Venture Capital Intelligence Report
February 17, 2026 • Synthesizing insights from top-tier VCs
VCs are bullish on AI's long-term potential but increasingly selective after 2023-2024's AI funding frenzy. Focus has shifted from foundation models to application layer and infrastructure optimization.
Series A+ rounds face heightened scrutiny with emphasis on unit economics. Pre-seed/seed remain active for AI applications. Growth rounds limited to proven revenue traction.
AI infrastructure seeing compression from 2024 peaks. Enterprise SaaS multiples stabilizing around 8-12x ARR for quality assets. Consumer social remains challenging.
The picks-and-shovels play for AI deployment at enterprise scale. Focus on observability, model management, and cost optimization tools.
AI-native solutions for specific industries with defensible data moats and workflow integration.
Hardware-heavy climate solutions becoming investable as manufacturing costs decline and policy tailwinds strengthen.
B2B fintech tools enabling embedded finance and next-gen banking infrastructure, especially for AI-native companies.
AI-powered development tools and platforms serving the growing population of AI/ML engineers and applications.
The shift from chat interfaces to autonomous agents will create trillion-dollar market opportunities
After the AI bubble, focus returns to fundamental business metrics and sustainable competitive advantages
AI tools enable 2-3 person teams to build what previously required 20+ engineers
Climate technologies are reaching cost parity with traditional solutions, creating massive commercial opportunities
Europe's privacy-first approach and regulatory framework create advantages in enterprise AI adoption
Tools for monitoring, debugging, and ensuring compliance of AI systems in production
Enterprise AI deployments hitting scale, regulatory pressure mounting
$50B+ market as AI becomes mission-critical
Early signals from: a16z, Greylock, General Catalyst
Companies to watch: Arize AI, Fiddler, Arthur
AI systems that can autonomously complete multi-step business processes
LLM reasoning capabilities crossing threshold for reliable task execution
$500B+ opportunity to automate knowledge work
Early signals from: Sequoia, Benchmark, Index
Companies to watch: Adept, Dust, Sierra
Programming biology like software for manufacturing, medicine, and materials
AI accelerating protein design, cost of DNA synthesis plummeting
$300B+ across pharma, materials, and manufacturing
Early signals from: a16z, Kleiner, General Catalyst
Companies to watch: Zymergen, Ginkgo Bioworks, Modern Meadow
Security solutions preparing for quantum computing threat to current encryption
Quantum computing progress accelerating, NIST standards finalizing
$25B+ security infrastructure overhaul
Early signals from: Kleiner, Lightspeed
Companies to watch: ISARA, PQShield, Crypto4A
Previous: Hot during pandemic/2021 bubble → Now: Significantly cooled
Platform maturity, user acquisition costs, and regulatory uncertainty around data privacy
What Changed: TikTok dominance and iOS privacy changes made user acquisition economics challenging
VCs Cautious: Benchmark, a16z, Lightspeed
Previous: Pandemic darling sector → Now: Selective interest only
iOS changes destroyed FB/Google advertising arbitrage, customer acquisition costs unsustainable
What Changed: Return to retail fundamentals; only brands with strong unit economics surviving
VCs Cautious: Forerunner, Kleiner, General Catalyst
Previous: Consistent VC favorite 2015-2022 → Now: Requires exceptional differentiation
Market saturation and AI threatening to automate many workflow tools
What Changed: AI making many point solutions obsolete; focus shifted to AI-native alternatives
VCs Cautious: Bessemer, Accel
Focus on workflow transformation, not feature enhancement
💡 Build AI-native workflows that couldn't exist without AI, rather than adding AI features to existing tools
— Benchmark
Show path to profitability within 18 months of current runway
💡 VCs want to see clear unit economics and reduced dependency on venture funding
— Sequoia
Bottom-up adoption through developers, not top-down enterprise sales
💡 Build products developers choose to use, then expand to enterprise buyers
— Index
Data network effects are the only sustainable AI moats
💡 Design products that get better with more users/usage, not just more training data
— Greylock
Hire for AI-native thinking, not traditional domain expertise
💡 Look for people who understand how to build products that leverage AI capabilities, not those trying to replicate existing solutions
— a16z
Deal activity remains robust for AI infrastructure and vertical applications, while consumer and horizontal SaaS see continued pullback. Series A rounds taking 6-9 months vs 3-4 months in 2021.
Series D • Lead: Amazon • Others: Google, Spark Capital
Validates continued big tech investment in AI safety and constitutional AI approaches
AI/Foundation ModelsGrowth • Lead: Thrive Capital • Others: a16z, General Catalyst
Shows fintech infrastructure remains attractive despite sector downturn
FintechSeries C • Lead: Kleiner Perkins • Others: Sequoia, OpenAI
Largest vertical AI funding round, validates sector-specific AI applications
Legal AIAcquisition • Key investors: Accel, CapitalG, Sequoia
Automation platforms with clear ROI metrics command premium valuations
IPO • Key investors: Greylock, Kleiner, Index
Design tools with strong network effects can achieve massive scale
Open source AI will dominate, not proprietary models
Most VCs betting on proprietary AI platforms
Reasoning: History shows open source eventually wins in infrastructure; AI will follow same pattern
Their Bet: Invested heavily in companies building on open source AI stack
Hardware-heavy climate tech offers better returns than software
VCs traditionally prefer asset-light software models
Reasoning: Physical world problems require physical solutions; software margins don't matter if market size is enormous
Their Bet: 60% of new investments in hard tech and climate infrastructure
European AI companies will outperform Silicon Valley
US maintains AI leadership
Reasoning: European focus on privacy and regulation creates sustainable competitive advantages
Their Bet: Doubled down on European AI investments, opened larger London office