AI technical due diligence

AI technical due diligence

Technical due diligence on AI companies

You may be considering making an investment in a startup that claims to use machine learning/AI and would like an impartial assessment of their technology. We can perform an evaluation of a company’s technology stack. This should be done in tandem with a traditional due diligence exercise. You can download our AI due diligence checklist.

Some of the points we will look at include:

  • is the product a real product and capable of being sold as is, or just a demo?

  • how viable and scalable is the technology long term?

  • where will the data for the AI come from? If from users, then does the product suffer from the cold start problem?

  • can the product scale in the real world?

  • how reproducible is the product?

  • how sustainable are the development workflows?

  • are code and models documented and under version control?

  • are the founders’ credentials and experience valid and as claimed?

  • is there any crucial employee, or exceptionally talented employee on whom the business depends?

  • is the team well-balanced with complementary experience, or have the founders recruited individuals with the same profile?

  • how robust is the organisational structure, does the company have a low bus factor?

  • how is the technology licensed?

  • how will costs scale as the operation scales?

  • if we are talking about a healthcare or medical device, is the product likely to need licensing?

  • how reproducible is the technology, irrespective of patents and legal protection?

  • what are the future risks from a technology perspective?

You can read more here about how technical due diligence can help you, and how Fast Data Science conducts technical due diligence on AI companies.

We have broken down machine learning due diligence into code and product due diligence, model, data, IP, workflow and people.

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