Regulated enterprise AI workflow demo

Decide what context reaches your LLM.
Before inference, not after.

Deterministic relevance, role, sensitivity, and compression decisions turn a noisy enterprise retrieval set into one lean, governed prompt. Six screens, one worked case — every number measured from the actual pipeline output.

6 screens · measured pipeline

PII engine

Regex and role rules in the control path.

Policy filter

Blocked and irrelevant data never reaches the model.

Audit trail

Every metric is computed from the actual output.

DataAPI control planeawaiting run

> query received: loan repayment review

> retrieved context blocks: 278

> applying OriginChain relevance policy

> masking customer identifiers

> removing risk model output

> assembling governed LLM prompt

PII

masked

Risk

blocked

Audit

clear

Decide what context reaches your LLM.Before inference, not after.

Decide what context reaches your LLM.
Before inference, not after.