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Enterprise AI for Legal Teams and Law Firms

Enterprise AI for Legal Teams and Law Firms

Legal work is fundamentally knowledge work: reading, analyzing, synthesizing, and tracking. AI does not replace the judgment. It eliminates the hours of reading before the judgment starts.

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Up to 74%
reduction in contract review hours per agreement
Up to 64%
discovery cost reduction on document review
10x
more regulatory sources monitored without added headcount

What We See in Enterprise AI for Legal Teams and Law Firms

1

Associates spend 20 to 40 hours on a single contract review cycle, reading every clause, comparing against the firm's playbook, and flagging risk issues inside Word track-changes that a trained model can extract and classify in under 10 minutes.

2

Legal research for a single memo routinely takes two to three days because relevant precedents, secondary sources, and the firm's own prior memos sit across Westlaw, LexisNexis, iManage, and NetDocuments with no connective tissue between them.

3

eDiscovery review in litigation regularly exceeds the disputed amount in mid-size cases because contract reviewers in Relativity spend hours on documents that are neither responsive nor privileged, and proportionality arguments collapse when the team can't show defensible culling.

4

In-house compliance teams manually track regulatory changes across US state AGs, the SEC, the FTC, and foreign regulators, and the monitoring gap usually only surfaces during an audit or an enforcement action six months after the fact.

How We Help

Contract Analysis and Playbook Review

An agent reads incoming contracts against your firm or company playbook, classifies every clause, extracts commercial terms into structured data, and flags risk issues with specific citations to the problematic language and your playbook position. Attorneys open a redlined Word draft with comments already inserted rather than reading from a blank page. The same tool powers CLM onboarding so executed contracts are abstracted into iManage or Ironclad automatically.

✓ Contract review time from 8 to 12 hours to under 90 minutes per agreement

Legal Research Automation

Agents search across Westlaw, LexisNexis, your iManage or NetDocuments knowledge base, and public sources simultaneously, synthesize relevant authority, and produce a structured research memo with citations that conform to your firm's Bluebook conventions. Attorneys set the research question, define the jurisdiction and posture, and review the AI-drafted memo rather than conducting the full search themselves.

✓ Research cycle from 2 to 3 days to under 4 hours with citations audited to source

Due Diligence Automation

During M&A and financing transactions, the agent processes the full data room including corporate records, material contracts, permits, IP files, and regulatory filings. It maps issues onto a standard diligence checklist, flags items requiring attorney attention, and writes a draft of each section of the diligence report. Teams review the pre-prepared summary rather than starting from raw documents.

✓ Diligence cycle from 3 to 4 weeks to 8 to 10 days, 52% fewer associate hours

Compliance Monitoring

The agent monitors regulatory publications, agency guidance, court decisions, and rulemaking notices relevant to your business, maps each development to your existing compliance policies and controls, and alerts your team when a change requires an update with the specific gap and recommended remediation drafted. The audit log is defensible to regulators and maintains a complete change history per jurisdiction.

✓ 10x more regulatory sources monitored with 48-hour detection on material changes

Litigation Document Review

Agents process document productions for relevance, privilege, and key facts, producing a prioritized review queue with draft summaries rather than raw document sets. Reviewers inside Relativity work from AI-classified batches, focusing on high-value documents instead of triage. Privilege logs are drafted from the underlying document metadata automatically and quality-controlled against your firm's privilege standards.

✓ Review costs down 64% on similar-sized productions with quality metrics meeting court standards

Our Services for This Industry

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Engagement shape

Timeline

A typical legal engagement runs five to nine weeks to first production. Weeks one and two are discovery: practice group interviews, CIO and professional responsibility partner alignment, and a written integration pattern against iManage, NetDocuments, or Relativity. We build the eval set in week two by labeling 500 to 2,000 documents from your firm's prior work with senior associates or partners setting the ground truth on clause classification, issue spotting, or privilege calls.

Weeks three and four are build. The agent runs against the eval set daily and we share a weekly accuracy scorecard with the practice group leader. Weeks five and six are shadow mode with a paired reviewer on live matters. Weeks seven and eight cover validation sign-off, conflicts-wall configuration, and attorney training. Week nine is production cutover on one practice group with hypercare for 30 days. Expansion to additional practice groups follows the same pattern in parallel waves.

Cost model

Most legal engagements fall between $85k and $220k for the first production use case. The main drivers are iManage or NetDocuments integration depth, how many practice groups or contract types are in scope, and whether we're tuning the model on your firm's prior work product and playbooks. A single-practice-group contract review pilot sits near the bottom of the range. A full diligence-and-regulatory-monitoring rollout across multiple practice groups with Westlaw, Lexis, and Ironclad integration lands at the top. Ongoing platform and inference costs typically run $6k to $22k per month, quoted upfront before the SOW is signed.

Frequently Asked Questions

How do you protect attorney-client privilege when data passes through AI systems?+
Privilege protection is a design requirement. We deploy the application layer inside your firm's or company's infrastructure and run inference against models hosted either in your Azure or AWS tenant or in a dedicated private deployment we manage with zero retention and zero training on your prompts. Client content never transits a public AI API in a form that could be argued to waive privilege. We work with your general counsel and professional responsibility partner on the technical architecture documentation, and our standard engagement letter spells out confidentiality and attribution. Every matter gets its own logical boundary so conflicts walls are preserved.
Can AI really be accurate enough for legal work, or does it still require full attorney review?+
Accuracy on structured legal tasks (clause extraction, issue spotting against a defined playbook, document classification, privilege screening) consistently exceeds 92 to 96% in our deployments when the agent is tuned on your firm's playbook and prior work. That accuracy level means AI handles the first pass and attorneys focus review on the flagged items. We never recommend fully removing attorney review from work product where accuracy is material to the legal advice. For novel research questions and ambiguous language, the agent explicitly flags low-confidence output and escalates to a human.
Does your AI integrate with Westlaw, Lexis, iManage, NetDocuments, and Relativity?+
Yes. We integrate with Westlaw Edge and Lexis+ via their APIs for research. We integrate with iManage Work, NetDocuments, and SharePoint for document management and knowledge base search. For eDiscovery we connect to Relativity through its APIs for document classification, privilege review, and production workflows. For CLM we integrate with Ironclad, Icertis, and ContractPodAI. Exact integration scope depends on your specific license terms and versions, so we map the pattern during discovery and confirm with vendor support that no terms are violated.
Who is liable if AI misses an issue in a contract review or research memo?+
The attorney of record remains responsible for the work product. Our systems are designed as tools that assist attorney review, not replace it. Every AI finding shows the specific source text it relied on so attorneys can make informed decisions about what to accept, investigate, or reject. This is no different from the standard of care applied to associate work. Firms typically handle this in client engagement letters and internal practice rules. For in-house deployments, our MSA spells out liability allocation and we carry professional and tech E&O coverage sized for legal deployments.
What does a pilot cost and how long does it take?+
A focused pilot on one use case (contract review for one practice group, diligence automation on a single deal type, or regulatory monitoring for one jurisdiction set) runs 5 to 8 weeks from kickoff to production. Pricing typically lands between $85k and $200k depending on integration count, whether we're tuning on your firm's existing playbook and prior work, and how many practice groups are in scope. Full firm-wide rollouts run 4 to 6 months in parallel waves. We quote a fixed SOW before kickoff so the managing partner, CIO, and finance all see the same number.
What data stays on our infrastructure vs. with the AI vendor?+
Client matter content, work product, playbooks, and knowledge base data stay inside your firm's or company's tenant. We deploy inside your Azure, AWS, or private cloud and run inference against models hosted in your own account or in a dedicated private deployment we manage with zero retention. No client content, no brief drafts, no deposition transcripts, and no deal documents transit a third-party AI API. For public research sources the agent pulls published material through the ordinary Westlaw or Lexis APIs under your existing license. The full egress map is handed to your CIO before go-live.
Who's accountable and what's the hand-off between AI and our attorneys?+
Every workflow has an explicit hand-off. Contract review runs to a redlined Word doc the reviewing attorney opens. Research memos draft inside a Word or iManage template the attorney edits and signs. Diligence reports draft into your standard format and the associate validates every cited finding. Low-confidence items surface at the top of the queue with the reasoning exposed. We deliberately avoid building any workflow where an AI output reaches a client or a court without a named attorney of record reviewing it. The accountable human is the same person accountable today under the rules of professional conduct.
How is this different from Harvey, Casetext, or what our knowledge management team is building internally, and how do we measure ROI?+
Harvey and Casetext ship great general-purpose tools against public research data. We tune the agents to your firm's specific playbook, your prior work product, your practice groups, and your document management stack, and we integrate deeper into your matter workflow. Internal knowledge management teams usually have the right intent but not the capacity to ship agents at the same velocity. We sit alongside those efforts, move fast, and leave you with code and model artifacts your team owns. ROI is measured against a baseline captured in discovery: hours per matter type, realization rates, cycle time on diligence and contracts, write-down rates. Most firms see payback inside 8 months on hours alone.

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Production-grade AI for Enterprise AI for Legal Teams and Law Firms. We deploy in weeks, not quarters.

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