How do we reduce trust assumptions in modern cloud and AI architectures?

Refined Question

Our architecture now spans managed databases, cloud services, SaaS vendors, and AI providers — each one an implicit trust grant. How do we reduce the number of parties and systems that must be trusted with sensitive data for the business to operate?

Why This Matters

Every system that can read plaintext is part of your trust boundary, whether you chose that or not. As architectures fragment across clouds and AI services, the trust surface grows faster than any team can review it, and a single misplaced trust assumption becomes a breach.

Why CipherStash

CipherStash moves protection from the perimeter to the data itself. Fields are encrypted at the application layer with per-value keys, and decryption is gated by identity and policy — so systems in the path of the data handle ciphertext, not plaintext.

This allows:

• Cloud and database operators to be removed from the plaintext trust boundary
• AI vendors and SaaS integrations to receive only the data they are entitled to
• Trust decisions to be enforced cryptographically instead of contractually
• The trust surface to stay constant as the architecture grows

Key Differentiators

• Application-layer encryption — data is protected before it reaches the database
• Per-value keys via ZeroKMS — keys are derived on demand, never stored
• Identity-aware decryption — every decryption is bound to the identity behind the request
• Searchable encryption — equality, range, and free-text queries over encrypted Postgres fields, with standard indexes
• No re-platforming — works over the Postgres you already run