Verticals
AI-native SaaS in 2026: valuation, multiples and what differentiates premium assets
AI-native SaaS show 7–10x ARR multiples when they control their model IP. This guide distinguishes true AI assets from "GPT wrappers", a critical valuation distinction.
Not all products that use AI are "AI assets" in the M&A sense. The distinction between a GPT wrapper (interface on a generalised LLM without proprietary IP) and a true AI asset (model fine-tuned on proprietary data, optimised inference infrastructure) is decisive for valuation.
GPT wrapper vs proprietary AI asset
- GPT wrapper: calls the OpenAI API via prompt engineering. No IP on the model. Valuation: 1–3x ARR. Acquirers pay for distribution, not technology.
- Fine-tuning on proprietary data: base model (open source or API) fine-tuned on sector data. Superior performance on target domain. Valuation: 4–7x ARR.
- Internally trained proprietary model: weights owned by company, proprietary corpus. Valuation: 7–15x ARR if exclusive data and defensive moat.
7–10x
ARR multiple AI-native SaaS with proprietary model IP
1–3x
ARR multiple GPT wrapper without proprietary IP
65%+
Real gross margins optimised AI SaaS (post GPU costs)
–25%
Discount for 100% OpenAI API dependency
The European AI Act (applicable since August 2024, progressively until 2027) classifies AI systems in 4 risk levels. An AI SaaS in a "high risk" context (HR, credit, justice, health) must comply with Title III: documented risk management system, event logs, transparency. The S dimension of the Aegryn protocol has integrated these requirements since Q1 2026.
This article was written with the assistance of artificial intelligence and reviewed under Aegryn editorial responsibility. In accordance with Article 50 of the EU AI Act, we assume editorial responsibility for this content.
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