Every AI coding tool has the same defect: it forgets. The decisions your team made in March, the migration that failed in April, the constraint a customer contract imposes — each new session rediscovers them, or worse, contradicts them. The industry's answer has been to bolt a memory onto the tool: a vector store here, a chat history there, each one private to one vendor and none of them accountable to your team.

Cratonis inverts that. The memory belongs to the application. Your app's own relational database carries its context — typed records with owners, priorities and visibility scopes, alongside its real identity, stack, history and schema — and compiles it into one instruction document that every agent reads, whichever vendor made it. The tool is a visitor; the application remembers.

That inversion is the subject of a pending patent, and its discipline shapes every part of the product: compilation is deterministic SQL, never similarity search, so what an agent reads is what your team ranked, not what an embedding found nearby. Delivery is dual-channel — a live endpoint and version-controlled files — from one compilation, so there is never a second truth to reconcile. And what an agent writes back is stamped as machine-authored, permanently, because a memory that cannot distinguish a decision from a guess is not a memory.

The boundary we keep

The SaaS platform that provisions and bills tenants holds no tenant context — ever. Your substrate lives in your own application's database, and the separation is enforced by tests that fail our own build if a context-shaped table so much as appears in the platform's schema. The working test we hold ourselves to: delete our platform, and your application keeps working with its memory intact; delete every tenant, and our platform keeps running with nothing of yours inside it.

Where it stands

Cratonis is in early access with design partners. The compiler, both delivery channels, the governed write path and role-based access are built and under continuous adversarial testing; the modules tier and usage metering are the next phases and are sold as such. If your team ships with AI agents and is tired of re-teaching them your own application, we would like to hear from you.