Agentic document review uses multiple AI agents that read and reason over documents rather than scoring them statistically. Agents collect, process, classify, summarize, and prepare documents for production, and each call comes with a written rationale cited to the exact source text. Human reviewers validate and sign off, so the record stays defensible.
Technology-assisted review ranks documents by a probability score. It is fast, but it cannot explain itself, and the output still needs a lawyer to interpret. Agentic review reads the document in context and produces a reasoned, cited explanation for every decision, so the reasoning is reviewable rather than statistical.
Both. Discovery AI is built for whoever owns the matter. In-house departments use it to bring first-level review inside instead of routing it to a per-GB vendor. Law-firm practice groups use it to own review capacity, which turns fixed-fee and alternative-fee work into margin rather than realization risk.
Collections are stored encrypted and tenant-isolated in the Discovery AI control plane. Inference runs BYOA on your own Azure AI Foundry: only prompts and derived representations reach the model, never your raw collection. Your data is never used to train models, and there is no cross-customer data sharing.
BYOA means Bring Your Own Azure. The AI models run inside your own Microsoft Azure tenant, under your identity, your region, and your governance, and consumption is billed by Microsoft at Microsoft list prices with no markup. For legal teams this means AI adoption does not require a new data-residency or vendor-risk conversation.
Per-GB pricing makes cost a function of collection size, which is unbudgetable at the start of a matter. Discovery AI charges a platform subscription plus per-matter complexity tiers, so the number is known before the matter starts. A representative single-matter review comes in at roughly half the cost of sending the review out.
On a representative matter, Discovery AI customers see approximately 20x faster first-level review, 99% recall, and roughly 50% lower cost than outsourcing the review, on the same collection and the same requests for production.
Those platforms are broad eDiscovery suites, typically priced per gigabyte and built around hosting and search with TAR layered on. Discovery AI is narrower and deeper: agentic first-level review with cited reasoning, priced per matter, running inference inside your own Azure tenant. Many teams keep an existing platform for hosting and use Discovery AI for the review phase, which is where the cost and time actually sit.
No. Agents propose, humans decide. Agents do the reading and the first pass; your reviewers handle judgment calls, validate the output, and sign off. The defensible record is produced by that combination, not by the AI alone.
Yes. Discovery AI lists on Azure Marketplace, so purchase can run through your existing Microsoft agreement and draw down committed Azure spend, with no new vendor onboarding.
The launch module is agentic document review for litigation and eDiscovery, covering collection through production. Jess, the companion product line, extends the same engine to contract review, M&A due diligence, and litigation portfolio management.
Frontier Preview is the current entry point: a thirty-day program with comped access, preferred commercials, and roadmap influence, in exchange for structured feedback on real matters. It suits in-house teams and law-firm practice groups already on Microsoft 365 or Azure.