Contract review & clause extraction
Surface risky clauses, missing terms and deviations from your playbook, with citations.
AI Solutions · Legal
AI for Legal
We are a senior-led AI development company, building production AI for law firms and in-house teams — contract review, legal research, drafting assistants and due-diligence review — grounded in your documents, with citations, and confidentiality preserved.
The Legal reality
Legal work is reading, research and drafting at volume — exactly what AI accelerates — but it is also confidential, privileged and unforgiving of a made-up citation. The value is real: contract review, research and first drafts can move far faster. The requirement is equally real: nothing can leave your perimeter, every answer must cite its source, and a lawyer signs off. We build legal AI that is grounded in your documents and law, cites everything, and keeps confidentiality and privilege intact.
Who we build for in Legal
- (01)law firms modernizing document-heavy practice areas
- (02)corporate and in-house legal teams
- (03)legaltech startups building AI-first products
AI use cases for Legal
6 areas
Where AI creates real, measurable value in legal — each of these is something we build into production, not a slide.
Legal research RAG
Answer research questions from your matter documents and sources, citing the exact passage.
Drafting assistants
Draft first versions of contracts, memos and correspondence from your templates for lawyer review.
Due-diligence review
Review large document sets to flag issues, obligations and anomalies for the deal team.
Intake & matter triage
Structure new-matter intake and route work with a completeness and conflict check.
Compliance & policy Q&A
An assistant that answers policy and compliance questions from your own materials.
How we deliver
6 capabilities
We build AI that does work, not AI that demos well. Every system ships with an evaluation suite, a measured cost-per-task, full logging of every decision, and a defined human handoff for low-confidence cases — and it can run inside your own cloud when data cannot leave your perimeter. We partner with a limited number of companies at a time and design to a real business outcome, not a feature list.
AI agents & automation
Goal-driven agents that plan, call tools and complete multi-step work, with guardrails and a human fallback.
Generative AI & LLM apps
Copilots, assistants and custom LLM applications built on Claude, GPT and open models, benchmarked per task.
RAG & knowledge systems
Your documents, tickets and databases turned into an answer engine your team actually trusts — with citations.
Machine learning & prediction
Forecasting, scoring, classification and computer-vision models wired into the systems you already run.
Evaluation & guardrails
Test suites, confidence thresholds, cost dashboards and logging from the first sprint — not bolted on later.
Secure deployment
Shipped into your own cloud account with monitoring you own, for teams with data-residency or compliance needs.
Why Legal teams choose Suthar
- Confidential and cited. Nothing leaves your perimeter, every answer cites its source, and a lawyer signs off — privilege and accuracy preserved, no black-box guessing.
- Senior-led, no hand-off. The senior engineers who scope your Legal project write the code — no account managers, no junior team.
- Built to a real outcome. We design to a measurable result — hours saved, tickets deflected, cycle time cut — not a feature list.
- You own everything. Your repositories, your infrastructure, full code and IP transfer documented at handover.
Questions
Legal
AI FAQ
We deploy inside your own environment so documents never leave your perimeter, with access controls and logging. Client data is not used to train third-party models, and confidentiality is designed in from the first sprint.
We use retrieval-grounded systems that answer only from your documents and sources and cite the exact passage, with confidence thresholds that flag uncertainty. A lawyer always reviews before anything is relied upon.
Yes. We connect to your DMS and existing tools through their APIs so review, research and drafting happen within the systems your practice already uses.
Almost always with a paid discovery sprint — one to two weeks that ends with a fixed scope, timeline and price. If we conclude the project should not go ahead, we will tell you, and you keep the work.
You do, completely. Your repositories, your infrastructure, and full IP transfer documented at handover — including anything produced during discovery.
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