A litigation attorney in Boston receives 15,000 pages of discovery documents in a wrongful termination case. Her job: find every mention of the plaintiff, identify all performance reviews, and flag potentially relevant communications. With junior associates billing $250/hour, manual review would cost $75,000 and take 3 weeks. Even with keyword search, context matters — 'Smith performed well' and 'Smith performed poorly' both contain 'Smith performed' but have opposite implications.
Document review is the largest cost in litigation, representing 70% of discovery expenses. Large firms use enterprise tools like Relativity ($50K+/year) with AI-assisted review (TAR — Technology Assisted Review) to cut review time by 80%. But small litigation firms handling 5-10 cases per year can't justify enterprise licensing. They either do manual review (expensive) or use basic PDF search (misses context).
Kira Systems and Luminance are enterprise-only with implementation timelines measured in months. eBrevia was acquired by DFIN. The opportunity is document intelligence at $99-199/mo for small litigation firms: upload a document set, AI extracts key entities (people, dates, companies), automatically identifies document types (contracts, emails, memos), creates a searchable timeline, and flags potentially relevant documents based on case parameters. Not full eDiscovery — just the 'make sense of these documents quickly' piece. Target solo litigators and small firms handling document-heavy cases who need AI assist without enterprise pricing.
💰 Revenue Blueprint
Three-tier value ladder to monetize from day one
Up to 5,000 pages, entity extraction, document classification, basic search
Unlimited cases, AI relevance scoring, timeline view, export to Clio/matter folders
Team access, custom training, privilege detection, advanced analytics, API
📊 Market Evidence
The Market Gap
Relativity/Kira are enterprise-only ($50K+/yr). No affordable AI document analysis for small litigation firms at $99-199/mo. Clear value: reduce $75K review to $5K.
🏆 Competitor Landscape
How existing players stack up in this market
| Competitor | Pricing | Notes |
|---|---|---|
| Kira Systems | Contact sales (Enterprise) | Contract analysis, Litera company |
| Luminance | Contact sales | AI document review |
| Relativity | Contact sales | eDiscovery + AI review |
| Eigen Technologies | Contact sales | Document intelligence platform |
| Docusign Insight | Contact sales | AI contract analytics |
Contract analysis, Litera company
AI document review
eDiscovery + AI review
Document intelligence platform
AI contract analytics
🛠️ Recommended Tech Stack
Suggested tools and technologies to build this idea
Score Breakdown
Good market signals with room for growth
Market (20%) + Revenue (20%) + Trend (15%) + Competition (15%) + Build (15%) + Pricing (15%)
🚀 Start Building
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Build a SaaS product called "Document-to-Insights for Law Firms". ## Product Overview AI summarization of legal documents ## Problem AI summarization of legal documents ## Solution Build Document-to-Insights for Law Firms ## Target Audience indie hackers, small businesses, and solopreneurs ## Tech Stack - Next.js 15 (App Router) with TypeScript - Tailwind CSS v4 for styling - Supabase for auth, database, and storage - Vercel for deployment - shadcn/ui for UI components - Framer Motion for animations ## MVP Features to Build 1. Landing page with clear value proposition 2. User authentication (sign up, sign in, forgot password) 3. Core product functionality based on the solution above 4. Dashboard for users to manage their data 5. Pricing page with at least 2 tiers (free + paid) 6. Basic settings/profile page ## Known Competitors Kira Systems, Luminance, Relativity, Eigen Technologies, Docusign Insight ## Key Risks to Address Standard market entry risks ## Deployment 1. Set up Supabase project and configure environment variables 2. Deploy to Vercel with `npx vercel --prod` 3. Set up custom domain 4. Configure Supabase RLS policies for security ## Instructions Start by creating the project structure, then build the landing page first. Use server components where possible. Make it mobile-responsive from the start. Focus on getting the core value loop working before adding polish.