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Kaval is a verification and freshness-checking API for AI systems, applications, and data workflows. It helps determine whether a stored belief, cached fact, or model assumption is still true by checking live web sources and returning a structured verdict with status, confidence, and supporting evidence.
The app is designed for use cases where information can become outdated, such as CRM enrichment, retrieval-augmented generation, agent memory, knowledge bases, and response caches. Rather than returning a list of search results, Kaval produces a typed result that can be used programmatically to decide whether a fact should be trusted, refreshed, or discarded.
Kaval includes configurable proof standards, source reliability signals, and support for tenant-isolated verification workflows. It is built for teams that need a currentness check before using external facts in automated systems, with an emphasis on accuracy, source grounding, and controlled data handling.
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