Your Associates Are Drowning in Document Search While Your Margins Evaporate
If you're a managing partner watching billable hours vanish into clause searches, you're funding the problem AI already solved.
Your associates spend 4 hours searching for precedent clauses across thousands of contracts. Your intake team qualifies leads over 3 email exchanges. Your billing descriptions are written at 11pm from memory. We build a RAG system over your document library -- 10,000 contracts ingested into pgvector. A lawyer asks show me all non-compete clauses from our pharma client contracts in 2026 and gets results with citations in seconds.
Your associate opens the DMS at 9pm, types "non-compete," and gets nothing -- because the clause you need says "restrictive covenant." Legal AI Integration fixes this. Your firm gets semantic search that understands meaning, not just keywords. It retrieves precedent clauses in seconds, drafts motion language from your existing work product, and qualifies intake leads while your team sleeps. Every response cites the exact document, page, and clause -- no hallucinated case law. Your data stays in your infrastructure. The Claude API processes queries in memory without training on your files. Full audit logs for privilege review. Access controls at the document level. This isn't ChatGPT cosplaying as counsel -- it's built for legal precision, connects to Clio and Smokeball, and typically pays for itself in recovered billable hours within 6–8 weeks.
What is holding your current website back?
Manual document search, repetitive drafting, and admin tasks that burn billable hours.
What Your Website Could Look Like
Custom-designed for your industry. No templates. No stock photos.
How We Build This Right
Every safeguard, built in from Day 1.
Contract Analysis RAG
We've ingested 10,000+ contracts into pgvector and the search holds up. You ask about non-compete terms, the system finds relevant clauses even when the underlying document uses different language entirely. Want to compare how non-competes have been structured across 40 deals? Done. And every result cites the specific document and page number.
Case Research Assistant
Query your own case law research and internal briefs in plain English. The AI surfaces relevant precedents, gives you a summary of each holding, and flags distinguishing factors between cases. All with citations you can actually verify before relying on them in court.
Client Intake Automation
AI handles the first conversation with a new lead on your website -- 24/7, not just during business hours. It captures case details, figures out whether the matter fits your practice areas, and routes it appropriately. By the time it hits your CRM, there's already a full case summary waiting for whoever picks it up.
Billing Description Generator
Drop in a time entry, get back a professional billing narrative that actually justifies the hours. It's pretty straightforward -- attorneys log what they worked on, AI converts cryptic shorthand into descriptions that hold up to client scrutiny. Fewer write-downs, less time reconstructing your own day.
Document Drafting
Template plus actual case context equals a real working first draft -- not a blank page. Pleadings, demand letters, briefs. The attorney's job becomes reviewing and refining rather than staring at a cursor. That's a fundamentally different workflow.
Knowledge Management
Every document, every brief, every internal memo gets indexed and searchable by meaning -- not just by filename or exact keywords. So when someone leaves the firm, the knowledge they accumulated doesn't walk out with them. It stays, accessible, forever.
What We Build
Purpose-built features for your industry.
Retrieve precedent clauses across 10,000 documents by concept, not keyword match
Your team stops burning 3–4 billable hours per day hunting for clauses manually
Generate draft motions and discovery responses from your existing work product
New leads get qualified responses in minutes instead of losing them to faster competitors
Qualify client intake leads with jurisdiction-specific questions before handoff
Billing descriptions write themselves from actual case activity, reducing write-downs
Analyze contracts for non-standard clauses and flag risk provisions automatically
Unusual contract terms get flagged before they surface in litigation two years later
Surface institutional knowledge from files created by attorneys no longer at the firm
Decades of accumulated legal work becomes searchable by meaning, not filename archaeology
Reconstruct billing narratives from cryptic time entries logged days earlier
One associate recovering 2 hours daily pays for the system within 6 weeks at market rates
Built on a Modern, Secure Stack
Our Development Process
From discovery to launch. Quality at every step.
Document Audit
Week 1We start by cataloging your actual document library -- what's there, how it's organized, which practice areas it covers. Then we map out the highest-value search use cases specific to your firm and design the ingestion and indexing strategy around those priorities.
RAG Architecture
Week 2Next comes the technical architecture: pgvector embedding pipeline design, chunking strategy, retrieval parameter tuning. We also work through security requirements and privilege considerations before a single document gets processed.
Ingest and Index
Week 3-5Then we actually run it -- processing and embedding your full document library. We test search quality against known queries where we already have verified answers, so we can measure accuracy before attorneys ever touch the system.
Build Workflows
Week 6-8Client intake chatbot, billing description generator, document drafting templates -- all configured and integrated with your practice management system. Each module is tested against your actual workflows, not generic demos.
Training and Launch
Week 9-10Attorney training, workflow customization, and go-live. Plus 30 days of post-launch tuning and support, because the first month always surfaces edge cases worth fixing.
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