The TIKOS™ Reasoning Platform technology

Proprietary IP
Regulations 1st Approach
Expert-in-the-Loop
Open Architecture
Enterprise Scale
Flexible Deployment
TIKOS™ creates two data assets for each model: Cases and Context

‘Cases’ enables observability for every decision output
This includes capturing activation path information from deep-neural networks. Cases are then optimised through information minimisation and serialised for efficient Case indexing, searching, retrieval, matching, and adaptation.
This process delivers log level monitoring and observability for individual decision outputs for any model.
‘Context’ enables explainability for every decision output
‘Context’ extends system capabilities from observation to explainability. Model features are combined with relevant domain information and represented in a knowledge graph, or other datastore.
Matched or adapted Cases relating to individual model output decisions are then explained using the Context.
Innovations
TIKOS™ is built on a family of proprietary formal methodologies, mathematical techniques and algorithms designed to work in concert to deploy the system at scale: