Custom Software and AI for Law Firms and Legal Operations

Where software and AI fit in a law firm

Most of a firm's automatable work is not legal reasoning. It is moving facts from one place to another, assembling documents from language the firm already trusts, and checking work against a standard the firm already wrote down. That is where we start.

• →Matter intake and conflict checks. A structured intake form feeds the conflicts search and opens the matter with the right parties, practice group and billing arrangement, instead of an assistant retyping an email into three systems.
• →Document assembly from your own precedents. Engagement letters, NDAs, routine motions and closing sets built from the firm's approved templates and clause library, with the variable facts pulled from the matter record.
• →Clause extraction against a playbook. Incoming contracts are read against your positions on indemnity, limitation of liability, assignment and the rest, and every deviation is flagged with the clause text beside it.
• →Billing narrative review. Time entries checked against client billing guidelines before the invoice goes out, so block billing and vague entries are caught by the firm, not by the client's auditor.
• →Research summaries with the sources attached. Summaries that link every proposition to the document it came from, so the reviewing attorney reads the source, not the summary.

Privilege and confidentiality are architecture decisions

A law firm cannot bolt confidentiality onto a system after it is built. The decisions that matter are made in the first week: where the documents are stored, which model processes them and under what terms, and how the system knows which people are walled off from which matters.

We design for that up front. Access is scoped per matter, so an ethical wall in your practice management system is respected by the AI tools too, and every retrieval and every generated draft is logged against the user who asked for it.

Documents are stored in infrastructure your firm controls. Reading a document still means sending its text to whichever model processes it, so the model is a scoping decision, not a detail: Anthropic's Claude or OpenAI, through their own APIs or through your cloud provider (Amazon Bedrock, Azure OpenAI or Google Vertex AI), chosen per engagement, under data-use and retention terms agreed with you before the build.

We sign an NDA before our first call about your matters, before we see any documents.

Why an attorney stays in the loop

Language models write fluent, confident text, and fluent is not the same as correct. A model can cite a case that does not exist or quote a clause that is not in the contract (see our glossary entry on hallucination). In most industries that is an annoyance. In a filing, it is a professional responsibility problem.

So the systems we build for legal work are drafting and review tools, not decision makers. Every extracted clause shows the text it came from, and every summary links to its source. Depending on the workflow, outputs can also be checked in code before they reach anyone: an extracted clause must match text that is actually in the document, a cited case or section must be found in the source set, and structured fields must agree with the matter record. Anything that fails a check goes to a review queue instead of into a document; the model's own sense of how sure it is decides nothing. Nothing is filed, sent or signed without an attorney approving it.

Build or buy: when a firm should not hire us

Plenty of good legal software already exists. If what you need is practice management, e-billing, or an off-the-shelf contract review product that fits your practice, buy it; it will be cheaper and better supported than anything we would build.

Custom software makes sense when one of three things is true: the workflow crosses systems that the vendors do not connect; your firm's own precedents, playbooks or matter history are the asset, and a generic tool cannot use them; or no vendor will meet your terms on where client data lives and who can process it. Our build vs. buy guide walks through the decision in more detail.

How a legal engagement runs

We start with the 90-minute AI workflow audit: one session mapping how a matter actually moves through the firm today, where the rework is, and which step is worth automating first. The audit is complimentary when it is bundled with a larger build and available as a paid one-off on its own.

From that we write a priced scope for one workflow in one practice group. Prototype, staging, and deployment milestones are agreed in the written scope. We agree with you, before the build, what "better" means for that workflow (time from intake to opened matter, for example, or hours spent on first-pass review for one contract type), and you record today's number so the result can be checked against it. Once one workflow is proven, the next one reuses the same access model and audit trail.