Build an automated compliance auditor where AI agents inspect data, record every reasoning step in a tamper-evident chain-of-thought (CoT) ledger, and produce audit-ready reports. Every decision is hash-chained with SHA-256, creating an immutable record that can be verified for integrity at any time.
Build a data operations pipeline where AI agents create isolated branches for speculative queries, test schema changes safely, and merge results back -- all without affecting production data. HatiData's branch isolation uses DuckDB schema-based separation with copy-on-write semantics for instant branch creation.
Build a retrieval-augmented generation system where AI agents query structured data via SQL and semantic memory through a single HatiData connection. This playbook demonstrates how to combine SQL queries with vector-based memory search to give agents persistent, context-aware reasoning.