Litigation firms
Chronologies, deposition summaries, and discovery drafts from records and productions — cited to the Bates page.
Private AI for confidential work
AI that keeps confidences.
JMNI Labs builds private AI for work that can't go to a public AI service. Your files stay on your computer, the AI runs on open models we operate — never a third-party AI vendor — and nothing is kept.
Built on
Open-weight modelsNVIDIA infrastructureZero data retentionNo third-party AI vendors
Products
Two products. One promise.
Your information stays under your control. Everything else — the models, the infrastructure, the updates — we handle.
For law firmsDesign partners
Ward
Private AI for law firms. Built first for litigation.
Bates-cited chronologies, deposition summaries, and discovery drafts from your own case files — with every cite checked and every AI use logged for your client.
- No hardware to buy — runs on your firm's computers
- Files stay on your computers; nothing retained
- Per-matter AI-use certificates
For learningPrivate preview
Recitation
Your personal university professor.
Upload any textbook and get a complete course — curriculum, interactive lectures, graded problem sets, and a professor that remembers you.
- Runs entirely on your own machine
- Grounded in your book, with page citations
- Free for individual learners
Who we serve
For people with something to protect.
Every practice area
Ask questions of your files, draft in your templates, and transcribe dictation — whatever kind of law you practice.
Schools
AI tutoring on hardware the institution controls, so student data and course materials stay on campus.
Teams
Train staff on internal manuals and procedures — documents that should never touch a public AI service.
Where your data lives
Private by design, not by promise.
Most AI tools ask you to upload everything and trust the vendor. Ours work the other way around: your documents stay where they are, and the AI sees only what a single question requires.
- Files stay on your computer. Documents are indexed locally, never uploaded wholesale.
- Zero retention. Requests are processed and discarded, never used for training.
- No third-party AI. Open-weight models on hardware JMNI Labs operates.
Where your data lives
JMNI Ward
- Your documents
- Your computer
- Search index
- Your computer
- Passages for a question
- JMNI private inference · encrypted
- Kept after the answer
- Nothing
- Third-party AI vendors
- None
Model updates tested in our labJMNI Labs
JMNI Research
We measure what local AI can really do.
Behind the products is our research lab: six NVIDIA GB10 systems where we run frontier open-weight models across switchless multi-node rings — and record every result.
It's how we plan our inference capacity from measurements instead of guesses, and how every model update is tested before it reaches a customer.
1Mtokenscontext retrieval benchmarked on a four-node ring
8 × 258Kconcurrent long-context sessions verified on two nodes
~2,400tok/sprefill on a single GB10 system
0network switches in the model path
Measured on the JMNI Research fleet. Methodology and limits →
Field Notes
From the lab.
Bring AI into your firm.
We're working with a small number of litigation firms as design partners. Bring a deposition or a stack of records, and we'll show you what Ward does with it.