How AI companies are valued — and why it changes
Finro's AI Research Hub brings together valuation benchmarks, market analysis, and financial modeling insights across the AI ecosystem. Built from real transaction and modeling work — not generic industry commentary.
AI Valuation Multiples Database — Q1 2026
A structured database covering AI public companies, private startups, and M&A transactions. Built from real valuation work — not scraped market commentary.
The most current AI valuation benchmark available from Finro. Covers 575 companies across 15 niches with EV/Revenue multiples segmented by public comps, private funding rounds, and M&A transactions — plus funding stage breakdowns from Seed through Series D+.
- 575 AI companies across 15 niches
- Public, private, and M&A transaction data in one framework
- EV/Revenue, median, 25th/75th percentile by niche and stage
- Core AI vs Applied AI segmentation (Infrastructure, LLM Vendors, Agents, Cybersecurity, Health Tech, and more)
- Quarter-over-quarter comparison: Q4 2025 vs Q1 2026
- Source links for every data point
How we analyze AI valuation trends
Finro's research focuses on what actually drives AI startup value — not headline multiples alone, but the revenue mechanics, growth efficiency, and capital intensity that separate durable businesses from narrative-driven ones.
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 over time.
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 that flatters early-stage narratives.
Niche-specific multiples
Agents vs infra vs vertical AI
AI is not one category. We benchmark by niche, margin profile, and revenue quality — so comparisons are actually meaningful rather than averaging across structurally different business models.
All AI valuation datasets
Every edition published by Finro, from the most current Q1 2026 release to earlier benchmark updates.
| Dataset | Companies | Date | Price | |
|---|---|---|---|---|
| AI Valuation Multiples: Q1 2026 Update Latest | 575 | Jan 2026 | €150 | View dataset → |
| AI Valuation Multiples: Q4 2025 Update | 565 | Oct 2025 | €99.90 | View dataset → |
| AI Agents Valuation Multiples: Mid-2025 Edition | 210 | Aug 2025 | €79.90 | View dataset → |
| AI Valuation Multiples Database: Q1 2025 Update | 400+ | Apr 2025 | €79.90 | View dataset → |
| AI Agents Valuation Multiples Database: 2025 Edition | 180+ | Mar 2025 | €49.90 | View dataset → |
| AI Valuation Multiples Database: 2025 Edition | 180+ | Jan 2025 | €49.90 | View dataset → |
| AI M&A Valuation Multiples Database: 2025 Edition | 90+ | Jan 2025 | €44.90 | View dataset → |
AI valuation analysis from the research desk
Selected analysis on AI multiples, growth mechanics, and valuation logic — the same thinking applied in live Finro engagements.
Workflow ownership and monetization clarity are separating winners from the pack. Cycle-over-cycle analysis across AI agents, infrastructure, and vertical AI using real public, private, and M&A data.
Read analysis Market structure · Q1 2026How public comps, private rounds, and M&A price Core vs Applied AI differently — and why the premiums in infrastructure and LLM vendors persist while applied segments compress.
Read analysis Market update · Q1 2026Widening dispersion as investors reward efficiency, monetization, and durable growth. The flagship quarterly update covering how the AI market repriced from Q4 2025 to Q1 2026.
Read analysis Valuation advisoryHow to construct defensible valuation ranges for AI startups — structured risk analysis, comparable selection, and the assumptions investors will actually challenge in fundraising and M&A.
Read analysisAI valuation and financial modeling that holds up in real conversations
The datasets give you the market context. Finro's advisory work turns that context into a defensible valuation range and financial model that can hold up in investor diligence, board discussions, and M&A conversations.
AI Startup Valuation
Transaction-grade valuation work anchored in real AI market comps, explicit assumptions, and scenario logic.
- Fundraising and pre-money valuation support
- Valuation ranges tied to real AI niche benchmarks
- M&A positioning and buyer-side conversations
- Scenario-backed outputs investors can challenge
AI Financial Modeling
Driver-based financial models built around how AI businesses actually grow — usage economics, retention mechanics, and capital needs.
- Fundraising-ready model and investor outputs
- Usage-based and seat + consumption revenue logic
- Capital efficiency and burn analysis
- Assumptions investors can interrogate directly
Typical first step: a 15–20 minute strategy call. No obligation. Every call is with Lior directly.