Agentic automation
Multi-step workflows that act on your behalf.
Multi-step agents that plan, call tools, and complete real work — triaging tickets, drafting reports, reconciling records, opening pull requests. Bounded, monitored, and reversible by design. Built to reduce real operational load, not to demo well.
When this service makes sense
You probably need this if…
Your team spends meaningful hours per week on a workflow that's repeatable but not currently automatable with traditional tools.
You've tried RPA and found it brittle every time a UI changes.
You have a workflow that requires reasoning over context — not just rule-following.
You want AI to do work, not to assist with work.
How we approach it
Our approach, step by step.
- 01
Pick a bounded workflow
Agents work when the workflow has clear inputs, clear outputs, and a measurable success criterion. We help you scope to one workflow that meets those tests before any code is written.
- 02
Design the action surface
What tools the agent can call, with whose authority, and what's reversible vs. gated. The most expensive mistakes in agentic systems happen because the action surface was too wide.
- 03
Build with bounded loops
Caps on planning depth, caps on tool call count, cost circuit breakers, and a forced fallback to human review if the agent can't reach a confident decision in the budget.
- 04
Instrument everything
Every plan, every tool call, every observation, every decision logged with cost and latency. Without instrumentation, you can't tell whether the agent is working — or quietly burning money in a loop.
What you get
Concrete deliverables.
- A production agent for the chosen workflow with bounded action authority
- Tool integration layer with reversibility classification per tool
- Cost and latency circuit breakers
- Eval suite covering happy path, edge cases, and adversarial inputs
- Operational dashboard showing throughput, deflection, cost per task, and intervention rate
Typical timeline
8-12 weeks for first production agent. Subsequent agents on the same platform are typically 4-6 weeks.
Common questions
What clients usually ask.
Will the agent take an action it shouldn't?
Eventually, yes — every system fails. The question is whether the failure is recoverable. We classify every tool call by reversibility and gate the irreversible ones behind human confirmation. The agent's worst day should still be a human's bad afternoon, not a regulatory incident.
Aren't agents just unreliable?
Unbounded agents are unreliable in expensive ways. Bounded agents on narrow workflows with good evals are surprisingly reliable. The reliability comes from the constraints, not from the model.
How do we know the agent is actually saving time?
Instrumentation. We measure the rate of fully-resolved tasks, the rate of human intervention, the cost per task, and the time saved per intervention. These numbers go in your weekly report from day one.
Want to talk about agentic automation?
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