Governed multi-step flows
Route intake, classification, and follow-up tasks through governed multi-step workflows.
By Use Case · Agentic Operations
Move from AI ideas to AI-powered execution.
Opal helps you put AI inside real operational workflows so work gets routed, reviewed, completed, and measured instead of stopping at recommendations.
Why Agentic Operations matters
A recommendation isn't business value.
A recommendation has no business value until it turns into an owned next step. Many AI tools stop at summaries, drafts, or suggestions. The real challenge is getting work to move.
AI inside the workflow
What Opal helps you do
From insight to accountable action.
- 01Run AI inside structured workflows, not outside them
- 02Combine automation with approvals and human-in-the-loop review
- 03Keep execution visible from trigger to outcome
- 04Connect AI output to tools, tasks, systems, and next steps
Example operational workflows
Patterns teams run on Opal.
AI-drafted approvals
Use AI to draft, summarize, or decide inside approval-heavy business processes.
System-triggered actions
Trigger downstream actions across systems when defined conditions are met.
Human-in-the-loop handoffs
Route the right decisions to the right humans without breaking the flow of work.
Reusable operating templates
Package proven end-to-end operations into reusable templates any team can run.
Ops observability
Monitor throughput, backlog, and SLA aging across every agentic workflow you run.
Typical outcomes
What teams actually see.
01
Higher throughput on repeatable business processes
02
Less manual orchestration and follow-up effort
03
Better consistency and accountability
04
More confidence in moving AI from experimentation into operations
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