Reveal AI

Reveal AI is Reveal Data’s agentic layer for eDiscovery and case development. The current product surface centers on search, review, analysis and case strategy: attorneys can ask questions in plain language and receive matter work product such as chronologies, key facts and deposition preparation grounded in the underlying evidence. ¹

The important buying distinction is between what is available now and what Reveal has announced for later releases. Reveal’s August 24 launch says the suite unifies existing aji document-review and ASK fact-finding capabilities with new agentic case-building, while broader orchestration across Reveal Hold, Onna, Reveal Enterprise and Logikcull plus additional MCP connectors will arrive in subsequent releases. Independent LegalTech coverage likewise describes a phased rollout rather than one fully completed end-to-end agent layer. ²³

That makes Reveal AI more substantive than a generic legal chatbot, but it should not be scored as if every announced lifecycle action is already deployed. The strongest current proposition is evidence-grounded legal work inside an established eDiscovery stack, with an attorney directing and approving the work. ²

Reveal also emphasizes model and infrastructure choice. Customers can use preferred models and can run the platform in Reveal’s commercial cloud or in controlled environments. Private Deployment documentation describes private-cloud, hybrid, sovereign or air-gapped and bare-metal configurations, which is unusually relevant for litigation data that cannot simply be sent to a generic SaaS endpoint. ⁴

Reveal AI is a sales-led enterprise product. The current public surface offers “Schedule demo” and “Talk to us” rather than a stable self-service monetary plan. AiToolMap therefore does not invent a subscription amount or reuse historical promotional pricing. ¹

That distinction matters because Reveal previously offered aji free through the end of 2025, but that promotion is stale and does not establish the current price of Reveal AI. Current cost is deployment- and contract-dependent. ²

G2’s current parent Reveal Platform page also describes annual subscription pricing as contact-sales and volume-dependent. That is consistent with an enterprise eDiscovery purchase, but it leaves buyers with less public cost predictability than products with transparent per-seat plans. ⁵

For organizations already operating a Reveal environment, the economic question is likely broader than the agentic feature alone: data volume, deployment architecture, review operations and the surrounding Reveal suite can all affect total cost. Buyers should request a quote tied to their actual data and workflow profile rather than compare a historical promotional price with a modern enterprise deployment.

Reveal’s trust posture is a meaningful strength. Its current Trust Center lists SOC 2 Type 2, ISO/IEC 27001, GDPR and CSA STAR Level 1, while Private Deployment lets customers control residency, network topology, access and security configuration in supported architectures. These are governance and deployment signals; they are not evidence that every generated legal conclusion is correct. ⁶⁴

The product design also foregrounds source grounding and lawyer control. Reveal says agentic case-building reasons across a matter while grounding outputs in cited source documents, with an attorney directing and approving the work. For litigation, that is more important than presenting an untraceable generated answer as final work product. ²

Independent numeric evidence for the new Reveal AI surface remains limited. G2 currently rates the parent Reveal Platform by Reveal Data at 4.2/5 from 52 reviews and explicitly lists agentic-AI/eDiscovery capabilities. Because those reviews cover the broader parent platform rather than a clean standalone Reveal AI surface, AiToolMap uses that rating only with a partial-surface factor. G2’s review summary praises eDiscovery workflow, AI-assisted review, usability and support while noting that performance can slow with large datasets. ⁵

The rest of the fixed evidence panel did not provide another attributable current numeric family for the exact product. An App Store result named “Reveal AI” was an unrelated FIRE TECH APPS LLC people-search app and was explicitly excluded. Missing coverage is not treated as a zero.

A further trust point is roadmap clarity. Reveal’s launch material does distinguish present agentic case-building from future orchestration and MCP capabilities. That disclosure reduces the risk of silently scoring roadmap items as shipped, although buyers still need to confirm the exact capabilities enabled in their contracted environment. ²

Reveal AI is primarily for litigation, investigations and eDiscovery teams that already think in matters, evidence sets and review workflows rather than isolated prompts. Its strongest use case is letting attorneys work directly with large evidence collections to build chronologies, identify key facts, prepare deposition material and move between discovery analysis and case strategy. ¹

It is especially attractive where deployment control matters. Law firms, corporations, government users and service providers that need private, hybrid or sovereign infrastructure have options that ordinary consumer AI assistants do not offer. ⁴

It is less suitable for a small team looking for a cheap, self-serve legal assistant with predictable monthly pricing. It is also premature to buy solely for the vision of one agent orchestrating every preservation-to-production step: Reveal itself describes parts of that broader orchestration as following in later releases. ²

Teams evaluating it should test the exact contracted surface against their own matters: citation fidelity, completeness, privilege-sensitive workflows, large-dataset performance, permission boundaries and the human review required before work product is used externally.