Software that takes the next step
An AI workflow agent is a custom application that reads business inputs, retrieves approved information, and uses software tools to complete defined tasks. It involves a person when judgment or approval is needed.
A chatbot answers questions. A workflow agent can also prepare a response, update a record, or route work for review.
Understand
Read incoming emails, forms, and documents to identify what needs to happen next.
Work
Retrieve information, prepare responses, and update approved systems within defined permissions.
Escalate
Pause for approval or pass the work to a person when information is missing or a request exceeds its authority.
Where routine work slows your team down
Start with a recurring task that takes time away from customers or other priorities. These examples show where a custom agent could help.
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Lead intake
Collect inquiry details, check service criteria, and prepare the next response.
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Customer service
Classify requests, draft answers from approved information, and route exceptions to your team.
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Document processing
Extract required fields, check for missing information, and prepare records for review.
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Internal knowledge
Help employees find answers in approved company documents, procedures, and policies.
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Scheduling
Gather requirements, check approved availability, and propose options for confirmation.
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Estimates and proposals
Apply your business rules to prepare a draft, then request approval before sending.
Start small. Test it. Build from there.
Begin with a Workflow Agent Assessment to decide whether an AI agent fits the work. Build a controlled pilot, then expand only when the results justify it.
Workflow assessment
Map the task, systems, bottlenecks, and desired outcome. Recommend an agent, conventional automation, or a process change based on fit.
Explore the assessmentControlled pilot
Build one working agent with defined tools, permissions, and approval points. Test routine requests, exceptions, and failure cases.
Explore agent pilotsIntegration and improvement
Connect approved systems, deploy with monitoring, and compare results with agreed success criteria before expanding.
Explore integrationWhy Service Time Lab
Work directly with the engineers building your agent
Our forward-deployed engineering approach means the engineers who map your workflow stay involved through design, integration, testing, and deployment. They work with the people who perform and supervise the task.
Your workflow, understood
Your team helps identify the steps, exceptions, and constraints that the agent needs to handle.
A defined engagement
We agree on the workflow, systems, environments, access, participants, responsibilities, and measurable acceptance criteria.
A clear handoff
Documentation, handoff, support terms, and additional scope are agreed for each engagement. Collaboration may be remote, onsite, or hybrid.
Keep people in control of the work
We engineer the permissions, approval steps, testing, and traceability around the agent. Conventional software rules handle steps that need exact, repeatable behavior.
Human approval
Define high-impact actions that must pause for an authorized person to approve, edit, or reject.
Scoped access
Limit the agent to the information, systems, and tools required for its agreed workflow.
Testing and traceability
Test realistic and failure cases against agreed criteria. Configure logs so actions and errors can be reviewed.
Clear escalation
Define when the agent must stop, explain the issue, and pass the work to a person.
Which workflow would you improve first?
Tell us:
- What your team does today
- Where the work slows down
- What a better result would look like
We will help assess whether an AI workflow agent is a sensible fit and what a useful starting scope could be.
A plain-language description is enough to start. Please leave out confidential or sensitive data.