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Custom development

Your precedent. Your playbook. Your tool.

When the library does not cover it, our engineers build the workflow against your own documents and ship it into your workspace.

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import { Lawrs } from "@lawrs/sdk";

const lawrs = new Lawrs({ apiKey: process.env.LAWRS_API_KEY });

// Run a playbook review across a matter and keep the citation trail.
const review = await lawrs.tools.run("playbook-enforcer", {
  matter: "brackenridge-msa-2026",
  playbook: "commercial/standard-v7",
  documents: ["doc_8fa21", "doc_8fa22"],
});

for (const finding of review.findings) {
  console.log(finding.severity, finding.clauseRef, finding.summary);

  // Every finding resolves to the exact source text behind it.
  const source = await finding.citation.resolve();
  console.log(source.documentId, source.page, source.quotedText);
}

Four shapes of engagement.

A tool against your precedent

4 to 8 weeks

We take a workflow your team runs by hand, train it on your executed agreements, and ship it as a tool in your library with the same citation guarantees as the standard set.

Playbook encoding

3 to 6 weeks

Your negotiation positions become machine-checkable rules with fallback ladders attached, so a deviation is caught at review rather than at signature.

System integration

2 to 5 weeks

Lawrs reads from and writes to your document management, matter management, and billing systems, so findings land where the work already happens.

Embedded platform

Ongoing

You build on the Lawrs API directly. We provide the retrieval, grounding, and audit layer, and your team owns the product surface on top of it.

How an engagement runs

  1. Sit in

    An engineer and a lawyer watch your team run the workflow by hand. We time it and record every judgement call.

  2. Ground

    We index your precedent and playbook, then build an evaluation set from matters you have already closed.

  3. Build

    The tool ships behind a flag to a small group. We score it against the human baseline until it clears.

  4. Hand over

    You get the tool, the evaluation set, and the runbook. You own the output and can take the eval set with you.

An engineering workspace with documents and screens

You keep the evaluation set. If you leave, you leave with the thing that proves whether the tool works.

Most legal AI engagements hand back a black box. We hand back the scored test set built from your own closed matters, because that is the asset that survives a change of vendor.

Bring the workflow that eats your week.

First conversation is a scoping call with an engineer in the room, not a sales qualification.

Book a demo