The verdict in three sentences
A 15-lawyer business law firm in New York that searches case law and statutes by hand across scattered internal memos and research databases still loses close to a day per lawyer per week. A custom AI legal research assistant costs, as a 2026 order of magnitude, between 50,000 and 90,000 USD, with an index of 8,000 decisions and internal memos and mandatory sourced citations on every answer. Delivered in three months, it saves about 6 hours per lawyer per week without exposing client files to public models.
Why research still drags
A partner at a Midtown business law firm handles commercial litigation, secured transactions, corporate and restructuring matters. For each memo, associates query Westlaw or Lexis, then dig through the firm's own work product: prior briefs, research memos and annotated decisions from the Second Circuit, the Southern District and the New York Appellate Division. The commercial databases are strong, but the firm's own knowledge is scattered across a document management system that keyword search serves poorly.
| Task | Current time | With AI assistant | Gain |
|---|---|---|---|
| Find Second Circuit cases on a UCC Article 9 issue | 2 to 3 h | 15 to 20 min | about 85% |
| Check the applicable version of a statute | 30 to 45 min | 5 min | about 85% |
| Draft a 5-page case law memo | 6 to 8 h | 2 to 3 h | 55 to 65% |
| Find a precedent template in firm archives | 30 min to 1 h | 2 to 5 min | over 90% |
| Summarise a 20-page opinion | 45 min | 5 min + review | about 80% |
| Compare two lines of authority | 3 to 4 h | 1 h | 70% |
The assistant does not replace legal analysis. It retrieves, summarises and cites. Every sentence points to the case name, citation, date and exact passage, and the lawyer clicks through to the source. An answer without a source is blocked: that rule is the defence against hallucinated citations, which have already led to court sanctions in New York.
Architecture and confidentiality
The approach is retrieval-augmented generation: the 8,000 decisions and memos are chunked, indexed and stored in a vector database dedicated to the firm. For each question, the system retrieves relevant passages, then a language model writes an answer from those passages only. Client files and queries never train a public model.
| Item | 2026 order of magnitude (USD) | Comment |
|---|---|---|
| Corpus collection and OCR | 6,000 to 12,000 | 8,000 decisions, statutes, internal memos |
| Indexing and vector database | 9,000 to 16,000 | chunking by legal issue and section |
| Answer engine with mandatory citations | 15,000 to 27,000 | unsourced answers blocked |
| Search interface and history | 9,000 to 16,000 | filters by court, statute, year |
| Security, access rights, audit logs | 8,000 to 14,000 | ethical walls by team and matter |
| Testing with lawyers and training | 3,000 to 5,000 | 200 real validation questions |
| Total | 50,000 to 90,000 | three-month timeline |
Model usage cost stays moderate: for 15 lawyers and 40 to 60 questions a day, API spend runs at roughly 300 to 800 USD a month. Hosting can be a dedicated US cloud tenant with a provider contractually bound to zero data retention, or on-premises with an open model, at higher hardware cost. ABA Formal Opinion 512 (2024) and New York Rule 1.6 require competence with the tool, client confidentiality and informed consent where client data is processed, so the firm's AI policy should be updated before rollout.
Market tools versus custom
Westlaw and Lexis now ship AI features at premium seat prices, often several hundred USD per lawyer per month on top of existing subscriptions. They excel on public case law but do not search your own work product. A custom tool makes sense when the firm holds 10 or 20 years of briefs, memos and templates: that knowledge base is where the assistant adds value the vendors cannot.
Mini case study
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David, partner at a 15-lawyer business law firm in New York, presents the project to his partners. Gain: 6 hours per lawyer per week, or 15 x 6 x 44 weeks = 3,960 hours a year. Valued at a conservative internal rate of 250 USD an hour, the freed time is worth 990,000 USD a year. Even if only 20% of it becomes billed time, the firm recovers 198,000 USD a year. With a 75,000 USD project and 15,000 USD of API and support a year, payback comes in under 5 months.
FAQ
Can the AI invent a case?
The system refuses any answer not grounded in a passage from the indexed base. During testing, 200 real questions confirm that 100% of citations point to an existing document.
Are client files sent to a public model?
No. The provider contract excludes training on your data and limits retention to 0 or 30 days. On-premises hosting with an open model is possible for an extra 30,000 to 60,000 USD in hardware.
How does the base stay current?
New decisions and memos are added by drag and drop and indexed within minutes. Count 2 to 4 hours a month for a librarian or paralegal.
Does the firm need technical staff?
No. The interface works like a search engine. A 2-hour training session is enough, and the vendor handles technical maintenance.
Can it connect to our document management system?
Yes. iManage and NetDocuments expose APIs, and syncing with matter-level permissions adds 3 to 5 weeks to the project.
Let's scope your project. We inventory your case law and work product, set confidentiality rules and deliver a citation-backed assistant within three months. Detailed quote within 48 h. WhatsApp +221 77 596 93 33.
Mohamed Bah
Fondateur, Kolonell
Passionate about digital and entrepreneurship in Africa, Mohamed has been helping Sénégalese businesses with their digital transformation since 2020. Founder of Kolonell, he believes every SME deserves a professional and accessible online présence.
