A validity layer for AI state that outlives its original data.
Persistara focuses on one enterprise AI control question: when authoritative data changes, is previously derived state still safe to reuse?
What Persistara is
Persistara is a provider-neutral validity-control layer for persistent machine-derived state. It is designed for AI agents, RAG systems and long-running automated workflows where authoritative source data can change after an answer or reusable state has already been created.
Its external control outcome is deliberately simple: REUSE when prior state remains eligible for reuse, REGROUND when a material change requires refresh, and HOLD when validity is unresolved.
What it is not
Persistara does not replace an LLM, memory platform, vector database, retrieval system, Databricks or application-specific domain logic. It sits alongside those systems and focuses on whether previously derived state should still be reused.
Engineering validation → controlled enterprise evaluation
The validation record now spans live changing-data benchmarks, mixed safety testing, a live Databricks App integration, 500-user load, independent replay, failure/recovery exercises and current v1.6.10 enterprise packaging with signed/private deployment validation.
The next commercial evidence gate remains independent shadow-mode validation against a real customer workload, with the customer's existing production system left authoritative.
Persistara does not claim Databricks certification, customer production validation, SOC 2 / ISO 27001 certification or universal production SLOs.