Patent-Pending Technology

Private by Design Retrieval-Augmented Generation

Private AI that delivers real answers — without exposing your data.

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Patent-Pending

The AI Privacy Tradeoff — Managed

Every AI system today forces the same choice: useful AI or private AI. If the AI can search your documents, it can read them. If it can read them, so can the people who run the servers. We built an architecture that manages this tradeoff — minimizing exposure to the smallest possible window — and filed a provisional patent application on it.

Unfamiliar with technical terms? We've got you covered.

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Layered Encryption

Your data stays encrypted — even from us

Multiple layers of cryptographic keys protect your data, each governing a different scope of access. No single key unlocks everything. No single party, including us, holds the complete set. Root keys live in dedicated hardware security modules.
 

Key rotation updates all stored data server-side in seconds. No re-uploading, no re-processing.
 
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Mathematical Isolation

AI searches your data without reading it

Each knowledge store gets its own cryptographically isolated search space. AI finds what's relevant with full accuracy, but the search operates on transformed representations, not your actual content. Cross-store comparison produces only random noise.

Search accuracy matches plaintext baselines. The mathematical transformations preserve the geometric relationships that make search work.
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Encrypted Knowledge Store

Everything you do builds your encrypted knowledge store

Every document, note, and conversation becomes part of your encrypted knowledge store, searchable and compounding over time. When you ask a question, AI searches your transformed embeddings without decrypting anything. Only the specific items needed are decrypted in volatile memory for the duration of response generation. That working memory is then overwritten at the byte level. Your data is always stored. It's just never exposed.

System operations are immutably logged for audit and compliance. No user content is ever included in logs.
 
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Privacy-First AI Routing

Internal AI first. Anonymized when external.

Every query gets decomposed, context is gathered from your documents, conversation history, and external sources as needed. Most of the time, our internal AI handles the full response without anything leaving our environment. When complex reasoning requires an external model, explicit PII like names, birthdates, and addresses is always anonymized first. The meaning survives. The identity doesn't.
 

Routing is automatic based on query complexity. Simple lookups stay internal; complex reasoning routes externally with full amazonymization.

Built to Be Verified, Not Just Trusted

We don't ask you to take our word for it. The architecture is designed so that privacy properties are structural, built into the mathematics, not added as a policy layer.

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Patent-Pending

Our Private by Design Retrieval-Augmented Generation architecture is the subject of a filed provisional patent application, not a marketing claim.

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Hardware-Backed Keys

Your encryption keys live inside Google Cloud's FIPS 140-2 Level 3 certified hardware security modules (HSMs). Tamper-resistant chips where private keys are stored and can't be extracted without your authorization.

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Auditable by Design

Every key derivation, access event, and destruction is immutably logged. Privacy isn't a promise. It's a verifiable property.

What This Means for You

These are properties of the architecture itself, not policies that can be changed.

Your data can't be read without you — decryption requires your key
AI search works with full accuracy on encrypted content
No decrypted copy of your data ever exists at rest
No single party holds complete key material
Cross-store data leakage is statistically negligible
Every operation is immutably audited

Experience it firsthand.

See how Private by Design RAG works in practice. Join the beta and try it yourself.

What to expect from the beta?