AI for legal, proven in production
Legal AI uses large language models and retrieval to research case law, review contracts, draft documents, and deliver legal guidance, with citations on every answer. We built Lawep, a world-first AI legislative drafting system, and Inpro, an AI consultation platform that delivers legal guidance at 85 percent lower cost. This page covers how the legal industry actually uses AI, with the delivered systems to prove it.
Why the Legal Industry Is Hard for AI
Legal work punishes the shortcuts generic AI takes:
Hallucinated Citations Are Disqualifying
A made-up case citation is worse than no answer. Legal AI must cite real, verifiable sources or say it does not know.
Privilege and Confidentiality
Sending privileged documents to a public model with no audit trail is a risk firms, departments, and governments cannot take.
Jurisdiction Is Everything
An answer that is right in one jurisdiction is malpractice in another. Generic tools trained on public data cannot tell the difference.
Access to Justice Is Priced Out
At $200 to $500 per hour, 80% of low-income people cannot access legal help. The need is enormous; the delivery model has not scaled.
How the Legal Industry Uses AI Today
Four patterns we have shipped for legal organizations:
Legislative Drafting and Policy Research
From Months to Weeks
- AI trained on legislative history, case law, and policy frameworks
- Drafts bills and acts with constitutional and precedent checks
- Cites the source behind every clause
- Behind Lawep: 15 bills drafted in 6 months across 8 jurisdictions
Consumer Legal Consultation
Legal Guidance That Scales
- AI chatbot that analyzes a situation and gives clear, sourced guidance
- Escalates to a human lawyer when the matter needs one
- Behind Inpro: 50,000+ consultations in year one at 85% lower cost
- 92% user satisfaction
Research and Contract Intelligence
Your Firm's Knowledge, Searchable
- Research over your matters plus Westlaw and LexisNexis, with citations
- Research time: 8 to 12 hours per case down to about an hour
- Contract review against your playbook, flagging deviations
- Review time: 3 hours down to about 30 minutes
Confidential by Design
Built for Privileged Data
- Deployment options: your cloud, on-premise, VPC isolated, or air-gapped
- End-to-end encryption, role-based access, full audit logging
- Your documents never train anyone else's model
- SOC 2 ready, GDPR compliant
THE EDGEFIRM DIFFERENCE
Unlike legal AI products (Harvey, Spellbook):
- • Built for your matters, playbooks, and jurisdiction
- • You own the code and infrastructure
- • No per-seat licensing fees
Unlike large consultancies:
- • 4 to 5 month delivery, not 18 to 24
- • Fixed-price engagements
- • Production code from day one
Unlike DIY experiments:
- • Citation and evaluation frameworks proven in production
- • Two delivered legal AI platforms
- • Confidentiality architecture from day one
Built on Production-Grade Legal AI Infrastructure
Foundation Models
- GPT-4 & GPT-4 Turbo
- Claude 3.5 Sonnet
- Llama 3.1 & Mistral
- Azure OpenAI
- AWS Bedrock
Retrieval & Knowledge
- Pinecone
- Weaviate
- pgvector
- Westlaw / LexisNexis APIs
- Citation engines
Frameworks & Orchestration
- LangChain
- LangGraph
- LlamaIndex
- Custom Python
- Evaluation harnesses
Infrastructure & Security
- Docker/Kubernetes
- AWS/GCP/Azure
- SSO (Okta, Azure AD)
- End-to-end encryption
- SOC 2 ready
Legal AI Across the Industry
Governments and Legislatures
Drafting Law With AI
Challenges
- • Drafting a bill takes legislators and researchers months
- • Policy research spans decades of legislation and case law
- • One missed precedent can undermine an entire act
Our Solutions
- • AI trained on legislative history, case law, and policy frameworks
- • Drafts bills and acts with constitutional and precedent checks
- • Cites the source behind every clause
Typical Results
- • Drafting time: months down to weeks
- • 15 bills drafted through the platform in 6 months
- • 8 jurisdictions using the system
Illustrative outcomes from comparable deployments. Actual results depend on your data, scope, and use case.
Lawep - World-First Legislative Drafting
"A world-first AI system for researching, drafting, and enacting policy and legislation, built on large language models and retrieval over legislative history."
Read Full Case StudyHow We Deliver Legal AI in 4 to 5 Months
Discovery and Data Preparation
- Interview stakeholders and document the highest-value use cases
- Inventory matters, precedents, templates, and playbooks
- Ingest documents into a private vector database
- Build an evaluation set with ground-truth answers
Deliverable: Technical architecture, data readiness report, project roadmap
Core System Development
- Build the retrieval and citation engine
- Implement drafting, review, or consultation logic
- Create prompt templates and jurisdiction rules
- Test accuracy against the evaluation set
Deliverable: MVP with citations and 80% plus accuracy on core tasks
Integration and Interface
- Connect to your document system and matter management
- Build the interface in web, Teams, or your existing tools
- Add access controls, audit logging, and PII handling
- Run acceptance testing with a pilot group
Deliverable: Production-ready system with all integrations
Refinement and Launch
- Improve accuracy based on pilot feedback
- Handle edge cases and add error recovery
- Document everything and train your team
- Soft launch, then full rollout
Deliverable: Organization-wide legal AI system plus 30 days support
Transparent Pricing for Legal AI
Typical Investment Range
$75,000 - $175,000
Full project delivery in 4 to 5 months
Factors that affect pricing:
Data Complexity
Volume of matters and documents, quality, and update frequency
Use Case Sophistication
Research Q&A versus drafting versus multi-step consultation
User Scale
Number of users, query volume, and response time needs
Deployment and Compliance
Cloud versus on-premise versus air-gapped, and confidentiality requirements
What's Included:
Common Questions About AI for Legal
Four patterns dominate in production: legal research with citations over a firm's own matters plus external case law, contract review against a playbook, document and legislative drafting from templates, and AI-powered consultation for routine legal guidance. We have shipped all four, including Lawep for legislative drafting and Inpro for consumer consultation.
Only if it is built for that. Our legal AI systems retrieve from indexed sources and cite the exact matter, clause, or case behind every answer. If the answer is not in the available data, the system says so rather than inventing a citation. We validate against an evaluation set with ground-truth answers before launch.
It can be, with the right architecture. We deploy in your own cloud tenant, on-premise, or air-gapped, with end-to-end encryption, role-based access, and full audit logging. Your documents never train anyone else's model.
From our delivered systems: legislative drafting time cut from months to weeks with 15 bills drafted in 6 months (Lawep), legal consultation at 85% lower cost with 50,000+ consultations in year one (Inpro), research down from 8-12 hours to about 1 hour, and contract review from 3 hours to about 30 minutes.
Products like Harvey or Spellbook are fast to adopt but generic: they do not know your matters, playbooks, or jurisdiction, and you pay per seat forever. A custom build costs $75,000 to $175,000 once, ships in 4 to 5 months, and you own the code. The right answer depends on how distinctive your workflows and data are.
Built With These Services:
Legal AI Development
Our dedicated legal AI service, covering research, drafting, and review on your own data.
Learn MoreCustom LLM & RAG Development
The retrieval and citation foundation behind every legal AI system.
Learn MoreIntelligent Process Automation
Automate intake, document handling, and compliance workflows around the AI.
Learn MoreAI Consulting
Scope where AI fits your legal organization before committing to a build.
Learn MoreReady to Transform Your Business with AI Solutions?
Schedule a free strategy call to discuss your project and get a custom AI implementation roadmap.
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