Kaia Legal
Part of Kaia Legal →End-to-end eDiscovery intelligence that learns from every review.
From document intake through post-litigation analytics, Kaia Legal manages the entire eDiscovery lifecycle with AI confidence scoring. Every accepted correction is designed to move the privilege-detection benchmark — evaluated on a frozen gold set before any release, published as measured. With full audit trails for court admissibility. Because that's what a GC's diligence team should be able to demand.
Built for Your Role
What Kaia Legal does for you.
Every role gets a purpose-built operating surface. Not a generic dashboard — a workspace designed for how you actually work in Legal.
Designed to cut review cost per document as the model compounds — measured per engagement, published as measured.
See case strategy, cost tracking, and review completion across all matters. Approve escalations and track ROI.
Confidence-ranked queues put the highest-risk documents first — throughput measured per engagement target.
AI surfaces the highest-risk documents first. Every correction you make trains the model for everyone.
Batch processing scales the desk without scaling headcount — measured per engagement target.
Track batch throughput, SLA compliance, and team productivity across all active matters.
Full EDRM audit trail from collection through production
Every classification, review decision, and correction is logged with timestamp and reasoning.
After signup, you choose your role and land directly in your Kaia Legal workspace.
Full Lifecycle
Every stage of eDiscovery, powered by intelligence.
Intake
Identification, legal-hold preservation, and defensible collection with forensic chain-of-custody.
Processing
Extraction, deduplication, de-NISTing, language detection, and normalization — culling obvious non-responsive material.
Review
AI classifies every document Hot/Warm/Cold/Privileged with confidence + reasoning; low-confidence and privileged routed to the attorney queue.
Analysis
Entity extraction, timeline construction, communication-thread analysis, and privilege clustering for case strategy.
Production
Export to Relativity / Concordance DAT / EDRM XML, court-ready privilege log, automated redaction, and Bates numbering.
Presentation
Exhibit management, case-strategy summaries, timeline visualization, and deposition and trial-prep materials.
Classification
Four categories. One confidence score. Full reasoning.
Highly relevant — key facts, admissions, smoking-gun content requiring immediate attorney review.
Potentially relevant — contextual information, background discussions supporting the case.
Not relevant — routine communications, administrative content that can be deprioritized.
Attorney-client privilege or work product — flagged for privilege review regardless of relevance.
The Learning Loop
Every correction makes the system smarter.
AI Classifies
Upload a document. The Intelligence Engine analyzes it and returns a classification with confidence score and detailed reasoning.
Human Corrects
Vetted practitioners review classifications. If the AI got it wrong, they correct it — selecting the right answer and explaining why.
System Learns
Each correction becomes a governed signal routed to the right learning layer. The model improves, measurably, with every correction.
Intelligence Engine
Every correction flows through the five-layer continuous learning system — from prompt fixes ($0.03, instant) to architecture evolution (monthly, human-required). The triage system routes each correction to the right learning mechanism automatically.
The market has converged on Kaia's architecture: open foundation models, post-trained on proprietary vertical data, measured on frozen sets before every release. The difference that remains is who publishes the measurements.
See the full Intelligence Engine architecture →Legal Differentiator
Court-admissible confidence.
In litigation, AI-assisted review must meet the Daubert standard — reliability, known error rates, peer review. Kaia Legal is designed against that standard, and ships the full record to support it: methodology, frozen evaluation sets, per-release measurements.
RRES
Target Benchmarks
Routing & Resolution Efficiency Score targets per vertical. Instrumentation in progress — auditable publication after production baselining.
0.90
Confidence Threshold
Every classification below 0.90 confidence triggers mandatory human review — a regulated-industry standard. No automated decisions on ambiguous documents.
Lead
The Lead Vertical
Deepest training history, longest learning loop — and the first to carry a published measured benchmark. Privilege accuracy measured continuously on our internal gold set against the serving model — public benchmark publication follows the pre-launch claims audit.
Hold every vendor to the same record
Every accuracy figure on this page is measured on a frozen evaluation set, against the serving model, per release, with the methodology attached. Hold every vendor in this market — including the one you already pay — to the same record.
Bring one closed matter
Already running a legal AI platform? Run one closed matter through Kaia Legal in parallel — same documents, same reviewers, our frozen-set methodology applied to the result. The comparison is yours to keep. Pilot capacity is limited while the practice team scales — early applicants schedule first.
Same Intelligence Engine · Every Kaia Product
Pricing
The number on the website is the number you budget with
Published tiers with directional ranges — before the first sales call. No seat-count arithmetic that changes at renewal. The number you budget with is the number on this website.
See it work. Right now.
Correct one legal decision. Watch accuracy move on the frozen eval set.
Kaia Legal Process
9-Stage Industry Process
eDiscovery operating platform targeting status-labeled privilege detection accuracy, TAR precision, and cost-per-page posture after production baselining. Every governed attorney correction improves tenant-scoped review routing and matter readiness without giving legal advice or making final production decisions.
Kaia runs process preparation, routing, evidence assembly, and correction learning; authorized humans retain final regulated authority.
Identification
Data source mapping, custodian interviews, scope definition
FRCP Rule 26(f) — meet and confer obligation
Preservation
Legal hold notices, collection verification, chain of custody
FRCP Rule 37(e) — spoliation sanctions
Collection
S3 ingestion, batch upload, metadata preservation
Processing
Text extraction, deduplication, language detection, quality scoring
Review
AI classification (HOT/WARM/COLD/PRIVILEGED) + human review
FRE Rule 502 — privilege safe harbor
Analysis
Pattern detection, key facts, privilege clusters, entity extraction, timeline construction
Production
Bates numbering, load file export (EDRM XML/DAT), redaction
FRCP Rule 34 — production requirements
Presentation
Case strategy summaries, timeline visualization, key document highlights
Post-Litigation Intelligence
Knowledge capture, precedent database, cross-matter learning
Target Benchmark Posture
Privilege Detection Accuracy
Target: 95%
Targets presented as targets until production baselines support public RRES publication.