Ask across firm knowledge
Find clauses, obligations, definitions, amendments, and precedent across authorized matter documents without moving those documents to an external AI provider.
↗LexDeploy designs, deploys, and manages private AI environments for legal practices that require data sovereignty, matter isolation, and verifiable answers.
Client documents may carry confidentiality obligations, contractual restrictions, internal AI policy requirements, or simply a risk profile that makes external processing undesirable.
LexDeploy gives the firm another option: run the AI, retrieval system, document index, and governance controls on infrastructure the firm controls.
Find clauses, obligations, definitions, amendments, and precedent across authorized matter documents without moving those documents to an external AI provider.
↗Answers are grounded in retrieved source material and linked back to deterministic document, page, section, and chunk provenance.
↗Identity and matter authorization are applied before retrieval, so semantic search cannot cross into matters the user is not permitted to access.
↗A model-agnostic private RAG platform built around access control, retrieval quality, provenance, and operational isolation.
The generation model can change as stronger local models emerge. The firm's knowledge and governance layer remain.
Citation identifiers are generated by the application from stored document metadata—not invented by the model.
The system narrows the evidence first, then asks the model to reason over the authorized passages that matter.
For most firms, LexDeploy uses controlled remote administration that is separated from the legal-data path. We can monitor health, restart services, and deploy tested releases without routinely exposing document content, prompts, or answers.
Client data stays in the firm's environment while LexDeploy receives restricted, audited administrative access for operations.
No persistent remote management path and no external telemetry. Designed for environments where administrative isolation is itself a requirement.
We build a controlled proof of concept on existing or temporary infrastructure, evaluate representative legal tasks, and use the results to determine whether production deployment makes sense.
Discuss a POC →No per-query or token charges for local inference. The firm owns its production hardware.
Controlled evaluation before a production commitment.
Final scope depends on document-system integration, identity, matter-access controls, deployment topology, and selected security mode.
Managed platform for up to 10 authorized users. Hardware purchased and owned directly by the firm.
The brief covers the private deployment model, RAG and citation path, matter isolation, managed operations, proof-of-concept methodology, implementation scope, and commercial model.
We use a short Google Form for initial lead capture instead of a CRM. No phone number is required.
Start with a focused conversation about your confidentiality requirements, document environment, and the legal tasks worth testing.
Request a private AI assessment ↗No production hardware purchase is required to begin the POC.