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Legal AI That Gives Attorneys Back the Hours Lost to Research, Review, and Intake
Bitontree builds privilege-aware AI for legal research, contract review, matter intake, and case-brief drafting with citations and audit trails. We embed senior AI engineers into your firm's workflow to wire it into iManage, NetDocuments, Clio, and Microsoft Word and Outlook, using vendor configurations that contractually exclude training on your client data, then stay to run and improve it.
50%
Research time saved
Legal research automation at a US legal advisory firm
0
Models trained when vendor contracts exclude client-data training
Privilege and confidentiality enforced by architecture and vendor posture
Cited
Answers traceable where retrieval is configured
Grounded retrieval with audit logs for defensible work product
Where does billable and non-billable time actually leak in a legal practice?
Law firms and legal advisory teams lose hours to research, review, and intake that AI can compress, but only if it respects privilege and produces defensible, cited work. These are the five drains we build for.
Research hours that don't scale
Associates spend hours running down precedent, statutes, and prior matters across databases and the firm's own document store. The work is essential but it doesn't scale with caseload.
Contract review volume
Reviewing agreements for clauses, risks, and deviations from standard terms is slow, repetitive, and error-prone at volume. Important issues hide in long documents under deadline pressure.
Intake and matter triage
New matters arrive by email, form, and call and need to be classified, conflict-checked, and routed before work can begin. Manual triage delays response and frustrates clients.
Due diligence document review
Diligence means reading thousands of documents to surface obligations, change-of-control terms, and red flags against the clock. Manual review is expensive and hard to staff at peak.
Privilege-aware drafting
Attorneys want AI help drafting briefs, memos, and correspondence, but not at the cost of confidentiality or with answers they can't trace to a source. Generic chat tools fail both tests.
What legal AI systems does Bitontree build?
Six production systems built for the way attorneys work and the systems of record they live in, all delivered through our AI development services.
Legal Research Automation
Retrieval-grounded research over case law, statutes, and your firm's prior work that returns answers with citations to source, not unsourced summaries. Compresses the hours associates spend running down precedent.
Contract Review AI
Reviews agreements for key clauses, risk terms, and deviations from your playbook, flagging issues with the exact location in the document. Turns hours of line-by-line reading into a prioritized review queue.
Matter Intake & Triage Agent
Classifies incoming matters, runs conflict checks against your system of record, and routes them to the right team with a drafted summary. Cuts the delay between a client reaching out and work beginning.
Due Diligence Document Review
Reads diligence data rooms to surface obligations, change-of-control clauses, and red flags into a structured, sourced report. Lets a small team cover a document set that used to need many reviewers.
Privilege-Aware Drafting Assistant
Drafts briefs, memos, and correspondence grounded in your matter documents and precedents, with citations and vendor configurations that contractually exclude training on your client data. Built inside Word and your DMS so it fits the existing workflow.
How we build legal AI that protects privilege and stands up to audit
In legal work the controls are the product, an answer you can't trace or a tool that leaks client data is worse than no tool at all. We build into your document and practice systems with confidentiality enforced by architecture.
iManage, NetDocuments, and Clio integration
We connect to your document and practice-management systems of record so the AI works on your real matters and your DMS stays authoritative, reading and writing only approved content.
Microsoft Word, Outlook, and SharePoint
Drafting, review, and intake surface inside the tools attorneys already use, Word, Outlook, and SharePoint, instead of forcing a separate app and a new workflow.
Attorney-client privilege and confidentiality
Architecture supports confidentiality boundaries between matters and clients, so the AI only sees what a given user is entitled to see. Privilege is a design constraint, not a setting.
No training on your client data
We use vendor stacks and configurations that contractually exclude training on your matters and documents and keep them within your agreed boundary.
Citations, audit logs, and data residency
Answers include source citations where retrieval is configured, actions are logged for audit, and data residency is configured to your jurisdiction so the work product is defensible.
Ownership and tuning after launch
We ship with evals for citation accuracy and retrieval quality, on-call response, and ongoing tuning as your playbooks and precedents evolve. You own the code, evals, and prompts.
What our legal AI systems handle
Every legal AI system Bitontree builds is configured for your practice areas, playbooks, DMS, and privilege requirements. These are the most common starting points.
| USE CASE | OUTCOME |
|---|---|
| Legal research and precedent | 50% research time saved (US legal advisory firm) |
| Contract review | Clause-level risk flags with in-document citations |
| Matter intake and conflict checks | Faster routing with a drafted summary, human-approved |
| Due diligence document review | A small team covers a large data room with sourced findings |
| Brief and memo drafting | Privilege-aware drafts with citations, inside Word and your DMS |
| Firm knowledge access | Grounded, cited answers over iManage and NetDocuments |
Frequently Asked Questions
How long does it take to deploy a legal research or contract review system?
A focused legal research or contract review deployment typically goes live in 4 to 8 weeks, with broader intake and diligence automation following over the next quarter. Most teams see grounded, cited answers on their own matters within the first month; connecting to your DMS and configuring privilege boundaries is usually the longest phase, not the AI.
Does legal AI replace attorneys and paralegals?
No, it compresses the research, review, and intake hours so attorneys and paralegals focus on judgment and client work. Every output is cited and surfaced for human review before it is relied on. At the US advisory firm where this is live, the result was 50% research time saved, not headcount removed.
How do you protect attorney-client privilege and keep client data confidential?
Confidentiality is supported by architecture: the AI only sees what a given user is entitled to see, matters are isolated, vendor stacks contractually exclude training on your content, and every action is logged for audit. We configure data residency to your jurisdiction and preserve attorney review before output is relied on.
What systems and data do you need to get started?
Access to your document and practice systems of record, typically iManage, NetDocuments, or Clio, and the matter content you want the AI to work on, surfaced through Word, Outlook, and SharePoint. We work within your existing permissions so the AI inherits the access controls you already enforce.
Should we build this in-house, buy a tool, or embed a team?
Off-the-shelf legal AI tools are fast to try but rarely fit your playbooks, your DMS, or your privilege boundaries, and your work product lives in their stack. An embedded team builds on your systems with confidentiality enforced by design, leaves you owning the code and evals, and stays to run it as your precedents change.
Are AI-generated research and drafts defensible for the work we rely on?
Yes, when built for defensibility, every answer is traceable to its source, attorneys review before relying on output, and audit logs record who generated and approved what. We ground answers in retrieval over your authoritative sources rather than open-ended generation, so citations can be checked.
Legal AI, Guides and Practice Insights
How we build, integrate, and run privilege-aware production AI for law firms and legal advisory teams.
Want to see where AI gives your attorneys hours back without risking privilege?
A 30-minute working session with a senior AI engineer, no slideware. We pressure-test your research, review, and intake workload against your DMS and privilege requirements, and come back with an honest read on feasibility and the shortest path to production.
Let's scope your legal AI build
Tell us about the research, review, or intake workload you want AI on. We'll come back with an honest read on what's buildable, what isn't, and the shortest path to production, usually within one working day.
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Years Of Experience
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