AI Agent Development
Agents that take actions across your tools, not just chat.
We build AI agents that do work: pull data, make decisions, and take actions across your systems with the right guardrails, approvals, and logging.
What you get
- Multi-step tasks across your tools
- Approvals and guardrails
- Full logging and observability
- Human in the loop where it matters
When an agent beats a plain automation
If the steps are always the same, write an automation. It is cheaper, faster, and cannot surprise you. An agent earns its place when the path varies with the input: triaging inbound requests that arrive in different shapes, research across sources, or handling exceptions a fixed workflow cannot enumerate.
We start most projects by trying to write it as a plain automation. If that works, we build that instead and tell you the agent was not needed.
Tools, permissions, and blast radius
An agent is only as capable and as dangerous as the tools you give it. Each tool needs a narrow definition, its own permissions, and limits: which records it can see, how many actions per run, and what it may never do without a human.
We separate reversible actions from irreversible ones. Drafting, labelling, and reading run freely. Sending, paying, deleting, and anything a customer sees require confirmation until you have watched it behave for a while.
Loops, costs, and stopping
Agents can loop, retry, and quietly spend money. Every run needs a step ceiling, a spend ceiling, a timeout, and a clear failure state that hands to a person rather than trying forever.
We log every step, tool call, and decision so a run can be replayed and understood. Without that, debugging an agent is guesswork, and you cannot answer a customer asking why something happened.
Rolling it out without an incident
The pattern that works is staged. First it suggests and a human approves everything. Then it acts on the safe subset automatically. Then you widen, based on what the logs show rather than on optimism.
This also gives you the evidence to decide whether it is worth continuing, which is a question worth being able to answer honestly.
AI Agent Development: common questions
Design assumes it will. Irreversible actions need confirmation, every run is logged and replayable, and there are hard ceilings on steps and spend. The question is not whether it errs but whether the error is contained and visible.
Other things we do.
Have a workflow worth automating?
Book a 30 minute call. We will map where AI voice, automation, or a new app can save your team real hours, and what it takes to ship it.