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AI Controls & Guardrails

Prompt caching

Live

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

What you get
  • ✓Stable-prefix caching against Anthropic's prompt cache
  • ✓Cache-read and cache-creation tokens broken out in your usage figures
  • ✓Cache reads counted at a tenth against your monthly token allowance
  • ✓The cache lifetime is Anthropic's ephemeral default, not a LexVio setting
Overview

What it is.

We cache the stable prefix of our prompts — system instructions, jurisdiction context, firm style — against Anthropic's prompt cache, sending the stable half marked cacheable and the variable half unmarked. A cache read is billed by Anthropic at a fraction of a fresh input token, and it counts against your monthly allowance at a tenth.

Your usage breakdown shows cache-read and cache-creation tokens separately from ordinary input and output, so you can see the caching working. Be aware of one limit in the cost figure: the cost estimate is computed from input and output tokens and does not currently price cache reads or cache writes, so the saving shows up honestly in the token counts and approximately in the money.

How it works

Three steps.
End to end.

01
1. First call

Cache miss — full cost, full latency.

02
2. Subsequent calls

Cache hit on the stable prefix — ~10% cost, ~half latency.

03
3. See it in your usage log

Cached vs uncached tokens broken out per request, so you can verify the savings.

Capabilities

What you get.

  • ✓Stable-prefix caching against Anthropic's prompt cache
  • ✓Cache-read and cache-creation tokens broken out in your usage figures
  • ✓Cache reads counted at a tenth against your monthly token allowance
  • ✓The cache lifetime is Anthropic's ephemeral default, not a LexVio setting
FAQ

Quick answers.

Does my document content get cached?

No — only the stable prefix (system instructions, jurisdiction context, firm style). Your document content is in the variable half and is not marked cacheable.

Does the cost figure reflect the caching saving?

Not precisely. The cost estimate is derived from input and output tokens and does not price cache reads or writes. The token breakdown is the accurate view of what caching saved you.

Related

More in AI Controls & Guardrails.

Citation verification
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Every citation comes back with a verdict — verified, ambiguous or unresolved — and a match on title alone is never verified.

Statute verification against official sources
Soon

Each legal claim we hold about a jurisdiction is checked against that government's own legislation service — and where it cannot be, the answer is "unverified", not silence.

No model training on your data
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We do not train models on customer content. There is no opt-in, because there is no training programme.

Prompt injection defence
Live

User-pasted text is sanitised before reaching the LLM.

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