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Whitepaper
Explainability You Can Defend
AI is already embedded into high-stakes workflows. But when outcomes are challenged, most organizations can’t prove why they happened. In this whitepaper, Seekr’s Dr. Stefanos Poulis, Chief Technology and AI Officer, and Dr. Andrew Bauer, VP of Applied AI, outline a defensibility standard built on evidence of influence, not logs or generated explanations. Download the whitepaper to learn how to build AI systems you can explain, challenge, and defend under scrutiny. What you’ll learn:
Why logs and observability fall short, and what “receipts” reveal about what actually drove an AI outcome.
A look inside the four properties of credible explanations: plausibility, faithfulness, consistency, and sufficiency.
A practical architecture for multi-layer attribution and contestability across context, data, and model behavior.
Download the explainability whitepaper
[Whitepaper] Explainability You Can Defend
Explainability You Can Defend: Why Receipts, Not Logs, are the Missing Control Layer for AI in Production
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