“We can finally see what leaves the model. Sensitive context is redacted before it ever reaches a response, and the security team no longer has to slow product teams down.”
Priya Raman
Head of Platform Security, Helix
01 // OVERVIEW
Sensitive context was moving through untracked AI workflows
Helix had rolled out AI assistants across support, claims and internal operations. Each team connected the systems it needed, and prompts routinely carried customer records, clinical notes and account context.
Nothing inspected what went into a prompt or what came back out, so exposure risk grew with every new workflow.
THE CHALLENGE
Internal AI workflows could surface regulated data without any inspection layer in between.
02 // Objective
Put an inspection layer between the model and the data
Helix needed to keep the productivity gains while guaranteeing that regulated data never left the boundary it belonged to.
The objective was an inspection layer that worked at runtime, applied the same rules everywhere, and produced an audit trail regulators could read.
03 // Solution
Classification, redaction and continuous evidence
1. Data Classification
Every prompt and response was classified in real time, so the team could see exactly which categories of sensitive data were moving through which workflow.
2. Automatic Redaction
Regulated fields were masked before they reached the model and before a response reached a user, without breaking the usefulness of the answer.
3. Continuous Evidence
Every decision was logged with its policy, its classification and its outcome, giving compliance a complete record instead of a sampled review.
