AI Valuation Research & Market Analysis

Finro’s AI Research Hub brings together valuation benchmarks, market analysis, and financial modeling insights across the AI ecosystem.

Instead of generic industry commentary, we focus on what actually drives startup value: revenue models, growth mechanics, capital efficiency, and comparable transactions across public companies, private startups, and M&A deals.

Built for founders, investors, and operators who want to understand how AI companies are valued — not just how they are described.

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AI Valuation Multiples Database

A structured database covering AI public companies, private startups, and M&A transactions. Built from real valuation work — not scraped market commentary.

  • 565+ AI companies across 15 niches
  • Public, Private, and M&A transaction data
  • EV/Revenue, EV/EBITDA, funding benchmarks
  • Cycle-over-cycle valuation analysis
Explore AI Valuation Multiples → View methodology →

How We Analyze AI Valuation Trends

Finro’s research focuses on revenue mechanics, growth efficiency, capital intensity, and how valuation actually evolves across AI niches, not headline multiples alone.

Revenue model dynamics
Pricing logic • Usage economics • Recurring revenue
AI valuation is tightly linked to monetization mechanics: usage-based pricing, API economics, seat + usage hybrids, and how recurring revenue actually compounds.
Growth efficiency
CAC payback • Retention • GTM scalability
Multiples follow efficiency. We focus on unit economics, retention quality, and capital efficiency, not just growth rate as a standalone metric.
Niche-specific multiples
Agents vs infra vs vertical AI
AI is not one category. We benchmark valuation by niche, margin profile, and revenue quality so comparisons are actually meaningful.

What’s Inside the AI Valuation Multiples Database

The database is structured for real comps work: clean segmentation, consistent metrics, and source-ready fields.

What you get
  • Company coverage: public companies, private startups, and M&A transactions
  • Niche tagging: agents, infra, vertical AI, data, dev tools, security, and more
  • Valuation fields: EV, revenue, EBITDA (when available), funding, and implied multiples
  • Comparable filters: stage, business model, margin profile, and revenue quality signals
  • Cycle tracking: compare multiples across updates and market regimes
  • Source trail: structured notes so every number is defensible
How people use it

Built for investors and founders who need comps that hold up in a real conversation, not a screenshot of a headline multiple.

Pre-money benchmarking
Board / IC memos
M&A comps
Round pricing sanity checks
Narrative support
Scenario framing
Explore AI Valuation Multiples → Ask a question →
Typical next step: send the stage + niche, and we’ll point you to the right comparable set.

Latest AI Valuation Insights

Selected analysis on AI multiples, growth mechanics, and financial modeling logic used in real valuation work.

AI Valuation Dataset
AI Agent Valuation Multiples — Q1 2026 Benchmarks
Cycle-over-cycle analysis across AI agents, infrastructure, and vertical AI companies using real public, private, and M&A data.
Explore dataset →
Financial Modeling
Financial Modeling for AI Startups: What Investors Actually Look For
How usage economics, retention, and capital efficiency shape AI financial models — beyond top-down growth projections.
Read analysis →
AI Valuation Services
Valuation Strategy for AI Startups: From Benchmarks to Investor Positioning
How Finro approaches AI valuation across fundraising, M&A, and strategic planning — combining market data with defensible modeling.
See how we approach valuation →
Work with Finro
AI valuation and financial modeling that holds up in real investor conversations
If you’re fundraising, preparing for diligence, or refining your strategy, we’ll map the drivers that actually move AI multiples and turn them into a clear, defensible valuation narrative and model.
  • Benchmark against real public, private, and M&A comps
  • Make assumptions explicit, testable, and scenario-backed
  • Align modeling outputs with what investors will challenge
Typical next step: a 15 to 20 minute strategy call.
Schedule a Call Or send a message