Use Case · Legal

Contract review on the Software Lifecycle Cloud

Contract review on KERNSTACK gives counsel a declared pipeline instead of an inbox: contracts and redlines land in a bucket, a worker extracts clauses and compares them against the playbook your team maintains as data, deviations arrive in a workflow as titled review steps for counsel, and the approval stamp — who accepted which deviation, when — is stored with the contract record.

Object BucketsContainer WorkersModel InferenceApproval Workflows
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The engineering bottleneck with assembled stacks

Counsel compare redlines against a playbook that lives partly in a document, partly in senior memory, and partly in last quarter’s email. The work is slow not because lawyers read slowly but because every contract restarts the same hunt: find the liability clause, remember the fallback position, check whether the last counterparty got a better one.

Architecture on the Software Lifecycle Cloud

The playbook is data: clause types, acceptable ranges, and fallback language in a table the legal team owns. On upload, a worker splits the contract into clauses, matches them against playbook entries, and classifies each as standard, deviation, or missing. The workflow presents deviations to counsel as individual steps; standard clauses never consume attention. Inference assists the matching, deterministic playbook data decides the verdicts.

The playbook stops being folklore

Because the playbook is a table, changing the company’s position is a reviewed data change with a date on it — and every past contract can be re-read against the new position to see what the portfolio already agreed to. That second capability, portfolio search over clause types, is usually the moment counsel stops treating the system as an intake tool.

  • Deviations arrive as separate titled steps, so counsel approve clause by clause, not document by document
  • Clause search across signed contracts reads the same extraction tables — precedents are a query, not a memory
  • The signed PDF stays in the bucket beside its clause map and approvals

What the machine must never do here

Extraction proposes; counsel disposes. The workflow has no state in which a contract becomes approved without a named human’s decision on each deviation, and the system records the playbook version the decision was made against. Legal judgement stays with lawyers; the pipeline removes the hunting, not the judging.

FAQ

Frequently asked questions

Counsel, as data. Clause types, acceptable ranges, and fallback wording live in a table the legal team edits; changing a position is a reviewed change with a timestamp, and extractions cite the playbook version they were judged against.

Yes — that is a side effect of the extraction tables. “Every signed agreement whose liability cap exceeds X” is a query over stored clause records, with the source PDF one bucket read away for verification.

No. It finds, classifies, and routes. Drafting responses and accepting risk stay with counsel, whose decisions the workflow records. Keeping the machine out of the judgement is what makes the audit trail worth having.

Connected in the Project Graph

Related capabilities, architectures, and comparisons

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