Venture Capital Intelligence Report
December 29, 2025 • Synthesizing insights from top-tier VCs
VCs see a bifurcated market: premium valuations for proven AI companies while non-AI startups face continued pressure. Tech mega-caps showing resilience with NVDA up 1% and stable cloud hyperscaler demand.
Flight to quality continues with Series A funding down 35% YoY but mega-rounds ($100M+) in AI infrastructure holding steady. VCs prioritizing revenue growth and path to profitability over pure growth metrics.
Down rounds becoming normalized; AI companies maintaining 20-40x revenue multiples while SaaS multiples compressed to 8-15x. Foundation model valuations cooling from 2024 peaks.
The picks-and-shovels play for AI gold rush. Infrastructure for model training, inference optimization, and AI developer tooling seeing massive demand as enterprises scale AI workloads.
AI agents for specific industries showing strong product-market fit. Legal, sales, customer support, and healthcare agents delivering measurable ROI with enterprise adoption accelerating.
Geopolitical tensions driving defense spending. Dual-use technologies in autonomous systems, cybersecurity, and space infrastructure attracting both commercial and government contracts.
Industrial decarbonization and energy transition creating massive infrastructure opportunities. Carbon removal, industrial heat pumps, and grid optimization seeing strong demand.
AI-driven drug discovery and development accelerating timelines from 10+ years to 3-5 years. Computational biology platforms showing early clinical successes.
Every enterprise software category will be rebuilt from the ground up with AI-native architectures, creating $1T+ in value creation over the next decade
Market rewarding sustainable unit economics and capital efficiency over growth-at-all-costs; companies need 40%+ gross margins and clear path to profitability
Europe's regulatory-first approach to AI creating competitive advantages in enterprise sales; GDPR experience translating to AI governance leadership
Security platforms built from the ground up to defend against AI-powered attacks and secure AI systems themselves
Rise of AI-generated deepfakes, automated social engineering, and model poisoning attacks creating new threat vectors
$50B+ TAM as AI adoption scales across enterprises
Early signals from: a16z, Greylock, Accel
Companies to watch: Robust Intelligence, HiddenLayer, Calypso AI
Platforms that manage and orchestrate AI agents as virtual employees, with scheduling, performance monitoring, and task delegation
AI agents becoming sophisticated enough to handle complex multi-step workflows autonomously
$100B+ as AI agents replace traditional software workflows
Early signals from: Kleiner, Lightspeed, Bessemer
Companies to watch: Multi-On, Adept, Rabbit
Using engineered biology to manufacture everything from materials to pharmaceuticals at industrial scale
AI breakthroughs in protein design making biological manufacturing economically viable
$1T+ manufacturing market addressable
Early signals from: Breakthrough Energy, Founders Fund, DCVC
Companies to watch: Ginkgo Bioworks, Zymergen successors, Modern Meadow
Previous: Red hot in 2021-2022 with massive valuations → Now: Funding down 70% from peak
User acquisition costs skyrocketing, Apple's ATT impact persisting, and shifting user behavior toward AI tools over traditional social
What Changed: CAC payback periods extended beyond VC fund lifecycles; focus shifted to AI-native social experiences
VCs Cautious: Benchmark, Lightspeed, General Catalyst
Previous: Billions invested in 2021-2022 → Now: 90% down from peak funding levels
User retention challenges, tokenomics complexity, and regulatory uncertainty dampening institutional interest
What Changed: Focus shifted to infrastructure and real-world asset tokenization over gaming speculation
VCs Cautious: a16z crypto, Paradigm, Haun Ventures
Don't build a chatbot wrapper—build proprietary datasets and fine-tuned models that create defensible moats
💡 Focus on data network effects and model specialization rather than general-purpose AI applications
— Benchmark
CROs demanding proof of ROI within 90 days; pilot programs must show measurable productivity gains
💡 Design products with built-in analytics that quantify business impact from day one
— Sequoia
Show 18-month runway minimum and clear milestones for next round; bridge rounds becoming toxic
💡 Raise for longer runway and hit profitability milestones before next fundraise
— Index
Hire senior enterprise sales talent early; product-led growth alone insufficient for B2B AI
💡 Bring in enterprise sales VP by Series A, not Series B
— General Catalyst
Deal volume down 40% YoY but average check sizes up 25% as VCs concentrate on fewer, higher-conviction bets. AI infrastructure deals averaging $50M+ rounds while traditional SaaS struggling to raise above $10M
Series A • Lead: a16z • Others: Sequoia, DST
Largest Series A in history signals continued appetite for foundational AI research despite market conditions
AI ResearchSeries C Extension • Lead: Google Ventures • Others: Spark Capital, Salesforce Ventures
Constitutional AI approach gaining enterprise traction; Google deepening strategic partnership
Foundation ModelsAcquisition • Key investors: Accel, CapitalG, Sequoia
RPA + AI integration driving premium valuations; automation market consolidating around AI-native platforms
Foundation model companies will become utilities with razor-thin margins
Most VCs see foundation models as the next Google/Microsoft
Reasoning: Commoditization inevitable as model performance converges; real value in applications and specialized models
Their Bet: Avoiding foundation model investments, doubling down on vertical AI applications
Physical world robotics will scale faster than digital AI agents
Software-first AI will dominate next decade
Reasoning: Manufacturing labor costs rising globally while robot costs falling; physical automation has clearer ROI
Their Bet: Heavy investments in industrial robotics and autonomous systems
First $100B AI infrastructure company will emerge by 2027
HIGHa16z • Timeframe: 24-36 months
Implications: Will likely be GPU cloud alternative or model serving platform; creates new category of infrastructure leaders
50% of Series A rounds will be AI-related by Q2 2025
MEDIUMIndex • Timeframe: 6 months
Implications: Non-AI startups will struggle to raise; market bifurcation accelerating
Regulatory approval for AI agents in healthcare by 2026
SPECULATIVEKleiner • Timeframe: 12-18 months
Implications: Unlocks $500B+ healthcare AI market; creates new category of digital therapeutics
Indicator of enterprise AI adoption velocity and willingness to pay premium pricing
If growing 100%+ QoQ, validates high enterprise willingness to pay for AI
If growth slowing, suggests enterprise AI adoption hitting constraints
Leading indicator of AI infrastructure investment demand
Continued acceleration signals AI buildout far from peak
Deceleration suggests AI infrastructure spending cooling
Shows whether valuation correction has bottomed for non-AI companies
Stabilization suggests funding environment normalizing
Continued decline means more down rounds and shutdowns ahead