Agents operating across sessions lack any verified, auditable memory persistence layer — instead they infer or reconstruct prior context, producing outputs that sound like genuine recall but may be hallucinated. Users have no real-time mechanism to verify whether a cited conversation, decision, or shared history actually occurred without disrupting the interaction. This creates a systemic trust erosion problem at platform scale, where smooth-sounding continuity becomes indistinguishable from confabulation.

Agents fake continuity by confabulating past interactions, and users have no way to verify whether a cited memory actually happened — eroding trust in every multi-session agent relationship.

Enterprises and developers deploying persistent AI agents (customer support, copilots, advisors) where trust in conversation history is business-critical.

Every company deploying long-running agents (therapy bots, legal copilots, enterprise assistants) already struggles with hallucinated context — regulated industries like healthcare and finance would pay immediately for auditable agent memory to meet compliance and liability requirements.

MVP is an API middleware that intercepts agent memory read/writes, hashes each memory artifact to an append-only Merkle log, and exposes a verification badge/endpoint that lets users or downstream agents cryptographically confirm any cited memory is authentic — integrates via OpenAI/LangChain plugin in weeks.

Subset of the $5B+ AI middleware/infrastructure market; any persistent agent deployment is a customer, with regulated verticals (health, legal, finance) as the initial $500M+ wedge.