Blind(L)LM™

Let any LLM operate on encrypted data

BlindInsightOrchestrator intercepts a natural-language prompt, translates it into encrypted queries or BlindML model runs, and returns aggregate results to the LLM—which never receives raw records. Keys are scoped to the minimum required for the session and revoked when it ends.

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Prompts route through the encrypted query layer

The orchestrator sits between your LLM and your encrypted data store. It issues queries against ciphertext, collects aggregate results, and passes only those aggregates to the model. The model receives counts, ratios, and inference outputs—not records.

blind_llm — orchestrator 
from blind_llm import BlindInsightOrchestrator

orc = BlindInsightOrchestrator(backend=proxy_backend)
r = orc.run("Cancer rate for women 60+ with dense breast tissue?")
# LLM sees only aggregate counts — no raw records
print(r.answer)
Blind(L)LM workflow Source customer data flows through a Blind Proxy into an encrypted data warehouse, is queried by Blind(L)LM which orchestrates BlindML models or any LLM through scoped key grants, and returns plaintext results only to authorized humans. Source data Any structured source Blind Proxy Never sees plaintext Encrypted EDW Field-level encryption Blind(L)LM™ Orchestrator Rule-based key orchestration BlindML (L)LMs Agents Humans Zero accuracy loss
Blind(L)LM architecture: prompt enters the orchestrator, gets translated to encrypted queries against the data store, and returns aggregate results to the LLM — the model never receives raw records.

Minimum key set. Session-scoped revocation.

The orchestrator assigns the minimum set of decryption keys the agent needs for the current prompt. At session end, access is revoked—not just the bearer token, but the specific decryption capability granted to that session.

Minimum key set
Scoped per session, not per user
Session revocation
Decryption capability revoked at session end
Aggregate-only responses
LLM receives counts and ratios, not records
Any LLM backend
OpenAI, Anthropic, Gemini, Llama, Mistral, Cohere, DeepSeek

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