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Review & Risk Analysis

Deep Audit — three models, cross-verified

Live

Run a contract past Claude, GPT and Gemini in parallel, then reconcile the three readings into one report.

What you get
  • Three model vendors reading the same contract independently
  • A reconciliation pass that merges them into one report
  • Per-upload choice, so the cost is spent where it matters
  • Roughly three times the token cost of a standard analysis
+1 more capabilities below
Overview

What it is.

Switch a single upload into deep mode and the analysis does not go to one model. Claude, OpenAI and Google each read the contract in parallel, and a reconciler pass merges the three readings into one report — so a finding that only one model saw is visible as exactly that, rather than presented with the same confidence as one all three agreed on.

It costs roughly three times the tokens of a standard analysis and takes longer, which is why it is a per-upload choice rather than the default. Use it on the contracts where being wrong is expensive.

How it works

Three steps.
End to end.

01
1. Choose deep mode on upload

A per-upload setting, not an account-wide one. Standard analysis stays the default.

02
2. Three readings in parallel

Claude, OpenAI and Google each analyse the contract independently, section by section.

03
3. One reconciled report

A merging pass produces a single cross-verified report rather than three you have to compare yourself.

Capabilities

What you get.

  • Three model vendors reading the same contract independently
  • A reconciliation pass that merges them into one report
  • Per-upload choice, so the cost is spent where it matters
  • Roughly three times the token cost of a standard analysis
  • All three vendors disclosed in the sub-processor list, and all three hard-disabled in air-gapped deployments
FAQ

Quick answers.

Is it more accurate?

It is more cross-checked, which is not the same claim. Three independent readings surface disagreements a single pass would have hidden; we are not going to put an accuracy percentage on it, because we have not measured one.

Does the extra spend show in my usage?

Partly. Anthropic tokens are logged per request; the OpenAI and Google calls on this path are not in that log, so your recorded cost understates a deep run. That gap is named on the Cost transparency page too.

Related

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Upload a ZIP of contracts and run the full analysis across all of them in one job.

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