Predictive Legal Agent

The Predictive Legal Agent. Drafts a senior associate would.

A counsel-supervised agent that drafts cited answers, flags risk early, and never files the brief.

Predictive Legal Agent works alongside your in-house legal function the way a senior associate would, except it reads every contract, every policy, and every regulator update overnight. It studies your policy library, your prior matters, and the regulatory feeds that touch your business, then drafts cited responses for counsel review. Counsel always finalises. The agent never advises a business stakeholder directly.

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★ Why not a chat wrapper

Generic LLMs can't do this.

A frontier chat model with no grounding does what ChatGPT did in Mata v. Avianca: it invents cases that sound right. Judge Castel sanctioned the lawyers $5,000 and ordered them to notify every judge whose name had been fabricated. Since that 2023 order, at least 15 more cases have surfaced with the same failure mode. A generic LLM also has no concept of attorney-client privilege, no policy library, no matter history, and no regulatory diff watch. Pasting client data into a public chatbot has now cost privilege in United States v. Heppner (S.D.N.Y., Feb 2026). Predictive Legal Agent is a different category: grounded retrieval over your documents, privilege markers on every output, refusal when no source exists.

NDA and vendor-paper triage with risk-tier routing
Paragraph-level citations. Refuses when no source supports the answer.
Regulatory diff watch: SEC, EU AI Act, DSA, GDPR, India DPDP, sector regulators
66% accuracy against a senior-counsel evaluator panel, model card per release
★ Use cases

What it actually does.

Real work the agent does end-to-end. Every step is auditable, every consent gate logged, every escalation routed to a named human.

  1. 01

    NDA and vendor-paper triage

    First-pass redline on inbound NDAs and standard vendor agreements, routed by risk tier.

    • Intake form classifies counterparty, deal value, and template (yours or theirs).
    • Agent extracts the 40 to 60 deal points the team cares about, scored against your playbook.
    • Green-tier NDAs return a clean redline and signature-ready draft in under a minute.
    • Yellow-tier surfaces non-standard clauses with a cited rationale from your playbook.
    • Red-tier (indemnity carve-outs, unusual IP clauses, data terms) escalates to a named lawyer with a written summary.
    Confidentiality gateDocuments processed in your tenancy, encrypted at rest, never used for cross-client training. Privilege markers attach automatically to draft outputs.
    Human in the loopCounsel signs every NDA before send. The agent only proposes.
  2. 02

    Policy compliance check

    Tests draft commercial terms, marketing copy, and product changes against your live policy library.

    • Business stakeholder submits the artefact through the intake form.
    • Agent retrieves applicable internal policy paragraphs and external regulatory text.
    • Each finding is returned with a paragraph-level citation and a confidence score.
    • Conflicting policies are surfaced rather than silently resolved.
    • Counsel approves, edits, or refuses.
    Confidentiality gatePolicy library indexed once, queried in tenant. No prompt or response leaves the customer's region.
    Human in the loopCounsel decides which findings are material and how to advise the business.
  3. 03

    Regulatory diff watch

    Tracks regulator publications and re-tests existing contracts and policies when wording changes.

    • Subscribes to SEC, EU AI Act, DSA, GDPR, India DPDP, and sector regulators by jurisdiction.
    • Detects substantive changes (not formatting) against the previous version.
    • Maps each change to affected contracts, policies, and prior advice.
    • Generates a counsel-facing memo: what changed, what it touches, suggested action.
    • Adds the change to a tracked register with owner and due date.
    Confidentiality gatePublic sources stay public. Mapping happens against your private corpus inside your tenancy.
    Human in the loopCounsel decides which change is material and which letters or contract amendments go out.
  4. 04

    Contract redline against playbook

    Counterparty paper compared clause-by-clause to your house playbook, with cited fallback positions.

    • Agent ingests counterparty draft and your playbook for that contract type.
    • Clause-level embeddings find your nearest sanctioned position.
    • Drafts a redline with preferred, fallback, and walk-away positions inline.
    • Each suggestion cites the playbook paragraph and any prior matter where the position held.
    • Surfaces the three clauses most likely to drive negotiation cycles.
    Confidentiality gatePlaybook and counterparty paper stay in your data perimeter. No model provider sees the file body.
    Human in the loopCounsel owns the redline that goes back. The agent's role ends at the first-pass draft.
  5. 05

    Matter intake and early case assessment

    Triages new disputes against the history of how similar matters resolved.

    • Intake captures parties, claim type, jurisdiction, exposure estimate.
    • Agent retrieves comparable closed matters from your history.
    • Returns base rates: settled vs litigated, average duration, ranges of cost and recovery.
    • Flags clause patterns or counterparty behaviour previously linked to escalation.
    • Drafts a one-page early case assessment with citations to the prior matter files.
    Confidentiality gateMatter files carry privilege markers. Outputs are tagged as work product where the test in Warner v. Gilbarco is met.
    Human in the loopLead counsel decides strategy and budget. The agent's base rates are inputs, not decisions.
  6. 06

    RFP and security questionnaire response

    Drafts answers to inbound legal, security, and AI-governance questionnaires from prior approved responses.

    • Parses the inbound questionnaire into individual questions.
    • Retrieves the most recent approved answer for each question, with the date and approver.
    • Marks any question whose answer is older than the policy refresh interval.
    • Surfaces conflicts where two prior answers disagree.
    • Returns a draft for counsel review before the sales team sees it.
    Confidentiality gateAnswer library lives in your tenancy. The agent refuses and flags if no approved source exists.
    Human in the loopCounsel approves every answer that touches privilege, security posture, or AI usage claims.
★ The journey

Phase by phase.

The end-to-end path the agent runs. Every phase logs what it captured, what consent applies, and where a human gates the next step.

  1. 01

    Intake

    Structured form classifies type, urgency, counterparty, jurisdiction. Privilege flag set if counsel directs.

  2. 02

    Retrieval

    Agent pulls relevant policy paragraphs, prior matters, playbook clauses, and live regulator text.

  3. 03

    Draft

    First-pass redline, memo, or response is generated with paragraph-level citations and confidence scores.

  4. 04

    Refusal check

    If a section has no source above the threshold, the agent refuses that section rather than fabricate.

  5. 05

    Counsel review

    Named lawyer accepts, edits, or rejects. Edits feed back into the evaluator-panel record.

  6. 06

    External action

    Counsel sends the redline, memo, or filing. The agent never sends externally on its own.

  7. 07

    Outcome capture

    Settlement, negotiated terms, or filed outcome is recorded against the original prediction.

  8. 08

    Archival and retrain

    Closed matter is indexed for future retrieval. Quarterly retrain uses your matter history only.

★ Posture

The non-negotiables, spelled out.

Consent, security, accuracy, and residency. Explicit, auditable, and the same line items your CISO or GC already asks about.

Citation discipline

Every output carries paragraph-level citations to the source document, with the document's last-edited date. If retrieval finds no source above the confidence threshold, the agent refuses that section and says so in writing. This is the only honest position after the Stanford RegLab study (April 2025) that showed Lexis+ AI hallucinating 17% of the time and Westlaw AI-Assisted Research 33%, both marketed as RAG-grounded. The Mata v. Avianca lesson is not "use better prompts." It is: a tool that cannot refuse will eventually invent. A senior-counsel evaluator panel scores a rolling sample of outputs against a written rubric. The panel's score is the accuracy number we publish.

Accuracy and retraining

Current production accuracy is 66%, measured against the senior-counsel evaluator rubric, not a public benchmark. We disclose the baseline because legal AI vendors publishing 90%+ figures without a method are mostly marketing. The figure improves monthly: every counsel edit is a labelled example, and the evaluator panel re-scores a new sample each month. Quarterly retraining uses only the client's own matters, with no cross-client mixing. Each release ships with a model card: training-data window, evaluator-panel composition, known weak categories, and the refusal rate.

Data residency and privilege

Deployment options are single-tenant cloud in the customer's chosen region, customer-owned cloud account (AWS, Azure, GCP), or on-prem for clients with a hard data perimeter. No prompt or response is used for cross-client training, ever. Documents flagged as privileged carry that marker through every retrieval and every output. The agent records who directed the work and under whose supervision, the four-factor test the court applied in United States v. Heppner (S.D.N.Y., Feb 2026) when it stripped privilege from a public chatbot session. SOC 2 Type II, ISO 27001, GDPR Article 28 controller-processor terms, and DPDP-aligned localisation for India clients.

★ Outcomes

What the numbers look like.

Figures we can point at. Every one carries a source you can verify.

94% accuracy on NDA issue-spotting vs 85% for senior lawyers
Ceiling figure for a narrow task. Counsel still finalises every NDA.
Source: LawGeex / Stanford CodeX, 2018
17% to 33% hallucination rate in vendor legal AI
Why refusal-on-no-source is non-negotiable for any legal agent worth deploying.
Source: Stanford RegLab, Journal of Empirical Legal Studies, April 2025
5 hours per week saved per legal professional (~240 hours/year)
Reclaimed time gets reinvested in strategic work, not headcount cuts.
Source: Thomson Reuters Future of Professionals 2025
GenAI use in corporate legal more than doubled, 23% to 52% in one year
Adoption is no longer the question; governance is.
Source: ACC / Everlaw 2025 CLO Survey
40 to 90% reduction in contract review cycle time
Variance is real. The high end requires a clean playbook and trained reviewers.
Source: Sirion 2024-25 benchmark, supported by Forrester TEI on Ironclad (314% ROI over three years)
★ Where it lands

What it replaces. What it augments.

Replaces

  • The first-pass NDA reviewer (paralegal or junior counsel time).
  • The manual regulatory tracking spreadsheet.
  • The week-three drafting of the security questionnaire response.

Augments

  • Senior counsel judgement on novel clauses, settlement strategy, and bet-the-company matters.
  • Outside counsel for specialist work.
  • The GC's quarterly board update on legal risk.
★ Inside Predictive Legal Agent

How the Legal Agent supports counsel

It studies your policies and matters, drafts cited responses for review, and flags risk early.

What it studies

  • Learns your policy library and keeps itself updated as regulations shift.
  • Reads your past matters to understand how your organisation actually handles risk.

How it supports counsel

  • Drafts responses with paragraph-level citations. Counsel reviews and finalises.
  • Runs a predictive layer across the whole team, flagging contracts, communications, and process changes that look likely to produce a legal issue.

Accuracy and trust

  • Current production accuracy is 66%, against a senior-counsel evaluator panel, improving monthly.
  • SOC 2 Type II, ISO 27001, GDPR Article 28, India DPDP-aligned localisation. Quarterly retrain on your matters.
★ Pricing

The numbers, up front.

Custom enterprise licence. Per-seat pricing punishes the team that gives the agent to its business stakeholders for intake, which is exactly the use we want. Per-matter pricing punishes high-volume teams and creates the wrong incentive to skip the agent on small matters. The licence scales with corpus size, deployment mode, and the size of the senior-counsel evaluator panel we run for you. Implementation includes the playbook intake, the policy library indexing, and the first evaluator-panel calibration.

What you get
Annual enterprise licencecustom quote
Counsel-panel evaluation harnessincluded
Quarterly retrain on your mattersincluded
SOC 2 / GDPR / DPDP controlsstandard
Predictive Legal Agent

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