Litigation Intelligence & Strategy

Litigation Intelligence does not start from scratch. It picks up where Data Intelligence finishes — consuming the structured Litigation Profile, the case-specific knowledge graph, the document classifications, and the vector-indexed corpus produced upstream.

• Litigation Profile — parties (with roles and aliases), attorneys, claims, defenses, disputed issues, and case-level timeline events, each linked back to the source document and page.
• Knowledge graph — traversable Case → cites → Statute, Author → wrote → Case relationships, plus communication graphs for every custodian.
• Document classifications — responsiveness, privilege, issue tags, hot-document flags, sentiment scores from the Document Review pass.
• Per-chunk vector embeddings for semantic retrieval grounded in the matter's own corpus, plus 25 structured retrieval tools that agents call with precision rather than free-text search.
• Element substitution — entities auto-mapped into jury-instruction placeholders so claim analysis is one operation, not a hand-wired translation.

The handoff is the strategic point: agents reason against grounded evidence, not against the open web. Hallucinations drop, citations sharpen, and every assertion can be traced back to a specific document, page, and span.

Ten advocacy agents collaborate to build the case from your client's perspective. Each agent produces a concrete, named deliverable — not a vague analysis.

• Case Analyst — A typed and rated fact inventory (F001…), a complete event timeline with dates and participants, party catalog, and information-gap list.
• Claims Architect — Viability scores (0.0–1.0) for each cause of action, mapped to specific jury-instruction elements across CA, Federal 9th/5th/11th, TX, FL, NY; tracks statutes of limitation.
• Legal Researcher — Research memo with binding/persuasive/secondary authority hierarchy, mandatory adverse-authority disclosure (Critical/Significant/Minor/Non-Issue), and Bluebook-formatted citations.
• Evidence Strategist — Element-coverage map showing which elements have evidence, admissibility analysis under CA Evidence Code §§ 210–1553 (with 18+ hearsay exceptions), foundation requirements, and exhibit strategy.
• Motion Drafter — Court-formatted briefs in CRAC/IRAC structure: Notice of Motion, Memorandum of P&A, Separate Statement of Undisputed Material Facts (with per-fact evidence citations), declarations, proposed order — compliant with margins, fonts, and page limits.
• Citation Validator — Every cite Shepardized for good-law status, every quote verified character-by-character against source, Bluebook format, signal use, unpublished-opinion detection, and severity-graded issues. Catches Rule 11 / CCP § 128.7 risks before filing.
• Document Assembler — E-filing-ready PDF/A package: TOC, TOA generated from headings and cites, exhibit tabs and bookmarks, page-limit verification, Proof of Service template.
• Discovery Specialist — Interrogatories (form and special, with 35-limit declaration of necessity), RFPs, RFAs (deemed-admitted monitoring), deposition outlines, PMQ/PMK strategy, motions to compel.
• Opposition Analyst — Red-team output: predicted defense theories, vulnerability map per element, predicted motions, opposing counsel profile, internal-contradiction detection.
• Narrative Strategist — Case theme using archetypes, three-act story structure, witness sequencing, and audience-adapted framings (judge, jury, mediator). Facts inform; stories persuade.

In parallel, six evaluation agents critique the same case data as a neutral arbiter would — explicitly instructed not to advocate, run with independent state, and graded against formal evidentiary and logical standards.

• Fact Auditor — Strips advocacy spin; classifies every assertion as Verified / Supported Inference / Disputed / Unsupported / Characterization / Cherry-Picked, with severity (Critical/High/Moderate/Minor). Includes a six-dimensional Bias Detector (linguistic, structural, epistemic, confirmation, anchoring, authority).
• Evidence Scorer — Scores each piece of evidence across Authenticity, Accuracy, Corroboration, and Relevance with a published composite formula. Aggregates to element-level score `1 − Π(1 − scoreᵢ)`. Five-factor witness credibility analysis included.
• Argument Mapper — Decomposes arguments into premises / inferences / conclusions; verifies valid logical forms; detects fallacies (Affirming the Consequent, Post Hoc, False Dichotomy, Straw Man, Hasty Generalization, Equivocation). Weakest-link scoring with green/amber/red diagrams.
• Rule Arbiter — Applies law neutrally; scores legal certainty on a 6-band scale (Settled 0.95–1.0 → Novel 0.00–0.24); spots missed claims, defenses, or SOL issues; applies the correct standard of review.
• Threshold Validator — Tests every element against burden of proof — Preponderance (0.51), Clear & Convincing (0.75), Beyond Reasonable Doubt (0.95) — and runs what-if modeling: "Obtaining the personnel file improves Element 3 from 0.42 to 0.68."
• Verdict Simulator — Capstone agent. Models Judge, Jury, and Appellate perspectives with explicit weighting (Jury: narrative 25% / credibility 25% / sympathy 20% / evidence 20% / damages 10%) and produces the win-probability distribution, expected value, and settlement zone.

Most litigation platforms do one thing: help attorneys build their case. LexGo AI does two things simultaneously — it builds the case and pressure-tests it from the bench. The two layers run on the same case data, with structured intersection points (quality gates), not as a sequential review.

The strategic output is the per-element divergence table: where advocacy says "strong" but evaluation scores 0.48 (At Risk), the attorney sees the strategic gap before opposing counsel does. That is the dual-layer advantage — the advocate and the judge, working together.

"Every litigation platform on the market does one thing: it helps attorneys build their case. LexGo AI does two things simultaneously — it builds the case and pressure-tests it from the bench."

LexGo AI ships 525 workflow templates across 25 categories on top of 13 hand-crafted core workflows. Each workflow names its inputs, its phases, its evaluation gates, and the work product it produces.

• Motion for Summary Judgment — six phases, two gates. Out: MSJ brief, Separate Statement, declarations, proposed order, e-filing package.
• Discovery Planning & Preparation — Out: interrogatories, RFPs, and RFAs each tied to a specific element gap identified by the Threshold Validator.
• Deposition Preparation — Out: topical outline, exhibit list, PMQ/PMK strategy, anticipated impeachment material, key admissions to extract.
• RFP Response & Document Production — Out: responses, objections, privilege log, Bates-stamped production.
• Trial Brief & Full Trial Preparation — Out: trial brief, motions in limine, jury instructions, witness order, exhibit list.
• Settlement Assessment / Mediation Preparation — Out: settlement opportunity assessment, BATNA / WATNA, settlement-zone calculation, Litigation Cost Opportunity Card.
• Demand Letter Response, Subpoena Issuance, Subpoena Response, Motion to Dismiss, Quick Case Assessment — full lifecycle coverage, same architecture.

Six orchestration agents (Case, ESI, Evidence, Advocacy, Evaluation, Strategy) coordinate cross-workflow planning, so what happens in discovery informs what happens in motion practice, which in turn shapes what shows up in the trial brief.

The model is simple: AI agents produce work product; attorneys make strategic decisions. No workflow advances past a quality gate without the attorney's explicit approval.

Pre-defined gates include INTAKE_REVIEW, CLAIMS_REVIEW, EVIDENCE_SUFFICIENCY, DISCOVERY_PLAN, PRIVILEGE_REVIEW, OBJECTION_STRATEGY, DRAFT_REVIEW, and FINAL_REVIEW. At each gate the attorney sees:

• All work products generated since the last gate, side-by-side with the evaluator scores and findings.
• The specific assessment criteria for that gate (e.g., element coverage, citation validity, threshold probability).
• Approve / Approve-with-Notes / Reject / Request Additional Analysis controls. Notes inject directly into downstream agent context to steer revision.
• Optional configurable auto-approval for routine matters when confidence exceeds threshold and auto-checks pass — recorded as system approval, distinct from attorney approval.

The Advocacy Orchestrator dispatches agents and routes evaluation feedback back into targeted revision — Motion Drafter fixes the logic gap; Legal Researcher hunts authority for a weak element; Discovery Specialist drafts targeted requests to close evidence gaps. The attorney never loses authority — workflows survive system restarts; a Friday-afternoon pause resumes Monday morning with full context.

Every engagement produces concrete, attorney-ready work product — not a wall of analysis.

• MSJ filing package — brief, Separate Statement, declarations, TOC/TOA, exhibit tabs, CRC-compliant PDF/A.
• Element-by-element case scorecard — per claim, per element: evidence strength × legal certainty, with threshold pass/fail and quantified gap.
• Verdict simulation report — win probability, expected damages, settlement zone, and best/expected/worst scenarios from Judge/Jury/Appellate viewpoints.
• Targeted discovery set — every interrogatory, RFP, and RFA mapped back to a specific element gap.
• Deposition outlines — topical structure with marked exhibits, anticipated impeachment, and key admissions to extract.
• Opposition profile and counter-strategy — predicted defense theories, vulnerability map, inoculation arguments to embed in opening filings.
• Settlement memo / Litigation Cost Opportunity Card — settlement zone with cost-of-trial vs. cost-of-settlement comparison from plaintiff, defendant, and mediator perspectives.
• Citation validation report — every cite Shepardized, every quote verified, Bluebook-conformed, severity-graded.
• Argument map — visual diagram of premises → inferences → conclusions, color-coded green/amber/red, with weakest-link scores.
• Trial binder — trial brief, motions in limine, jury instructions, witness order, exhibit list.
• Privilege log — FRE 502 / CA Evidence Code compliant, with waiver-risk analysis.

The Verdict Simulator is the capstone of the Evaluation Layer. It consumes the outputs of the Fact Auditor, Evidence Scorer, Argument Mapper, Rule Arbiter, and Threshold Validator and produces a quantified outcome distribution.

• Probability-weighted outcome — e.g., "78% full grant, 15% partial, 7% denial."
• Expected Value = probability of winning × likely damages award; Risk-Adjusted Value applies a risk factor.
• Settlement Zone = [defendant's minimum, plaintiff's minimum] — the negotiating window.
• Multi-perspective scoring with explicit weights:
  • Judge: legal certainty 35% / evidence 30% / precedent 20% / procedural 15%.
  • Jury: narrative 25% / credibility 25% / sympathy 20% / evidence 20% / damages 10%.
  • Appellate: legal correctness 40% / preservation 25% / standard of review 20% / record support 15%.

In a study of 1,000 litigators, attorneys predicted they would win at trial 70–90% of the time. Actual win rates hover around 50%. Quantified evaluation makes strategy conversations sharper than instinct alone.

Every conclusion in the final work product can be traced backward through the agent chain to its source in the case record. Nothing is asserted without provenance.

• Cross-reference IDs — Facts get F-IDs, claims C-IDs, elements C-IDs-E-IDs, evidence EV-IDs, arguments ARG-IDs, citations CIT-IDs. Every conclusion reaches back to a specific source page or passage.
• Confidence propagation — each agent inherits and reports confidence; the final number is the product, not a marketing claim.
• Versioned work products — SEED → DRAFT → REVIEW → APPROVED → COMMITTED → ARCHIVED, with every version recording content, source type, scores, and inputs snapshot.
• Citation Validator — independent verification of every citation, quote, and signal before filing.
• Independent Evaluation Layer — explicitly instructed not to advocate; runs with separate state and context.
• Validation Agent — court-vetted methodology grounded in Da Silva Moore v. Publicis Groupe: sample-size calculation, confusion matrices, recall/precision/F1, and pass/fail vs. defensibility thresholds. Blocks production until validation passes.
• Weakest-link argument scoring — `argument_score = min(premise_scores) × min(inference_scores)` — one bad premise breaks the chain.
• Iterative feedback — evaluation findings flow back to advocacy agents for targeted revision, then re-scored to confirm the gap closed.

The cost of catching a bad citation during validation is measured in seconds of computation. The cost of catching it after filing is measured in sanctions motions, ethical complaints, and lost credibility.

Engagements are scoped per matter and run with you — not as a black box. Our Legal AI professionals work alongside your trial team in standups, share drafts, accept feedback, and iterate against the gates and orchestrator above.

For firms running a portfolio of matters, we offer standing engagements with reserved capacity, shared infrastructure across cases, and per-matter cost attribution so any case can be tracked, reported, or invoiced on its own meter.

Pricing is engagement-based and scoped to case complexity. Most engagements include a complimentary scoping call with a written estimate, a not-to-exceed cap, and a clear plan for the first quality gate before any work begins.