LLM Data Shield: Pseudonymization & Egress Gate

October 28, 2026

An LLM security layer that keeps customer names, identifiers and business data from ever reaching the external model — and measures leakage on every release instead of assuming it away.

The Model Never Knows the Customer — Yet Still Answers the Question

The cost of adding AI to business software is usually invisible: the user's question, the table on screen, the record a tool returns — all of it leaves inside a prompt. Motice Shield narrows that path to a single gate. Everything bound for the model passes through it first, and in any undefined situation nothing is sent.

Inside the gate runs an in-memory pseudonym vault, scoped to each conversation turn and each business. Ayşe Yılmaz reaches the model as "Customer-1" and becomes Ayşe Yılmaz again on the user's screen as the answer streams back. The user's question, the screen context, the system instructions and tool outputs — all four outbound channels pass through the same rules. Tool output without a manifest declaring which fields may be shared never reaches the model at all.

Trust is tied to the provider contract too. Unless no-training, no-retention, data region and the legal basis under Turkish data-protection law (KVKK) are on record, not a single call is made with real data. The model may only use record IDs it actually saw in that turn — a rule we added after measuring that one invented branch ID could make 11 bookings show up as "0".

How It Works

• Per-turn, per-business pseudonym vault, rehydrated in the response stream
• Egress control on four channels: question, screen context, system prompt, tool output
• Field manifests: undeclared data is withheld from the model by default
• Fail-closed egress gate: no call without policy, purpose context and decision log
• Provider contract evidence: training, retention, data region and KVKK checks
• ID-provenance gate: the model may only use identifiers it has actually seen

We Measure the Leakage

We do not hide the residual risk. Every release runs the same role-based question set and reports leaked pseudonyms, output withheld from the model, latency and token cost. Security becomes a test result, not a claim.

Where We Use It

Ask Motice, the AI assistant inside Motice — our platform for pilates, yoga and studio businesses — runs behind this layer. Its core was designed as a package independent of Motice's business rules, so the same protection can move to other products.