Custom Software for Law Firms & Legal Operations

Legal work combines three pressures that almost no other industry has at once. The data is privileged. Attorney-client communications, work product, and matter data are subject to confidentiality rules that exceed almost every other industry's privacy obligations. A vendor learning about your data model from a stack-trace email is a malpractice risk, not a customer-service issue. Second, the regulatory chain is unusually wide and unusually personal. State bar rules on advertising, fee splitting, unauthorized practice of law, IOLTA accounting, ABA Model Rules 1.6 and 5.3, conflict-check duties, and the rapidly evolving state-level guidance on generative AI in legal work all carry direct disciplinary consequences for the lawyer, not just the firm.

Third, the integration surface is awkward. Clio, MyCase, PracticePanther, Smokeball, Filevine, and a handful of practice-area-specific platforms each implement intake, document automation, conflict checking, and trust accounting in their own way. A boutique with a specific intake workflow finds the platforms cover 70% of what they need and force the other 30% into spreadsheets and email. We build that other 30% directly, leaving the matter and billing system inside the platform that does it well.

ABA Model Rules 1.1, 1.6, and 5.3. Technology competence (1.1), confidentiality of information (1.6), and supervision of non-lawyer assistants including vendors (5.3) all apply to the engineering team that touches firm data. We sign confidentiality agreements that exceed standard NDAs and segregate access at the matter level.

State bar advertising rules. Lawyer-advertising regulation varies wildly by state — TCPA-aware lead handling, mandatory disclosures, and prohibition on certain testimonial structures all live in different state rules. We build forms and content modules that can be tuned per jurisdiction.

IOLTA and trust accounting. Three-way reconciliation, no-commingling, fee-application authorization, and audit trails. We integrate with the firm's IOLTA accounting system rather than replacing it; we provide the surrounding workflow and evidence trail.

Confidentiality and segregation of matter data. Row-level access control tied to the matter and the user's role on that matter. Audit log captures every read and write. PII and confidential data minimized in logs and observability.

Generative AI in legal workflows. ABA Formal Opinion 512 and state-bar opinions (CA, NY, FL, and growing) require lawyer supervision, accuracy verification, and confidentiality safeguards. We default to private-tenant LLM endpoints (Azure OpenAI, AWS Bedrock with custom guardrails), prompt isolation between matters, no training-data sharing, and human review checkpoints.

SOC 2 and cyber insurance. Larger firms and corporate clients increasingly require SOC 2. Our builds align with Common Criteria; cyber-insurance underwriters get pentest reports formatted to their checklists. See penetration testing for details.

Next.js 15 or 16 with React 19 and TypeScript for the web layer. Postgres on Neon or RDS for the system of record. Prisma or Drizzle as the ORM. Clio API or MyCase API as the matter-management system of record where the firm is already on a platform; otherwise a custom matter model with row-level access control. DocuSign or Adobe Sign for binding signatures. AWS S3 with server-side encryption and bucket policy lockdown for matter documents.

For generative AI features, Azure OpenAI Service or AWS Bedrock with private tenancy, prompt isolation, and explicit no-training contracts. Output verification with a citation-checker step before any drafted text reaches a client. Auth via Clerk or Auth0 with MFA-required on every attorney and paralegal surface. Logging via Better Stack or Datadog with PII/PHI/privileged-info redaction. Hosting on Vercel for the web tier; the matter document store stays in a hardened VPC.

Three patterns recur. First, the firm tries to replace Clio or MyCase. Almost always the wrong move — those platforms are good at matter and billing, and the bar-aware accounting is genuinely hard. The right scope is to keep the system of record where it is and build the workflow the platform does not handle. The economic case is clearer and the rollout is dramatically less painful.

Second, generative AI gets bolted on without supervision controls. A drafting tool ships, a paralegal stops reading the output carefully, and the first time a hallucinated citation makes it into a filing the firm has a malpractice problem. We bake supervision checkpoints in: every AI-drafted text passes through a citation-verification step and a named human reviewer before any client-facing release.

Third, intake automation is built without conflict screening. A firm shoots up the lead volume by 5x and discovers two months later that conflicts are slipping through because the intake form did not capture the parties needed to run the conflict check. Conflict screening belongs at the lead stage, not at the matter-open stage.