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AI Controls & Guardrails

No model training on your data

Live

We do not train models on customer content without explicit opt-in. Default is off.

What you get
  • Opt-out by default at the organisation level
  • Per-org toggle with audit trail
  • Sub-processor terms align (Anthropic API does not train on inputs)
  • Revocation respected for future runs
Overview

What it is.

Your documents are not used to train, fine-tune, or improve any model unless you explicitly opt in. The default for every organisation is off. Even our sub-processors (Anthropic) honour this — their consumer-grade training-data policies don't apply to API customers like us.

If you want to opt in (e.g. to help us tune the Indian-law model in exchange for early access), it's a per-organisation toggle in admin settings with a clear acknowledgement.

How it works

Three steps.
End to end.

01
1. Default off

New organisations are opted out by default. No action needed.

02
2. If you opt in

Per-organisation toggle in Admin → AI. Clear acknowledgement required.

03
3. Revoke anytime

Toggle off and content already processed is excluded from future training runs.

Capabilities

What you get.

  • Opt-out by default at the organisation level
  • Per-org toggle with audit trail
  • Sub-processor terms align (Anthropic API does not train on inputs)
  • Revocation respected for future runs
FAQ

Quick answers.

What about ML telemetry — model latency, error rates?

We collect aggregated, content-free telemetry to monitor model health. No customer content leaves to power this — only timings and error categories.

Related

More in AI Controls & Guardrails.

Prompt injection defence
Live

User-pasted text is sanitised before reaching the LLM.

Per-org cost guardrails
Live

Daily and monthly cost ceilings per organisation. Soft warnings, hard cutoffs.

Prompt caching
Live

Stable prompt prefixes are cached. Faster responses, lower bill, passed to you.

Token cap per request
Live

200K input / 8K output limits with graceful truncation and a clear notice.

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