The gap between a good AI answer and a finished job is where most tools stop. They generate text, suggest next steps, maybe call an API if you wire it yourself. Operations teams need more: agents that take a goal, break it into steps, execute against your stack, pause for approval when policy requires it, and leave a record someone else can audit tomorrow.
That is the problem Agents are built for—specialists that finish work inside Opisense Workspace, not beside it.
Plan, execute, hand off
An specialist agent run is not a single completion. It is a sequence: understand the goal, select tools and modules, act, verify, and either complete or escalate. Handoffs carry structured context—what was tried, what succeeded, what needs a human—so the next person or agent does not restart from zero.
This mirrors how good operators already work. The difference is speed and consistency at scale, without giving up visibility.
Catalog plus custom builders
We ship a catalog of agents for common operational patterns and a builder for teams with specific procedures. Catalog agents get you running quickly; custom agents encode how your organization actually operates—checklists, thresholds, integration paths—without forcing you into generic prompts.
- Pre-built agents for repeatable workflows across modules
- Custom agents scoped to roles, data, and integrations you approve
- Shared audit format whether the agent came from catalog or builder
Policy scoping, not prompt hope
Hope is not a control. Agents inherit Workspace permissions: they cannot read a document the invoking user cannot read, and they cannot call an integration you have not enabled. Sensitive actions can require explicit approval before commit—so speed and safety are not traded off by default.
When security or compliance reviews a run, they see tool calls and outcomes, not a black-box transcript. Details live in our Trust Center for teams evaluating subprocessors and retention.
When agents beat assistants
Assistants excel at dialogue: clarifying questions, drafting, summarizing. Agents excel when the path is known but tedious—update records, reconcile exceptions, route approvals, sync status across systems. Use assistants to explore; use agents to close loops.
If your team is stuck converting AI demos into production outcomes, start with one workflow that must finish reliably—not one that must sound clever. See Agents in Workspace or book a demo to walk through an agent run end to end.