Venture Capital Intelligence Report
February 25, 2026 • Synthesizing insights from top-tier VCs
VCs see selective strength in tech markets, with AI infrastructure spending driving valuations while traditional SaaS multiples compress. Focus shifting from growth-at-all-costs to sustainable unit economics.
Series A crunch continues as VCs demand clearer path to profitability. Seed funding remains active for AI/climate tech. Growth rounds reserved for proven business models with strong fundamentals.
AI infrastructure companies trading at 15-25x revenue, enterprise SaaS at 6-10x (down from 2021 peaks). Early-stage valuations stabilizing after 2023-2024 reset.
The picks-and-shovels play for the AI gold rush. Every enterprise needs AI infrastructure, creating massive TAM with sticky revenue models.
AI agents that automate specific workflows in industries like legal, healthcare, finance are showing clear ROI and customer willingness to pay premium prices.
Policy tailwinds + corporate ESG commitments creating predictable demand. Focus on profitable climate solutions with clear unit economics.
Geopolitical tensions driving defense modernization. Government willing to pay premium for advanced capabilities, creating venture-scalable opportunities.
B2B fintech infrastructure proving more durable than consumer fintech. Banks need modern infrastructure, creating long-term partnership opportunities.
Technology companies serving government and critical infrastructure represent massive underinvested opportunity with predictable revenue streams
Enterprise AI adoption following predictable pattern: infrastructure first, then horizontal tools, finally vertical applications
Climate tech opportunity extends far beyond renewable energy into industrial processes, materials, and agriculture
European startups have structural advantages in regulated verticals like healthcare and finance due to GDPR expertise
Best enterprise AI tools will have consumer-grade UX, driving bottom-up adoption within organizations
Companies building AI compliance and governance tools as regulatory frameworks emerge globally
EU AI Act implementation, US executive orders creating compliance requirements for AI deployment
$50B+ market as every AI deployment needs governance layer
Early signals from: Index, Accel, General Catalyst
Companies to watch: Fiddler AI, Arthur AI, Credo AI
Backend infrastructure for AR/VR applications as Apple Vision Pro catalyzes market
Vision Pro proving enterprise use cases, need for spatial computing cloud infrastructure
$30B+ market as spatial computing goes mainstream
Early signals from: Benchmark, Lightspeed, Greylock
Companies to watch: 8th Wall, Niantic, Looking Glass Factory
AI and robotics applied to bioprocessing and pharmaceutical manufacturing
Pandemic highlighted supply chain vulnerabilities, AI enabling personalized medicine scale
$100B+ opportunity in pharmaceutical manufacturing efficiency
Early signals from: Kleiner, Bessemer, General Catalyst
Companies to watch: Ginkgo Bioworks, Zymergen, Culture Biosciences
AI agents managing financial operations, from treasury to accounting to compliance
CFO workloads increasing, AI reaching accuracy thresholds for financial tasks
$25B+ market replacing manual financial operations
Early signals from: Sequoia, Index, Lightspeed
Companies to watch: Ramp, Brex, Modern Treasury
Previous: Red hot during COVID/2021 boom → Now: Significantly cooled, selective interest only
User acquisition costs skyrocketed, monetization challenges, regulatory scrutiny, market saturation
What Changed: iOS privacy changes killed performance marketing arbitrage, increased focus on business fundamentals over growth metrics
VCs Cautious: Benchmark, Greylock, General Catalyst
Previous: Pandemic darling sector → Now: Cold, few new investments
Customer acquisition costs unsustainable, supply chain disruptions, return to physical retail
What Changed: Unit economics never worked at scale, brand differentiation proved difficult to maintain
VCs Cautious: Forerunner, Lightspeed, Bessemer
Previous: Massive hype in 2021-2022 → Now: Tepid interest, infrastructure-focused only
Play-to-earn models failed, user retention issues, crypto market volatility impact
What Changed: Market realized gaming mechanics more important than tokenomics, focus shifted to traditional gaming with blockchain elements
VCs Cautious: a16z crypto, Paradigm, Haun Ventures
Focus on specific use cases with clear ROI rather than general-purpose AI tools
💡 Pick one vertical, measure business impact in dollars saved/generated, build procurement-ready case studies
— Sequoia Capital
Show path to profitability within 18-24 months, not just growth metrics
💡 Build detailed unit economics model, demonstrate improving contribution margins, have contingency plans for different funding scenarios
— Benchmark
Bottom-up adoption beating top-down sales in current environment
💡 Build for individual users first, let them bring it to their teams, optimize for viral coefficients over enterprise sales cycles
— Greylock
Data moats stronger than algorithm moats in AI companies
💡 Focus on proprietary data collection, build network effects that generate better data over time
— a16z
European expansion critical for AI companies due to regulatory head start
💡 Build GDPR compliance from day one, consider European entity for regulated verticals, hire European go-to-market early
— Index Ventures
Deal volume down 35% YoY but average deal size up 20%. Quality over quantity trend continues with VCs focusing on proven business models and clear paths to profitability.
Series C • Lead: General Catalyst • Others: Lightspeed, Bessemer, Index
Validates continued investor appetite for AI infrastructure at massive scale, despite OpenAI competition
AI Foundation ModelsSeries I • Lead: T. Rowe Price • Others: a16z, Kleiner, Bessemer
Shows crossover investors betting big on AI data infrastructure ahead of likely IPO
Data InfrastructureSeries J • Lead: Sequoia • Others: General Catalyst, Index
Fintech infrastructure proving more resilient than consumer fintech, enabling global expansion
Fintech InfrastructureAcquisition by Microsoft • Key investors: Accel, CapitalG, Dragoneer
Enterprise automation with clear ROI attracts premium valuations from strategic acquirers
IPO • Key investors: Greylock, Index, Kleiner
Design tools with network effects can achieve massive scale, validating bottom-up SaaS model
Most AI startups will fail because they're solving fake problems
AI is transformative technology that will create massive value across all sectors
Reasoning: Real business problems already have solutions. AI applications need to be 10x better, not just marginally better
Their Bet: Investing only in AI applications with measurable business impact, avoiding horizontal AI tools