AI Agents
AI agents that take on the repetitive parts of the work.
An AI agent can research, classify, retrieve information, draft, route, schedule, update systems, and coordinate repetitive work. It carries a task across several steps instead of producing a single response. Where a decision has real consequences, a person stays in the loop.
How an Agent Works
Trigger. Understand. Decide. Act. Verify.
- 1TriggerA request, document, or event starts the workflow.
- 2UnderstandThe agent reads and interprets what’s actually being asked.
- 3DecideIt determines the right next action based on your rules and data.
- 4ActIt updates systems, drafts content, or moves the task forward.
- 5VerifyA person reviews or approves before anything irreversible happens.
Where Agents Apply
Common patterns we build.
Customer support assistants
Answering common questions from your documentation and escalating what they can’t resolve.
Lead qualification
A first-pass review of inbound leads, routed by fit, urgency, or service line.
Intake automation
Structured intake requests turned into records without manual re-entry.
Scheduling workflows
Availability checked, times proposed, and bookings confirmed automatically.
Document processing
Key fields extracted from documents and written to the systems that need them.
Internal knowledge assistants
Search and Q&A over your internal documentation.
CRM automation
Records kept current automatically as work moves through your pipeline.
Email & workflow automation
Inbound messages classified, drafted, and routed for approval.
Back-office automation
The repetitive administrative work behind day-to-day operations.
Multi-step agent workflows
Tasks carried across several stages, not a single prompt and response.
Human-in-the-loop systems
Approval steps built in wherever a decision has real consequences.
Our Approach
AI needs engineering, not just prompting.
A good prompt gets you a good demo. A dependable agent also needs workflow design, access to accurate data, guardrails on what it's allowed to do, testing against real edge cases, a clear escalation path to a person, observability into what it did and why, security around what it can touch, and ongoing maintenance as your systems change. That combination is what separates an agent that works in a demo from one that works in production.
Have a workflow that could run through an agent?
We'll map the workflow, identify what's safe to automate, and where a human checkpoint belongs.