Data trust is the confidence that the data feeding your decisions and AI is accurate, governed, and used only as permitted — verified at the moment of use rather than assumed. IndyKite continuously evaluates trust using live context, provenance, and Trust Score to provide a measurable indicator of confidence for every dataset.

Data governance defines policies and manages data assets. Data trust applies those policies together with provenance, context, and trust signals to determine whether information can be confidently used for a particular purpose.

IndyKite evaluates data against a live knowledge graph, weighing signals such as provenance, freshness, sensitivity, and consent. TrustScore converts these signals into a measurable indicator of confidence, helping AI systems use only data that is verified, permitted, and fit for the task at hand

Context-aware controls allow organizations to securely share sensitive data across teams, partners, and B2B ecosystems while preserving governance, provenance, and trust. Data remains protected and appropriate use can be enforced consistently across organizational boundaries.

Every data decision is recorded and fully traceable, allowing organizations to prove what data was used, where it originated, under what conditions it was accessed, and why. By capturing provenance and maintaining a queryable history, IndyKite helps turn compliance into a continuous, provable process rather than a periodic review exercise.