Intake and routing
Read what comes in, sort it, and send it to the right place with the right context.
AI Agents
AI that finishes the work.
We build and run AI agents that carry a task from trigger to finished result, inside the systems your team already uses.
The problem
Most AI stops at the answer.
A chatbot can explain what should happen next. Someone on the team still has to go do it. The work that repeats every week keeps landing on the same desks.
The shift
From asking a tool to handing off a task.
How it usually runs
- A tool that answers, then waits
- Recurring work that always needs a person to start it
- AI that lives in a separate tab from the real systems
- No record of what was done or why
How it could run
- An agent that completes the task end to end
- Work that runs on a trigger or a schedule
- AI working inside the tools the team already uses
- Every action logged, with humans keeping final say
The difference
An agent does the work. A chatbot talks about it.
Most tools sold as AI are chatbots. They answer a question and stop. An agent is given a job, a set of tools, and limits — then it carries the task through to a finished result.
Chatbot
AI agent
What starts it
ChatbotA person types a question
AgentA trigger, a schedule, or an event in a system
What it does
ChatbotAnswers, then waits
AgentWorks through the steps needed to finish a task
What it touches
ChatbotThe conversation
AgentReal systems: records, files, messages, tools
How it ends
ChatbotThe reply is the result
AgentThe work is done and logged, or sent for review
Who follows up
ChatbotA person still has to act
AgentThe agent acts, and flags what needs a human
What agents handle well
The work that keeps coming back.
Agents fit tasks with a clear trigger, clear steps, and a clear definition of done.
Research and reporting
Gather information from multiple sources, check it, and deliver it in a usable format.
Follow-up
Track what is waiting, send the next message, and escalate what goes quiet.
Data upkeep
Keep records complete and consistent across the systems that need them.
How we build and run them
Scoped, tested, supervised.
01
We pick one task with a clear finish line.
02
We give the agent the tools, data, and limits it needs.
03
We test it against real work before it runs on its own.
04
We monitor it, review the exceptions, and improve it over time.
Have something in mind?