AI agents for structured business execution.
Agents in Opal work with context, tools, memory, workflows, and guardrails so you can move beyond isolated prompts into repeatable operational work.
Most useful when they live inside real workflows.
Agents are most useful when they can participate in real business workflows instead of acting like standalone chat tools.
From setup to live workflow.
- Step 01
Define the role
Set the agent's scope, instructions, and the tools it is allowed to use.
- Step 02
Wire in context
Connect Knowledge, Memory, and Connectors so the agent works with real business data.
- Step 03
Place inside a flow
Embed the agent into a workflow with the right approval and review checkpoints.
- Step 04
Observe and refine
Watch runs, review outputs, and adjust scope, prompts, and guardrails over time.
What you can do with Agents.
- 01Access business context through Knowledge and Connectors
- 02Take action through Tools and workflows
- 03Retain continuity through Memory
- 04Collaborate with people through Threads, Tasks, and Spaces
- 05Operate inside governance, review, and approval controls
What teams actually see.
Hours back time returned weekly
Routine coordination handled by agents instead of teammates.
Consistent quality of execution
Standard prompts, tools, and guardrails reduce variance run to run.
Auditable every decision
Each step an agent takes is logged, reviewable, and reversible.
Works with the rest of the platform.
See the full platformExplore digital workforce use cases.
See how Opal Agents help you move from AI experimentation to governed execution.