AI Due

The data-driven analysis of PyThia in combination with the high-end expertise of our AI engineers and advisors help us identify the hidden AI-related risks and opportunities for a given investment, our clients need to understand what’s going on in the AI model/algorithm itself. That’s why we dig deep into the AI model and the data it utilizes in order to help them answer (indicative) questions like:
  • To what extent does the system take into account principles beyond performance measures, such as fairness, explainability, robustness and provenance for the AI component(s) of their platform?
  • Are there any risks related to bias either on the data or the AI system itself?
  • Can one explain in simple terms the decisions made by the system?
  • What is the organisation’s maturity to hold their AI system accountable?
Based on these results, as well as our clients’ own business context, our advisors develop actionable, prioritized recommendations to ensure their objectives stay on track.
An AI Due Diligence engagement with Code4Thought includes important qualitative and quantitative components to tell our client(s) how a company’s AI assets will affect their ability to grow and thrive.
AI risk profile
Identifies and evaluates the risks associated with the target company’s overall approach on adopting AI — not only the obvious main frameworks in use, but also the many supporting technologies such as data analysis and preparation, model’s deployment and so on.
Situational analysis
In such analysis we clarify the future adaptability, scalability, and integration ability of the target company’s AI-model, giving our clients a factual basis to understand the feasibility and likely costs of future growth.
Post-transaction pragmatic improvement roadmap
Our guidance and recommendations are practical, pragmatic and can lead to measurable improvements in PyThia, our AI testing platform. That means you can start your improvement plan right away alongside our guidance and advisory.
Insight into other due diligence streams
The PyThia AI-Testing platform provides a comprehensive overview of all relevant findings around aspects such as the existence of Bias, the provision of explanations and the level of Robustness of a given AI-based system. Whether it’s a business executive accountable for the system’s operation or a machine learning engineer, all stakeholders get the appropriate insight. Especially for the former, the outcome of our work provides experts in other workstreams irreplaceable insights into everything from CAPEX and OPEX projections, to AI system’s functional fit and level of trustworthiness on its way of working.


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