Touchless contract processing for a legal team

The challenge

A representative corporate legal team reviews a high volume of third-party paper, and the first pass is the bottleneck.

Manual first-pass review is slowest exactly when it matters most — during diligence, when volume spikes and deadlines do not move. Deloitte's benchmark for intelligent document processing in finance is 60-80% less processing time and 50-70% lower cost, with extraction accuracy commonly reported in the 90-99% band and heavily workload-dependent.

The risk in this scenario is not throughput alone. It is a missed clause in a long agreement, which is what a consistent, auditable first pass is meant to prevent.

Setting

Representative — corporate legal

System concept

DocuMind

Illustrative duration

14 weeks

The architecture

We deploy DocuMind against the legal team's own document management system. Extraction and clause models are tuned and evaluated on the client's own historical corpus under a signed data agreement and validated against senior attorney review. The system produces a structured first pass — parties, dates, obligations, and deviations from the client's standard positions — with every extracted field linked back to its source span, so a reviewer can verify it in one click. Risk flags are ranked for attorney attention; the system does not approve, sign, or advise.

A proposed delivery path

This sequence illustrates the engagement. The actual scope, timeline and quotation are agreed around your requirements.

Benchmark context

Published figures used to frame this scenario. Baselines describe the referenced setting; targets are illustrative, not measured project outcomes.

Deliverables & controls

What the scope can include

• Extraction and analysis agents running against your own document management system
• Clause taxonomy and standard-position library built with your legal team
• Evaluation report scoring extraction against senior attorney review, per contract type
• Source-linked review interface, access controls mapped to existing roles, and an operator runbook
• All source code in your repository, with the deployment owned by your team

Where people stay in control

• The system produces a first pass. Attorneys make every call — nothing is approved, signed, or advised by an agent.
• Every extracted field links to its source span in the original document, so no output has to be taken on trust.
• Accuracy is stated as a published ceiling, not a commitment; your own evaluation against attorney review sets the operating threshold.
• Client documents stay inside the environment named in the data agreement and are not used to train shared models.

Sources behind the scenario

1. IDP: 60-80% less processing time, 50-70% lower cost
   Deloitte
2. Extraction accuracy up to ~99%, commonly 90-99% and workload-dependent
   Industry IDP benchmarks — treat as a ceiling
3. 60-70% of work hours are technically automatable with GenAI
   McKinsey MGI, 2023
4. GenAI value to banking $200B-$340B/yr (9-15% of operating profit), much of it document and knowledge work
   McKinsey, 2023