Resource library
Straight technical reads on a target's AI in a live deal -- telling real capability from AI washing, a defensible moat from a wrapper, and what each finding does to price and structure.
Weighing a live deal? Agathon provides independent AI due diligence -- a written assessment you can put in the deal file and stand behind.
How the due diligence worksFeatured guide
Which LLM should you use?Claude, GPT, Gemini and more compared on pricing, context windows and strengths -- with a decision guide to pick the right model. Regularly updated.
The full checklist, free and ungated: 24 questions across six assessment areas that show whether a target's AI is real, defensible and worth the price.
How to tell whether a target's AI is real or marketing, and when a genuine moat that lives in a few people becomes a key-person discount on price.
You're buying a target that calls itself AI. How to tell if the AI is real, whether the moat holds, and what an honest read does to the valuation.
A technical read for investors running diligence on an AI-enabled target: how to spot AI washing, what it does to price, and when it justifies walking.
Pre-LOI technical diligence on an AI-enabled target. The diagnostics that separate a real moat from AI washing, and what each finding does to price.
A technical read on a target's AI inside a live deal: tell real moat from a frontier-model wrapper, and turn the finding into invest, pass, reprice, or walk.
Whether an AI target's data moat is real, illusory, or decaying, and what each finding does to price and deal structure before you sign.
Running diligence on an AI target? How to tell a defensible system from a GPT wrapper, and what the finding does to price and structure.
The plain definition, five outside-in tests that separate a thin wrapper from a real AI product, and an honest answer to when a wrapper is a good business.