AI Agents
Custom agents that take the repetitive, rules-based work off your team — built on your data, deployed into your existing tools, with humans kept in the loop where judgement matters.
Good candidates for automation
The work worth automating is high-volume, rules-based and currently done by someone too expensive to be doing it.
Visibility monitoring
An agent that re-runs your prompt set, diffs results against last week and escalates only genuine movement — not noise.
Research & briefing
Competitor tracking, market monitoring and source gathering compiled into briefs your team can act on immediately.
Lead qualification
Enrichment, scoring and routing against your criteria, so sales sees context instead of a raw form submission.
Content operations
Drafting, schema generation, internal linking and pre-publish checks against your editorial standards.
Reporting
Pulling from your real sources and writing the commentary, so the monthly report stops eating a week.
Support triage
Classifying and routing inbound, drafting replies for review, and surfacing the themes worth a product decision.
Narrow, observable, reversible.
Most failed agent projects tried to do too much at once and couldn't be debugged when they went wrong.
We scope narrowly and instrument heavily. Every agent logs its reasoning and its actions, has a defined escalation path to a human, and can be switched off without breaking the process it supports. We'd rather ship one reliable agent than five impressive demos.
Process mapping
We document the workflow as it actually runs today, including the exceptions people handle without thinking about them.
Pilot
One workflow, running alongside the human process, measured against it until the agent is demonstrably better.
Deploy & monitor
Into your stack with logging, alerting and a documented rollback. We stay on through the first month of real traffic.
Common questions
Will this replace people on our team?
In our experience it moves people off the mechanical parts of their job rather than removing the job. We'll tell you plainly if we think a process should just be deleted instead of automated — that happens more often than you'd expect.
What happens when the agent gets it wrong?
It will sometimes. That's why every agent we ship has confidence thresholds, an escalation path and complete logs. The question isn't whether errors occur, it's whether you can see them and recover quickly.
Do you use our data for training?
No. Your data stays in your environment and is not used to train shared models. We'll document the data flow explicitly before anything is built.
Have a process in mind?
Tell us what's eating your team's week and we'll tell you honestly whether an agent is the right answer.