Introduction
Sentinel is an enterprise SaaS platform for legal compliance monitoring and eDiscovery. It gives legal and compliance teams one place to ingest large volumes of documents and communications, make them instantly searchable, review and code them, and surface the facts that matter — supported throughout by an AI assistant that is grounded in your own evidence rather than the open web.
Who Sentinel is for
- Litigation teams managing discovery: collecting custodian data, reviewing productions, logging privilege, building productions, and preparing for depositions, hearings, and trial (including jury selection).
- Corporate / transactional teams running deals: organizing diligence data rooms, tracking document request lists, and working due‑diligence checklists.
- Real‑estate teams managing property transactions with deal pipelines, diligence, and closing checklists.
- Compliance and investigations teams monitoring communications and documents against regulatory frameworks.
What makes Sentinel different
Everything is searchable, by meaning. Every file that enters Sentinel flows through a single ingestion pipeline that extracts text (running OCR on scans and multimodal extraction on images, audio, and video), deduplicates it, and builds a searchable index. There are no feature‑specific "silos" that the search layer can't see — a document you upload to a data room, a transcript from a deposition, and an email pulled from a monitored mailbox are all findable the same way. See Core Concepts → The content pipeline.
An AI assistant you can trust. Emma, the built‑in assistant, answers questions about your matter using only what your documents actually say. When Emma references a document she does so with a citation token that is mechanically verified against the documents a tool actually returned — if a response references a document that wasn't retrieved, the system blocks it. This "citation grounding" is core to keeping AI output defensible as legal work product. See Emma → Citations and guardrails.
Your data stays in your environment. Sentinel is multi‑tenant by design, but each customer's documents live in that customer's own database and storage. AI calls that leave the environment for inference are configured to not retain your data. See Security & Compliance.
The shape of the product
At a high level, you work in Sentinel like this:
- Pick a matter. A matter is a case (litigation), a deal (transactional), or a property transaction (real estate). It is the container for all of that work's documents, sessions, findings, and analysis.
- Get documents in. Upload them, share an upload link with a client, import a court docket, or connect a monitored mailbox. Sentinel ingests and indexes everything automatically.
- Find and review. Search by keyword or meaning, open documents in the review workspace, tag and code them, and ask Emma questions.
- Produce the work. Build Bates‑stamped productions, maintain a privilege log, draft motions, work checklists, prepare for depositions, and export.
Practice modes at a glance
The interface adapts to one of three practice modes per tenant:
| Mode | Primary objects | Representative features |
|---|---|---|
| Litigation | Cases, custodians | Discovery review, productions, privilege log, motions, jury selection, depositions |
| Transactional | Deals, counterparties | Deal data rooms, request lists, due‑diligence checklists, business intelligence |
| Real Estate | Properties, stakeholders | Deal pipeline, diligence, closing checklists |
Practice mode is set per tenant by an administrator (and by Sentinel during provisioning). See Core Concepts → Practice modes.
How to use this documentation
- The Getting Started section gets you signed in and oriented.
- Core Concepts is the single best page to understand the whole system.
- The User Guides each cover one feature in depth.
- Administration, Integrations, API Reference, and Security & Compliance are reference material for admins, integrators, and evaluators.
- The FAQ and Glossary answer common questions and define terms.
Continue to Getting Started →