
Build, share and govern custom assistants configured with natural-language instructions, document context and an explicit or auto-selected model — fitting operating models whose use cases demand task-specific assistants, and whose IP and customer-data posture cannot accept consumer assistant tooling that lacks tenant isolation and policy enforcement.
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More from Liminal AI
Single-pane access to leading generative AI models behind a governed control plane that inspects every prompt and response — fitting operating models whose workforce is already using AI and whose security posture cannot continue treating each consumer AI tool as an unmanaged egress channel.
A policy engine applies redact, mask, warn and pass-through actions on PII, PHI, financial identifiers and internal terminology before prompts reach a model — with rehydration of masked terms in the response — fitting operating models whose regulated data cannot be sent verbatim into third-party LLM endpoints, and whose privacy posture demands a deterministic control plane rather than user-side discipline.
Sanctioned, observable AI usage across web, desktop and embedded applications replaces ad-hoc consumer AI tools — fitting operating models whose security posture has discovered employees pasting sensitive content into unmanaged AI surfaces, and whose governance posture cannot rely on blocking AI as a sustainable strategy.
A desktop helper extends the same governed AI surface into the productivity, CRM and collaboration applications already in use — fitting operating models whose adoption strategy demands AI in the flow of work, and whose architecture posture cannot tolerate a separate, unmonitored AI app on every desktop.