TREN

Document operations · Scope to be defined during discovery

AI System for Extracting a Critical Clause Inventory from Contracts

We design an AI system that reviews a contract and legal checklist together with their source and recency details. The system prepares a clause summary linked to page references, but does not implement it as a final decision. If the contract includes a termination, penalty or data clause, the suggestion does not proceed; the legal specialist makes the final assessment.

Representative contract operations panel with a work queue, checks and an audit trail: contract clause inventory queue — **Contract clause inventory queue** Representative interface — contains no real data. The panel does not provide a legal opinion or make a contract decision; a legal specialist reviews each clause.

The problem

In day-to-day operations, contracts and legal checklists arrive through different systems and files, preventing the team from reviewing the same case in one view.

As a result, the link to source evidence can be lost while a page-referenced clause summary is prepared, leading to repeated checks and uncertainty about the basis for the decision.

Incomplete automation may overlook a termination, penalty or data clause, while incorrect automation risks an incomplete summary being mistaken for a professional assessment.

What we set out to improve

Time taken for the page-referenced clause summary draft to be ready for review
Correct routing of records containing a termination, penalty or data clause to the appropriate specialist queue
Record of suggestions corrected or rejected by the legal specialist

How the system works

01 Retrieve the contract and legal checklist from authorised sources
02 Verify the source system, record identifier and recency information
03 Map the fields to the target process schema
04 Prepare the page-referenced clause summary draft
05 Compare the draft with business rules and source records
06 Check for an exception: a termination, penalty or data clause
07 Have the legal specialist approve, revise or reject the suggestion
08 Write the input, suggestion, changes and final decision to the audit log

Methods we used

Source-traceable data extraction for the contract and legal checklist
Structured output that limits the page-referenced clause summary fields through business rules
An exception gate that separates cases containing a termination, penalty or data clause
A queue that shows the legal specialist the source evidence and suggestion together
Duplicate-processing controls and a reversal record to reduce the risk of an incomplete summary being mistaken for a professional assessment

Where people stay involved

The legal specialist is the final decision-maker. The workflow pauses for a termination, penalty or data clause and presents the case to the specialist with its supporting records. The specialist can revise or reject the suggestion, or stop the process.

Data and security

Only fields required for the task are processed from the contract and legal checklist. Source-system permissions are preserved, and personal or commercially sensitive data is minimised before being passed to the model. Every read, suggestion, human change and write to the target system is logged.

Who this suits

A good fit

Document operations teams that perform repetitive reviews
Companies with defined ownership for sources and approvals
Organisations that want exceptions to remain under human supervision

Not a good fit

Operations where source data is not current
Operations where the decision owner and reversal process are not defined
Operations where the existing method is sufficient for the low volume

Frequently asked questions

What data is used?

The contract and legal checklist are used. The exact connections, fields and retention limits are defined during the access review.

How are exceptions handled?

The workflow pauses for a termination, penalty or data clause. The record is placed in the legal specialist's queue with its source evidence.

How is incorrect automation controlled?

Because of the risk of an incomplete summary being mistaken for a professional assessment, no final action is taken without human approval. The source, suggestion and human decision are recorded separately.

Project led by:DijitalPi

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