Large law firms accumulate decades of work product in DMS folders, email, and matter files — when a new matter comes in, the precedent brief or deal structure the firm drafted 3 years ago is effectively invisible. DeepJudge is an AI-powered enterprise search platform that indexes a firm’s internal institutional knowledge and makes it searchable via hybrid keyword + semantic search, so attorneys can ask ‘have we done this before?’ and get cited answers grounded in the firm’s own documents. Founded in 2021 by ex-Google search engineers (CEO Paulina Grnarova, ETH Zurich PhD) in Switzerland. Total funding ~$52M ($10.7M seed led by Coatue; $41.2M Series A led by Felicis, Nov 2025, ~$300M pre-money valuation per Sacra). Key differentiator: searches the firm’s own knowledge, not public legal databases — the Thomson Reuters partnership (Oct 2025) bridges this gap by integrating DeepJudge into CoCounsel Legal for a ‘360-degree view’ combining internal + external content. Named customers: Freshfields (Magic Circle), CMS Switzerland (deployed on Azure). SKILLS.law NPS survey (Apr 2025, ~100 KM/innovation leaders at top firms): ranked #1 most recommended legal AI vendor. ~78 employees. 15K+ LinkedIn followers. Deployment: on-prem, client cloud (Azure/AWS/GCP), or managed hosting — firms choose where data lives and which AI models to use (LLM-agnostic). SOC 2 Type II + ISO 27001 certified. Ethical walls and access controls synchronized with source systems. Does not train on client data. AI Workflows feature (Mar 2025): low-code/no-code builder for custom AI agents (e.g., Negotiation Intelligence, Find Answers). Claude Cowork integration (Feb 2026). Reddit sentiment strongly positive: ‘best enterprise search tool I have used in 12+ years of legal tech’ (r/legaltech). No G2/Capterra presence. Pricing not publicly available — enterprise contracts only, can be bundled with Thomson Reuters subscription. Not suitable for solo/small firms or in-house corporate legal departments — exclusively BigLaw/large firm positioned. No quantitative ROI metrics published by any customer.
Company Info
- Founded: 2021
- Team size: 11-50 employees
- Funding: $10.7M
- HQ: Switzerland
- Sector: Knowledge Management
What We Haven’t Verified
This page was assembled from publicly available information. Feature claims and workflow mappings are based on what the vendor and third-party listings publish — not hands-on testing or practitioner feedback.
Workflows
Based on practitioner evidence, Deepjudge is used in these workflows:
What practitioners struggle with
Real frustrations from legal professionals — the problems Deepjudge addresses (or should address). Sourced from practitioner reviews, Reddit threads, and case studies.
BigLaw firm with 1,000+ lawyers has decades of work product locked in DMS folders — the precedent brief the partner drafted 3 years ago is unfindable, institutional knowledge walks out the door when partners leave, and junior associates waste hours recreating work that already exists somewhere in the system
BigLaw KM team has decades of federal court briefs, motions, and orders scattered across DMS and individual attorney drives — no way to systematically capture, index, and surface relevant precedent filings when a similar motion comes up in a new case
Mid-size law firm has used the same desktop billing software for 15 years and it works, but remote attorneys can't access it from home, new hires expect a browser-based interface, and the managing partner is worried about the vendor sunsetting the product — the switching cost feels enormous because 15 years of billing history and custom templates live in that local database
When my firm's 20-year-old desktop billing system finally can't run on the newest Windows, I need to migrate decades of billing history to a cloud tool without losing client records, archived invoices, or trust account balances — and the attorneys refuse to learn anything that looks different
PE firm's junior associate preparing a sell-side data room for a portfolio company exit has 4,000 documents dumped from the target company's shared drive — manually categorising contracts, financials, HR records, and IP filings into a diligence-ready folder structure takes two weeks, and mis-filed documents mean buyers either can't find critical disclosures or see draft versions instead of executed contracts
Where it fits in your workflow
Before Deepjudge
Law firm accumulates decades of work product in DMS (iManage, NetDocuments), email, matter management systems, and shared drives. When a new matter comes in, attorney or KM team needs to find relevant precedent — prior briefs, deal structures, contract clauses, memos — across all these repositories. Associates waste hours searching iManage folders manually or recreating work that exists somewhere in the system.
After Deepjudge
After DeepJudge surfaces relevant internal documents → attorney reviews and adapts precedent for current matter → AI Workflows automate specific tasks (Negotiation Intelligence analyzes firm's historical negotiation positions; Find Answers provides cited responses grounded in prior work). Thomson Reuters CoCounsel integration adds public legal research layer on top of internal search results.
Integrations & hand-offs
DMS (iManage/NetDocuments) → DeepJudge (indexing + semantic search + AI workflows) → CoCounsel Legal (public law research augmentation) → drafting tools (Word, contract platforms) → matter management / billing systems. Low-code/no-code workflow builder reduces dependency on vendor for customization.
Also used by similar teams
Community Data
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