most downloaded app portfolios, then acquired Evernote

Founded in 2013 and headquartered in Milan, Bending Spoons spent years outside the spotlight building a portfolio of globally used mobile applications. Known for hits like Remini (AI photo enhancement), Splice (video editing), and 30 Day Fitness, the company had become a quiet juggernaut in the consumer tech world.

Then, in late 2022, Bending Spoons made a bold move: it acquired Evernote, the note-taking pioneer that helped define modern productivity. The acquisition was completed in early 2023, marking a turning point, not just for Evernote, but for Bending Spoons’ position in global tech..

It acquired Evernote to reimagine a product millions still rely on

By the time of acquisition, Evernote was no longer top of mind for many users. Once a category-defining app, it had suffered from technical issues, lagging updates, and rising competition from Notion, OneNote, and others.

Bending Spoons didn’t see a legacy product; they saw a foundation worth rebuilding. They immediately began reengineering Evernote’s infrastructure, launching performance upgrades and revamping the user experience. It wasn’t a brand reboot, it was a full product overhaul aimed at returning Evernote to form.

Bending Spoons combines product obsession with an operator-first model

What sets Bending Spoons apart is its ability to operate like a modern tech company and a disciplined acquisition firm all in one.

Its Milan-based team is engineering-led, product-centric, and deeply analytical. When it acquires a product, it doesn’t just rebrand or bundle it reinvests. From core code to monetization mechanics, the company takes ownership of every layer. It centralizes operations, HR, marketing, and infrastructure, to allow product teams to focus.

It’s this blend of operational control and creative freedom that has made it possible to run multiple high-performing apps with small, efficient teams.

Evernote was just one move in a bigger playbook, and more are coming

The Evernote acquisition wasn’t a one-off bet. It was part of a larger strategy. Bending Spoons now manages a portfolio with more than a dozen active products and over 200 million monthly users. These include:

In 2024, Reuters reported that Bending Spoons had raised capital at a $2.55 billion valuation and was considering a U.S. IPO. It now sits among Europe’s most valuable and profitable consumer app builders.

Bending Spoons moves quickly, reinvests deeply, and builds for longevity

Key advantages of the Bending Spoons model:

• Centralized operations: Core functions like finance, HR, and data science are shared across apps.

• Deep product refactoring: Legacy apps are rebuilt to perform like new.

• Cohesive team culture: Hiring is rigorous, and most team members work from the Milan HQ.

• Focus on long-term retention: Rather than chase installs, apps are optimized for subscriber lifetime value.

• Selective M&A: The company acquires only when it sees lasting product potential.

This model gives acquired products like Evernote a true second life, not just a rebrand, but a re-foundation.

Bending Spoons offers a powerful case for European tech leadership

In a world where most top consumer apps are based in the U.S. or China, Bending Spoons is a standout. It's proving that European tech companies can scale globally without leaving their principles or their headquarters behind.

Its approach is neither flashy nor growth-at-all-costs. It's deliberate, product-led, and relentlessly operational. For other tech ecosystems looking to nurture world-class innovation, Bending Spoons offers a blueprint grounded in smart talent, long-term thinking, and conviction around product excellence

Conclusion: Bending Spoons isn’t chasing headlines; it’s rewriting playbooks

What’s most impressive about Bending Spoons isn’t just what it’s built, it’s how quietly and intentionally it has done it.

While others chase blitz-scaling or viral hype, this Milanese firm is quietly transforming well-known software products and returning them to best-in-class quality. And it’s doing so while building a company that’s profitable, disciplined, and increasingly global.

The future of consumer software doesn’t belong only to Silicon Valley. And if Bending Spoons has anything to say about it, the next great productivity revolution may just start in Milan.

Cap Table Management and Adverse Talent Selection: Navigating the Startup Growth Minefield

What Is a Cap Table and Why It Matters

A cap table tracks ownership stakes, including founders, employees, investors, and option holders. It determines who owns what—and by extension, who has power and incentives. A clean, transparent cap table is essential for:

• Attracting investors

• Retaining top talent

• Making strategic decisions

The Link Between Cap Tables and Talent

Early hires are often granted equity in lieu of high salaries. But if the cap table becomes bloated or unbalanced, top talent may be disincentivized. For example:

• Too little equity left in the option pool = weak incentive for new hires

• Over-diluted founder stakes = loss of strategic vision

• Complex or unclear ownership = legal or trust issues

This can result in adverse talent selection—where top candidates decline offers due to poor equity packages or unclear growth prospects, leaving the company with suboptimal hires.

Avoiding Adverse Selection

• Plan the Option Pool Early: Allocate enough equity for future hires. Revisit regularly.

• Balance Stakeholder Interests: Align investor returns with talent retention.

• Be Transparent: Clearly communicate equity value, vesting schedules, and growth potential.

• Seek Legal Expertise: Poorly structured cap tables can have long-term legal and tax consequences.

Long-Term Cap Table Strategy

Managing a cap table isn’t just about this round—it’s about the next 5 to 10 years. Founders should:

• Model dilution scenarios in advance

• Keep clean records and use tools like Carta or Pulley

• Align equity strategy with business milestones

Conclusion

Cap table management is one of the most underappreciated disciplines in startup building. Done well, it becomes a growth enabler. Done poorly, it becomes a silent killer. When combined with smart hiring strategies and transparent communication, it lays the foundation for sustainable growth and a high-performing team.

Studio Structures: Building for Scalability and Resilience

The traditional startup model often puts founders on a lonely, risky path. But there’s a new approach gaining traction: venture studios. These startup studios—or company builders—are redefining how companies are launched and scaled.

What Is a Venture Studio?

A venture studio is an organization that creates startups from scratch. Unlike accelerators or incubators that support existing startups, studios identify market opportunities, assemble teams, and develop products internally. Once a venture is validated, it is spun out with funding and a dedicated team.

This structure centralizes support functions—such as marketing, finance, HR, and legal—enabling new startups to hit the ground running. It’s a system designed for scalability, speed, and resilience.

Key Benefits of the Studio Model

• Operational Efficiency: Shared services reduce overhead and allow startups to focus on product-market fit.

• De-risked Innovation: Ideas are tested systematically, reducing the chance of premature failure.

• Talent Pool: Studios attract top-tier talent who can rotate between projects or take leadership roles.

• Faster Time-to-Market: With processes and resources already in place, new ventures can launch quickly.

Building for Scalability

Studios are designed to build not just one successful company—but multiple. This requires:

• Repeatable Processes: Standardized systems for validating, launching, and scaling ventures.

• Cross-functional Teams: Experts in design, engineering, growth, and operations working in sync.

• Robust Infrastructure: Tools and frameworks that allow each startup to scale independently.

• Ensuring Resilience

• Resilience is about adaptability, especially in uncertain markets. Studio structures offer:

• Pivot Flexibility: Centralized oversight allows quick changes in direction when needed.

• Capital Efficiency: Shared resources help conserve cash.

• Learning Loops: Failures from one venture become lessons for the next.

A New Era of Entrepreneurship

Studios are not for everyone—but for mission-driven founders who want to build fast and learn faster, they offer a compelling model. With the right leadership and vision, venture studios can become innovation engines, capable of launching multiple high-growth businesses with reduced risk and increased resilience.

Private Equity in Company Building: Fueling Long-Term Growth

Private equity (PE) is often associated with large-scale buyouts, corporate restructuring, and financial engineering. However, in recent years, PE has increasingly positioned itself as a powerful partner in company building. Rather than simply optimizing existing businesses, many private equity firms are now focused on creating long-term value through hands-on operational support, strategic planning, and growth acceleration.

Understanding Private Equity’s Evolving Role

Historically, private equity was primarily viewed as a financial tool—buy a company, optimize it, and sell it at a profit. While this remains part of the playbook, the role of PE is evolving. Today’s investors are increasingly hands-on, bringing in talent, tools, and methodologies that help startups and growth-stage companies scale sustainably.

These investors are not just financiers; they act as co-builders. They offer deep expertise in areas such as market expansion, talent acquisition, technology integration, and operational efficiency. This model of active ownership is becoming a core element of modern private equity.

Why Private Equity Matters in Company Building

PE firms bring a unique set of advantages to the table:

• Capital Injection: Provides the necessary funding for product development, talent acquisition, or market expansion.

• Strategic Guidance: Helps refine go-to-market strategies and unlock new revenue streams.

• Operational Support: Offers access to a network of experts who can support execution across sales, finance, HR, and more.

• Governance and Accountability: Introduces performance metrics and milestones to ensure progress is measurable and continuous.

This combination of capital and capability makes private equity a strategic ally for founders and executives looking to scale their ventures.

Case Study: From Startup to Market Leader

Consider a SaaS startup with a strong product-market fit but limited resources to scale. A private equity firm steps in, not only providing capital but also bringing in a new COO, revamping the sales strategy, and introducing OKRs (Objectives and Key Results). Within two years, the company expands into three new markets, doubles its revenue, and becomes a category leader.

This illustrates how PE firms can shift from being reactive investors to proactive builders.

Challenges and Considerations

Despite the benefits, founders should be cautious:

• Loss of Control: PE involvement often comes with board seats and voting rights.

• Short-Term Pressure: Some firms may push for rapid returns over sustainable growth.

• Cultural Fit: Not all PE firms align with startup culture and vision.

Choosing the right partner is crucial. Founders should look for investors who understand their vision and are committed to long-term value creation.

Final Thoughts

Private equity in company building represents a strategic evolution in the investment landscape. With the right partnership, it can offer far more than funding—it can be a catalyst for growth, innovation, and long-term success.

Company Building in the Next Innovation Cycle: Embracing the Future

If the last innovation cycle gave rise to unicorns powered by cloud software, mobile-first products, and direct-to-consumer brands, the next one will look and feel different. Today, builders are working against a backdrop of AI breakthroughs, climate urgency, shifting labor models, and economic pressure to scale responsibly, not recklessly.

So, what does successful company building look like in this next phase? It’s more intentional, more human, and far more collaborative than before. Here’s what founders, operators, and ecosystem leaders need to know.

Think Beyond Technology, Start with Systems

While AI and automation dominate headlines, the real winners in this cycle will think in systems, not just features. They’ll build for resilience, design for circularity, and operate with inputs from diverse communities.

That means moving beyond point solutions. The next wave of builders will ask: How does this company improve the system it exists within? Whether that’s a supply chain, a talent pool, or an entire sector.

Companies like Figma and Notion didn’t just offer productivity tools—they created new standards for how people collaborate. That’s the level of systemic thinking that endures.

Embracing Technological Convergence

The rapid advancement of technologies such as artificial intelligence (AI), machine learning, and quantum computing is redefining the boundaries of what's possible. Companies are now leveraging these tools not just for efficiency but to create entirely new value propositions. 

For instance, AI agents are evolving from simple assistants to autonomous entities capable of complex decision-making, impacting industries from healthcare to finance. This technological convergence demands that companies remain agile, integrating emerging tools into their operations and staying ahead of the curve.

Prioritizing Sustainable Innovation

Sustainability is no longer a buzzword but a business imperative. Consumers and stakeholders alike are holding companies accountable for their environmental and social impact. 

In response, forward-thinking organizations are embedding sustainability into their core strategies, from supply chain management to product design. This shift not only addresses global challenges but also opens up new markets and opportunities for growth.

Fostering a Culture of Continuous Learning

In the face of rapid change, a company's ability to learn and adapt becomes its greatest asset. Building a culture that encourages experimentation, values feedback, and embraces failure as a learning opportunity is crucial. Such environments empower employees to innovate and drive the company forward.

Organizations that invest in upskilling their workforce and promoting cross-functional collaboration are better positioned to navigate the complexities of the modern business landscape.

Leveraging Data-Driven Decision Making

Data has become the lifeblood of modern enterprises. Harnessing data analytics enables companies to make informed decisions, personalize customer experiences, and identify emerging trends. However, with great power comes great responsibility. Ensuring data privacy and ethical use is paramount.

Companies that strike the right balance between data utilization and ethical considerations will build trust and gain a competitive edge.

Building Resilient and Adaptive Structures

The unpredictability of today's world, from global pandemics to geopolitical tensions, underscores the need for resilience. Companies must design structures that can withstand shocks and adapt to new realities. This involves diversifying supply chains, investing in digital infrastructure, and developing contingency plans.

Resilient organizations not only survive disruptions but often emerge stronger, having turned challenges into opportunities.

Embracing Collaborative Ecosystems

No company operates in isolation. The next innovation cycle emphasizes the importance of collaborative ecosystems, where businesses, startups, academia, and governments work together to drive progress. Such collaborations foster knowledge sharing, accelerate innovation, and create synergies that benefit all parties involved.

Engaging in these ecosystems allows companies to tap into diverse perspectives and resources, fueling their growth and adaptability.

Conclusion

The next innovation cycle presents both challenges and opportunities. Companies that proactively adapt, embrace technological advancements, and prioritize sustainability and learning will not only navigate the complexities of this new era but thrive within it. By fostering resilience, leveraging data responsibly, and engaging in collaborative ecosystems, businesses can build a future-ready foundation poised for sustained success. 

This Is a Cycle for the Builders Who Care! The next innovation cycle isn’t just about what you can make, it's about why you’re making it, how you build it, and who benefits from it.

If you’re building something right now, you’re doing it in one of the most exciting (and challenging) environments in decades. There’s more noise, more tools, more complexity. But there’s also more need, more urgency, and more opportunity to lead with purpose.

Liquidity Along the Path to Exits: Smart Moves for Founders and Investors

Understanding Liquidity Before the Exit

For years, liquidity in startups meant one thing: wait for the big exit. Whether through an IPO or an acquisition, that was the long game for everyone involved: founders, employees, and investors alike. But today’s startup landscape is different. Companies are staying private longer. Funding cycles have expanded. And liquidity, once a distant milestone, is becoming a necessary tool along the way. In this post, we will explore how liquidity works before the exit, the options available to founders and early stakeholders, and what you need to consider if you're building or investing in a company with a long road to a traditional exit.

Why Liquidity Matters More Than Ever

Startups are maturing differently now. Ten years ago, companies like Facebook went public in under a decade. Today, many high-growth businesses operate privately for 10, even 15 years. That long timeline can make it difficult for early employees and investors to access any return on their equity, often their most valuable asset. 

Pre-exit liquidity. It's become a lifeline for founders and team members looking to fund new ventures, pay taxes on stock options, or simply achieve personal financial goals. For investors, it’s a way to de-risk a long-term position without abandoning support for the company.

The Rise of Secondary Transactions

One of the most common ways to unlock liquidity is through secondary sales, when existing shareholders sell their shares to new investors.

Secondary sales don’t generate capital for the company, but they do serve a vital purpose: allowing founders, employees, and early backers to realize value without forcing a company into an early exit.

Platforms like CartaX, Forge, and EquityZen have made this easier by streamlining transactions and verifying pricing. Secondary markets are now playing a bigger role in the startup economy, especially in later-stage companies where demand from outside investors remains high.

Equity-Backed Loans: Borrowing Without Selling

Another liquidity option gaining traction is loans backed by startup equity. In this model, individuals use their shares as collateral to access cash, often without selling a single share.

Here’s how it works:

• A founder or early employee borrows from a lender based on the current valuation of their equity.

• The loan typically carries interest and is structured to be repaid at the time of an eventual exit or liquidity event.

• Some companies even offer internal lending programs as a benefit to key team members.

While this option avoids dilution and keeps cap tables intact, it does carry risks, especially if the company’s valuation drops or an exit is delayed. Still, for those confident in the future of their startup, it’s a compelling way to stay invested and financially flexible.

Private Equity as a New Liquidity Channel

Traditionally, private equity firms entered the picture much later, usually post-exit. But today, many PE firms are acquiring minority stakes in growth-stage startups, offering direct liquidity to founders and early investors.

This approach has become especially appealing in tech. Firms like KKR, General Atlantic, and Insight Partners are investing in companies that may not go public for years but have strong fundamentals and clear revenue models. These investments give the startup fuel to grow, while giving shareholders a chance to take some chips off the table.

Best Practices for Startup Liquidity

If you're considering liquidity for yourself or your team, here are a few best practices to keep in mind:

1. Get Clear on the Company’s Position: Liquidity should support growth, not signal weakness. Ensure the company is in a strong financial and strategic position before exploring options.

2. Protect the Cap Table: Too many secondary sales or poorly timed loans can impact the cap table and scare off future investors. Maintain transparency and cap table hygiene.

3. Understand the Tax Implications: Secondary sales and equity-backed loans can have complex tax consequences. Involve a tax advisor early in the process.

4. Communicate with Stakeholders: Be transparent with your board, co-founders, and team. Liquidity decisions affect everyone, not just the seller.

Final Thoughts: Liquidity Is Now Part of the Growth Journey

Liquidity is no longer a one-time event at the end of a company’s story—it’s now a thoughtful part of the journey. Founders don’t need to wait a decade to see the value they’ve built. Employees shouldn’t have to walk away from great companies just to pay down loans or fund life goals.

As long as it’s managed with care, liquidity can strengthen startups, fuel new ventures, and keep everyone motivated along the way.

Why Traditional Insurance Companies Should Embrace Venture Studios: Insights from Mandalore Partners

The insurance industry, traditionally characterized by caution and risk aversion, is facing unprecedented challenges from technological advancements and changing consumer expectations. To remain competitive, insurance companies must innovate—and venture studios offer a compelling pathway.​

The Need for Innovation in Insurance

Emerging technologies, such as artificial intelligence and blockchain, are disrupting traditional insurance models. Consumers now demand personalized, digital-first experiences, and new entrants are capitalizing on these trends. To keep pace, insurers must explore innovative solutions.​

Mandalore Partners provides a Venture Capital-as-a-Service (VCaaS) model that enables insurance companies to incubate startups focused on insurtech solutions. This approach allows insurers to experiment with new products and distribution channels without disrupting core operations.​

Real-World Applications: Success Stories

Several insurance companies have successfully engaged with venture studios:​

• AmFam Ventures: Developed by American Family Insurance, this venture studio focuses on insurtech innovations, providing both minority investments and majority ownership in startups to better serve stakeholders.

• ARK Venture Studio: Combining a venture studio, think tank, and venture fund, ARK builds insurance-enabled businesses to tackle systemic risks to people and the planet.

Strategic Advantages for Insurers

Engaging with a venture studio offers multiple benefits:​

• Accelerated Innovation: Rapid development of new products and services.​

• Risk Management: Controlled experimentation minimizes potential disruptions.

• New Revenue Streams: Venture studios allow exploration of adjacent business models.

• Future-Proofing: Adapting to tech shifts before they become industry standards.

For insurers looking to thrive in a fast-evolving landscape, venture studios represent not just a trend—but a strategic imperative.

From Paris to Singapore: Mandalore Partners' Cross-Border Approach to Venture Building

In an increasingly interconnected world, the ability to navigate diverse markets is crucial for startup success. Mandalore Partners leverages a cross-border approach to venture building, fostering innovation that transcends geographical boundaries.​

The Importance of Cross-Border Collaboration

Cross-border collaboration enables startups to tap into new markets, access diverse talent pools, and leverage varied regulatory environments. By understanding and adapting to different cultural and business contexts, venture studios can create solutions with global relevance.​

Mandalore Partners operates from Paris to Singapore, embodying this global perspective. Their partnerships, such as with Temasek's Menyala, highlight the benefits of cross-border collaboration in accessing new markets and talent pools.​

Real-World Applications: Success Stories

Several venture studios have successfully implemented cross-border strategies:​

• X, The Moonshot Factory: Formerly Google X, this venture studio focuses on ambitious projects with global impact, such as self-driving cars and delivery drones.

• FasterCapital: This venture studio emphasizes cross-border partnerships, enabling startups to scale across borders by aligning with overseas partners and tapping into diverse markets. 

Strategic Advantages of a Global Approach

Adopting a cross-border approach offers multiple benefits:​

• Market Diversification: Reducing dependency on a single market.​

• Talent Acquisition: Accessing a broader pool of skills and expertise.​

• Innovation Synergy: Combining diverse perspectives to foster creativity.​

• Regulatory Navigation: Understanding and leveraging different regulatory environments.​

The Future of Global Venture Building

As globalization continues to shape the business landscape, venture studios like Mandalore Partners are well-positioned to drive innovation that resonates across borders, fostering startups that are both locally grounded and globally scalable.​

Beyond Capital: How Mandalore Partners Drives Value Creation in Venture Studios

While capital investment is a cornerstone of startup development, the venture studio model offers a more holistic approach to value creation. By providing strategic guidance, operational support, and access to networks, venture studios like Mandalore Partners play a pivotal role in nurturing startups from inception to success.​

The Comprehensive Support of Venture Studios

Unlike traditional venture capital firms, venture studios are deeply involved in the day-to-day operations of startups. They assist in assembling founding teams, refining business models, and navigating market challenges. This hands-on approach ensures that startups are well-equipped to achieve product-market fit and scale effectively

Mandalore Partners exemplifies this model by offering a suite of services beyond funding. From strategic mentorship to market insights and talent acquisition, Mandalore ensures that each project is poised for success.​

Real-World Applications: Success Stories

Several venture studios have demonstrated the value of comprehensive support.
High Alpha: Combining company building with venture funding, High Alpha partners with corporations to bring ideas to market, providing resources and support needed for growth. 

• FutureSight: This venture studio focuses on forming new ventures, creating significant equity value through its operation as a co-founder, and providing strategic and operational support.

Strategic Advantages for Startups

Engaging with a venture studio offers multiple benefits:​

• Accelerated Development: Streamlined processes from ideation to execution.​

• Expertise Access: Guidance from seasoned entrepreneurs and industry experts.​

• Resource Optimization: Efficient allocation of resources and capital.​

• Network Leverage: Connections to potential partners, customers, and investors.

The Future of Value Creation

As the startup ecosystem becomes increasingly competitive, the comprehensive support offered by venture studios like Mandalore Partners will be instrumental in driving sustained growth and innovation.​