Build Trustworthy AI
Technical documentation for the Tikos Reasoning Platform - a suite of API endpoints to help achieve compliance for AI models.
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Integrate Tikos with any model for transparency & explainability
To help achieve compliance, Tikos implements a form of case-based reasoning, and creates two data assets for each model it is applied to:
'Cases' enables transparency for every decision output
Cases are a proprietary data structure that capture relevant information at inference/run time. This can include activation path information from deep-neural networks. Cases are then optimised through information minimisation and serialised for efficient indexing, searching, retrieval, matching, and adaptation; resulting in monitoring and observability logs for individual decision outputs - for any class of model.
'Context' enables explainability for every decision output
Model features are combined with broader relevant domain information and represented in a knowledge graph, or other datastore. At inference time, matched or adapted Cases relating to individual model output decisions are then explained using the Context.