AI Research Hub

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.

Featured dataset

AI M&A Multiples by Funding Stage, Q2 2026

A transaction-level dataset focused on when AI companies get acquired, how acquisition multiples change by funding stage, and where buyers are most active across the AI market.

AI M&A Multiples by Funding Stage: Q2 2026

Finro’s latest AI M&A dataset analyzes 156 AI and AI-adjacent acquisitions across 14 niches. The workbook includes target funding stage, buyer, niche, AI layer, transaction value, revenue, funding raised, EV/Revenue, EV/EBITDA, EV/Funding, and source links where available.

  • 156 AI and AI-adjacent acquisition transactions
  • 14 AI niches, including Infrastructure, Data Intelligence, Cybersecurity, Marketing Tech, Computer Vision, HR Tech, Health Tech, Fintech, Legal Tech, and PropTech
  • Funding-stage analysis from Seed through Series H, IPO/Public, PE-owned, and bootstrapped targets
  • EV/Revenue, EV/EBITDA, and EV/Funding multiples where inputs are available
  • Buyer analysis covering repeat acquirers and acquisition patterns
  • Core AI versus Applied AI classification for every target
156 Transactions
14 AI niches
€79.90 One-time purchase
Broader AI valuation benchmark: Q1 2026

For users looking beyond M&A transactions, Finro’s broader AI Valuation Multiples Database covers 575 AI companies across 15 niches, including public companies, private funding rounds, and M&A transactions in one comparable framework.

  • 575 AI companies across 15 niches
  • Public, private, and M&A valuation benchmarks
  • Core AI versus Applied AI segmentation
  • EV/Revenue, median, and percentile ranges by niche and stage
575 Companies
15 AI niches
€99.90 One-time purchase
Research methodology

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.

Dataset archive

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 M&A Valuation Multiples: Q2 2026 Update Latest 575 Jan 2026 €99.90
AI Valuation Multiples: Q1 2026 Update 575 Jan 2026 €99.90
AI Valuation Multiples: Q4 2025 Update 565 Oct 2025 €99.90
AI Agents Valuation Multiples: Mid-2025 Edition 210 Aug 2025 €79.90
AI Valuation Multiples Database: Q1 2025 Update 400+ Apr 2025 €79.90
AI Agents Valuation Multiples Database: 2025 Edition 180+ Mar 2025 €49.90
AI Valuation Multiples Database: 2025 Edition 180+ Jan 2025 €49.90
AI M&A Valuation Multiples Database: 2025 Edition 90+ Jan 2025 €44.90
Work with Finro

AI 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
Explore valuation services

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
Explore financial modeling

Typical first step: a 15–20 minute strategy call. No obligation. Every call is with Lior directly.