Provenance stamping is the foundation of AI output compliance. In this deep-dive, we'll explore the cryptographic techniques that power our tracking system.

Every AI output that flows through Souma receives a unique cryptographic signature that captures the complete lineage: the prompt, the model, the timestamp, and the organizational context. This signature is tamper-proof and can be verified independently.

We use a combination of hash chains and Merkle trees to create an efficient, verifiable record of every output. This allows us to prove not just what was generated, but the exact conditions under which it was created.

The technical challenge is scale. At millions of outputs per day, traditional database approaches break down. We've developed a novel architecture that combines append-only logs with probabilistic data structures to achieve sub-millisecond stamping times.

Our verification system allows any stakeholder-legal, compliance, or auditors-to independently verify the authenticity and lineage of any output without accessing sensitive model details or prompts.