Venture Capital Intelligence Report
December 22, 2025 • Synthesizing insights from top-tier VCs
VCs see a bifurcated market: AI infrastructure winners taking massive share while application layer sees fierce competition. Public market tech rally (NVDA +3.9%, AMD +6.2%) signals continued AI infrastructure demand, but VCs are selective on valuations post-ZIRP era.
Funding remains available for proven AI companies but Series A bar significantly higher. Pre-seed/seed active for infrastructure plays. Growth rounds compressed 30-40% from 2021 peaks but stabilizing.
AI infrastructure commands premium multiples (15-25x revenue), while SaaS+AI seeing 8-12x depending on AI integration depth. Consumer social/fintech seeing multiple compression.
The picks-and-shovels play for AI gold rush. Model training, inference optimization, and developer tooling seeing massive demand as enterprises deploy AI at scale.
AI agents that can actually complete workflows end-to-end in specific verticals. Moving beyond chatbots to autonomous task completion.
Not just adding AI features to existing software, but rebuilding enterprise workflows from first principles with AI at the core.
Institutional adoption driving need for enterprise-grade crypto infrastructure. Stablecoins, custody, and compliance tooling seeing renewed interest.
IRA funding and corporate climate commitments creating massive market for carbon removal, clean energy manufacturing, and industrial decarbonization.
AI will be as transformative as the internet, but we're still in the dial-up era. Infrastructure investments today will compound for decades.
2025 is the year AI moves from science projects to production workloads. Companies that can handle enterprise deployment complexity will capture outsized value.
The next platform shift isn't just about better AI models, it's about AI that can actually take actions and complete workflows without human intervention.
IRA and corporate climate commitments have created a $1T+ market opportunity for climate tech manufacturing. The winners will be those who can scale production.
AI applications that combine multiple models, tools, and data sources rather than relying on a single large model
Single model limitations becoming apparent, need for specialized tools and data integration growing
$100B+ market as enterprises build sophisticated AI workflows
Early signals from: Sequoia, Greylock, Index
Companies to watch: LangChain, Dust, Fixie
Chips and hardware designed specifically for AI workloads, not adapted from general computing
Moore's Law slowing, AI compute needs exploding, NVIDIA supply constraints
$500B hardware market transformation over next decade
Early signals from: a16z, Kleiner, General Catalyst
Companies to watch: Groq, Cerebras, SambaNova
Platforms that automate compliance and regulatory reporting across multiple jurisdictions
Regulatory complexity exploding across AI, crypto, privacy, and ESG domains
$50B+ market as every company needs compliance automation
Early signals from: Bessemer, Lightspeed, Accel
Companies to watch: Vanta, Drata, SecurityScorecard
Using engineered biology to manufacture everything from materials to medicines to food
Costs plummeting, AI accelerating bio-engineering, climate pressure increasing
$1T+ transformation of manufacturing over 2 decades
Early signals from: General Catalyst, Kleiner, Breakthrough Energy
Companies to watch: Ginkgo Bioworks, Zymergen, Perfect Day
Previous: Red hot during 2020-2021 lockdowns → Now: Significantly cooled, few new investments
User acquisition costs skyrocketing, platform risk from iOS changes, harder monetization in competitive landscape
What Changed: TikTok dominance and Apple's privacy changes fundamentally shifted unit economics
VCs Cautious: Benchmark, Greylock, General Catalyst
Previous: Massive sector 2019-2021 → Now: Selective investments only in specialized niches
Rising interest rates killed growth models, credit quality concerns, incumbent bank competition
What Changed: ZIRP era ended, making lending unit economics much harder
VCs Cautious: Accel, Index, Lightspeed
Previous: Reliable investment category for decade → Now: Must have clear AI differentiation
Market saturation, AI making many tools obsolete, buyers consolidating vendors
What Changed: AI agents can now do what many SaaS tools used to do
VCs Cautious: Bessemer, Lightspeed
Focus on workflow transformation, not feature addition. Users want AI to eliminate entire steps, not just make existing steps faster.
💡 Map out user workflows and identify which steps can be completely automated, not just assisted
— Benchmark - Sarah Tavel
Enterprises are buying AI transformation, not AI tools. Lead with business outcome metrics, not model performance.
💡 Build ROI calculators showing specific cost savings or revenue increases, not accuracy percentages
— Sequoia - Roelof Botha
Don't compete on foundation model performance - compete on data, distribution, and domain expertise.
💡 Identify unique data sources or distribution advantages rather than trying to build better general models
— Greylock - Reid Hoffman
Hardware climate solutions need to plan for manufacturing scale from day one - R&D mindset kills companies.
💡 Build manufacturing partnerships and supply chain relationships before Series A, not Series C
— Unknown VC
Deal volume down 40% YoY but quality up significantly. AI deals commanding premium valuations while traditional SaaS seeing compression. Series A bar highest in 5 years - companies need clear traction and differentiation.
Series C • Lead: Amazon • Others: Google, Spark Capital
Largest AI round of year, shows big tech doubling down on AI model competition
AI Foundation ModelsSeries I • Lead: Andreessen Horowitz • Others: NEA, Coatue
Record valuation for data platform, AI integration driving massive enterprise demand
AI/Data InfrastructureSeries F • Lead: Accel • Others: Tiger Global, Dragoneer
AI training data becoming critical bottleneck, Scale positioned as picks-and-shovels winner
AI Data InfrastructureAcquisition by Private Equity • Key investors: Accel, CapitalG, Sequoia
RPA market consolidating as AI agents make traditional automation obsolete
Blocked Acquisition • Key investors: Greylock, Index, Kleiner
Regulatory scrutiny increasing for big tech acquisitions, VCs need alternate exit paths
AI bubble will burst by 2026 - most applications don't create enough value to justify current valuations
Most VCs believe AI is transformational and early innings
Reasoning: AI improvements are incremental, not transformational. Market has priced in perfection.
Their Bet: Reduced AI exposure, increased focus on hard tech and manufacturing