Agents
Agent Orchestration
An agent that only drafts a reply is a chatbot. Ours plan a task, take the actions to complete it across your systems, then check their own work against the outcome you defined — and hand off to a person when confidence is low. Every step is logged and reversible, so autonomy never means losing control.
Outcomes
What you get, stated as results.
- Routine work cleared autonomously, around the clock
- A verifiable record of every action an agent takes
- Confidence-based handoff that keeps people on the hard cases
Capabilities
What this practice covers.
Multi-step planning
Agents decompose a goal into steps, sequence them, and adapt when a step fails — no brittle if-this-then-that scripts.
Tool & system access
Governed connectors into your ticketing, ERP, data, and internal APIs, so agents act where the work actually happens.
Self-verification
Each action is checked against the target outcome before it counts as done; failed checks trigger a retry or a human handoff.
Human-in-the-loop gates
You choose which actions an agent may take alone and which need a person to approve — configurable per workflow.
Full audit trail
Every decision, tool call, and output recorded in order, so you can replay exactly what the agent did and why.
Reversible actions
Nothing an agent does is one-way. Actions are checkpointed and can be rolled back if an outcome is wrong.
How it works
A sequenced path, not a big bang.
Define the outcome
We encode what "done" means for the workflow — the check the agent measures itself against.
Wire the tools
Governed access to the systems the task touches, scoped to least privilege.
Run with a human gate
The agent runs live but escalates low-confidence steps to a person while trust is built.
Widen autonomy
As the audit record proves reliability, gates move up and throughput climbs.
Where it applies
FAQ
Agent Orchestration — questions, answered.
What is agent orchestration?
Agent orchestration is the practice of coordinating autonomous AI agents that plan a task, take the actions to complete it across your systems, and verify their own work against a defined outcome — handing off to a person when confidence is low. Every step is logged and reversible, so autonomy never means losing control.
How is an orchestrated agent different from a chatbot?
A chatbot drafts a reply and stops. An orchestrated agent decomposes a goal into steps, acts across your ticketing, ERP, data, and internal APIs, then checks each action against the target outcome before it counts as done. It finishes the work rather than just responding to it.
How do you keep autonomous agents under control?
You choose which actions an agent may take alone and which require human approval, configurable per workflow. Every decision and tool call is recorded in order, and actions are checkpointed so they can be rolled back if an outcome is wrong. Autonomy widens only as the audit record proves reliability.
How much routine work can agents handle without a person?
In our incident workflows, agents resolve around 70% of routine incidents with no human in the loop, around the clock. Confidence-based handoff keeps people on the hard cases while the audit record proves reliability, and gates move up as throughput climbs.
What happens when an agent gets something wrong?
Nothing an agent does is one-way. Each action is checked against the target outcome before it counts as done; a failed check triggers a retry or a human handoff. Because actions are checkpointed and reversible, a wrong outcome can be rolled back rather than left to compound.
Put Agent Orchestration to work.
Tell us the workflow. We'll show you the shortest path to a running agent.
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