Service / AI Systems

Custom AI Agents

Autonomous agents built around your workflows — reasoning, taking action and handing off safely when a human needs to step in.

What you get

A system with a job to do.

We design agents around a specific job, not a generic chat window: clear inputs, bounded actions, an audit trail and a defined moment to hand off to a person.

01

A focused technical and operational audit

02

A working prototype against real inputs

03

Human approval points and reliable fallbacks

04

Documentation your team can own

05

A measured rollout, not a big-bang launch

Where this earns its keep

Common use cases.

01

Automating multi-step approval chains that currently need a person to shepherd them through email

02

Monitoring a queue of inbound requests and resolving the straightforward ones without waiting on a human

03

Coordinating handoffs between two internal systems that don't talk to each other today

Before you ask

Questions about custom ai agents.

What's the difference between a custom AI agent and a chatbot?

A chatbot mainly answers questions in a conversation. An agent takes action — it can look things up, update a record, trigger a workflow or hand off to a person, based on reasoning about what the situation actually needs.

How long does it take to build a custom AI agent?

A focused, single-purpose agent is typically ready to pilot in 3–6 weeks. Agents that touch multiple systems or need custom integrations usually take 6–10 weeks.

More on ai systems in general.

How do you make sure the AI doesn't say something wrong to a customer?

Every customer-facing system launches with defined guardrails and an escalation path, and runs in a supervised mode until we have real production data on its accuracy — not just evaluation-set numbers.

Do you build on top of models like GPT, or train something custom?

Almost always the former. We design the system, prompts and guardrails around an existing frontier model, since that's faster and more reliable for most business use cases. Custom fine-tuning only happens when the evidence says a general model can't hit the accuracy bar.

One good conversation

Bring the messy version. We’ll find the signal.

Tell us where work gets stuck. We’ll come back with a sharper view of what to automate, what to keep human, and what to leave alone.