Services

Where legal AI earns its keep.

Six engagements where a well-engineered AI system has saved real reviewer hours — with the citations and confidence scores your team needs to trust the output.

01

Contract Risk Analysis

Score every clause in an agreement against your firm's playbook. Non-standard indemnification language, weak limitation of liability, missing data-protection provisions, and unfavorable venue clauses are surfaced with a rationale and a source citation.

  • Playbook-driven scoring — your standards, not a generic template
  • Severity tiers: blocker, negotiate, acceptable
  • Redline suggestions with the precedent language your team prefers
02

Clause & Section Extraction

Convert a PDF contract into a structured record: parties, effective date, term, renewal, governing law, exclusivity, IP assignment, indemnification, limitation of liability, data processing, and 40+ additional named clauses.

  • JSON, CSV, or direct CLM-system integration
  • Handles amendments, exhibits, and incorporation by reference
  • Confidence scores per field so reviewers know where to look
03

Due Diligence Automation

Run the contract side of an M&A data room in hours instead of weeks. Change-of-control provisions, assignment restrictions, termination rights, and exclusivity obligations are mapped across the full corpus — with exceptions escalated to human reviewers.

  • Bulk processing of thousands of agreements
  • Change-of-control and assignment summaries per counterparty
  • Reviewer queue for exceptions — not a black box
04

Obligation & Deadline Tracking

Extract every time-bound obligation from an executed contract — renewal notices, audit rights, reporting requirements, payment triggers, termination windows — and drop them into your calendar, CLM, or operational system of record.

  • Relative dates resolved against the effective date
  • Conditional triggers captured with their conditions
  • Integration with common CLM and calendar systems
05

Contract Comparison & Redlining

Compare a counterparty's proposed agreement against your standard template, clause by clause. Substantive changes are separated from cosmetic ones, and each deviation is explained in plain English with a severity tag.

  • Semantic diff, not text diff — synonyms and reorganization are recognized
  • Severity-tagged deltas: material, moderate, cosmetic
  • Exportable redline in DOCX with tracked changes
06

Compliance & Regulatory Review

Screen agreements against regulatory regimes — GDPR, CCPA, HIPAA, export controls, sanctions — and surface the provisions that need attention, with citations to both the contract language and the applicable requirement.

  • Data processing and transfer clause review
  • Sanctions and restricted-party screening
  • Gap analysis against jurisdiction-specific requirements

Engagement Model

Three ways to work together.

Pilot

2–4 weeks

Bring a redacted document set and a playbook. I'll stand up a working system against your corpus, measure extraction precision on a gold set, and deliver a report on fit and cost.

Advisory

Ongoing

Your team builds; I review. Architecture reviews, model selection, evaluation design, vendor due diligence, and troubleshooting for an in-house AI effort that's already underway.

Which of these describes your problem?

Tell me the workflow, the document volume, and the constraints — I'll tell you what's actually achievable and what it will cost.

Describe Your Use Case