The problems this exists to solve.
How it works for your team, day to day.
One policy across every Gemini surface
AccuroAI applies a single policy engine to Workspace Gemini, the consumer site, Vertex AI deployments, and API traffic. The same 40+ classifiers, the same sub-38ms inline inspection, the same audit trail — regardless of which door the interaction came through.
Inspection that isn't text-blind
Uploads are inspected as content, not just filenames — a screenshot of a customer table or a photographed contract is treated with the same seriousness as the pasted equivalent, before it transmits.
Project- and team-level control
Marketing experimenting in Gemini and engineering shipping on Vertex don't need the same rules. Policies scope to Google groups, projects, and use cases, with per-team analytics showing where the value and the risk actually sit.
The questions we hear most.
Doesn't Google's admin console already control Gemini?
Workspace admin controls toggle features on or off. They don't inspect content, redact sensitive fields, or produce interaction-level audit evidence — that's the layer AccuroAI adds.
Is Vertex AI really the same problem?
It's a bigger one — Vertex is production traffic, often carrying customer data by design. Per-model policies let you enforce what each deployment may receive and return.
What about personal Gmail accounts using Gemini?
Browser-boundary coverage on managed devices governs gemini.google.com regardless of which account is signed in.
Does multimodal inspection add noticeable delay?
Uploads are scanned before transmission within the same latency envelope as text — users don't perceive it.