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Artificial Intelligence Valuation Multiples

Explore private market Artificial Intelligence valuation multiples with benchmarks structured by stage and region. Updated quarterly.

Coverage
EV/Sales; EV/EBITDA
Valuation Multiples
Private Market
Benchmarks
Stage & Region
Adjustment
Quarterly
Updated
Sector Profile

Artificial Intelligence

Artificial Intelligence companies software, infrastructure, and applications that enable prediction, automation, and decision support at scale. Private market AI valuations are often influenced by model differentiation, data advantages, compute intensity, and the ability to translate innovation into repeatable commercial traction.

The category spans foundational models, applied AI products, workflow copilots, and enabling infrastructure. DealMatrix tracks valuation dynamics across 7 funding stages and all major global regions, updated every quarter.

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Model Differentiation
Investors often assign premiums where technical performance, proprietary tuning, or workflow integration creates defensible product value.
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Data Advantage
Access to unique datasets, feedback loops, and domain-specific training signals can improve product quality and strengthen moat assumptions.
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Compute Economics
Margin profiles and scaling potential depend heavily on inference efficiency, infrastructure costs, and pricing power.
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Commercialisation Speed
Valuations increasingly reflect which AI companies can move from experimentation into recurring production deployments.

Sector

AI

Software & Data

Sector tracked since

2000

25+ years of data

EV/SALES & EV/EBITDA ACROSS

6 Regions · 7 Stages

Modelled independently via proprietary econometric approach

UPDATE FREQUENCY

Quarterly

Data updates & model improvement

Private Market

AI Valuation Multiples

Select a region and funding stage to preview how Artificial Intelligence companies are valued in private markets. Full data available on the platform.

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Methodology

The Venionaire DealMatrix Multiples Model

DealMatrix multiples are derived through a five-step model combining public capital market comparables, proprietary VC/PE/M&A transaction data, and macroeconomic indicators.

The model produces three components: The reported public multiple, the model-predicted multiple, and the lower bound predicted multiple averaged into the DealMatrix Composite, then adjusted for region and funding stage. The methodology follows the IPEV Guidelines 2025.

Read full Methodology
Model Architecture
Step 1: Data Acquisition
↓
Step 2: Data Cleaning
↓
Step 3: Econometric Modelling
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Step 4: Multiple Averaging
↓
Step 5: Region/Stage Adjustment
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Final DealMatrix Multiples
Following IPEV Guidelines 2025
Deals Monitor
Latest AI Deals
April 7, 2026

9fin Series C: 9fin raises $170M at $1.3B valuation to scale AI platform for debt markets

raised

USD 170m

Valuation

USD 1.3b

Region

Stage

Read more →
March 30, 2026

Granola Series C: Granola raises $125M, hits $1.5B valuation as it expands from meeting notetaker to enterprise AI app

raised

USD 125m

Valuation

USD 1.5b

Region

Stage

Read more →
March 16, 2026

AMI Labs Funding: Ex-Meta AI chief Yann LeCun’s AMI Labs raises $1.03 billion for alternative AI approach

raised

USD 1.03b

Valuation

USD 3.5b

Region

Stage

Read more →
February 23, 2026

FYLD Raises $41 Million Series B to Accelerate the Delivery of Large-Scale Infrastructure Projects with AI

raised

USD 41m

Valuation

Region

Stage

Read more →
February 2, 2026

Parloa Raises $350M Series D at $3B Valuation

raised

USD 350m

Valuation

USD 3b

Region

Stage

Read more →
January 19, 2026

Parloa Raises $350M Series D at $3B Valuation

raised

USD 350m

Valuation

USD 3b

Region

Stage

Read more →
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