AI agents & automation

Hand the repetitive work to an agent.

We build AI agents that read incoming requests, apply your rules and recommend or complete the next step. Your team stays in control of the decisions that matter and stops spending its day on the ones that don't.

Sound familiar?

If a task is repetitive, follows rules and lives in text, it is a good candidate for an agent.

  • Requests pile up in an inboxSomeone reads every email or form, works out what it is and forwards it by hand.
  • Experts do lookups all daySkilled people spend hours searching manuals, codes and spreadsheets to answer routine questions.
  • Data gets retypedInformation from PDFs, forms and documents is copied into another system field by field.
  • Answers depend on who you askThe rules exist, but they are applied differently from person to person and shift to shift.

What we build

Each agent is designed around one workflow and the people who own it.

01

Intake & triage agents

Read incoming emails, tickets or forms, classify them, pull out the key details and route them to the right person or queue.

02

Recommendation agents

Take a description of a case and recommend a code, category or next action, with the reasoning shown so a reviewer can approve it in seconds.

03

Document extraction

Turn invoices, reports, forms and scanned documents into structured data that flows straight into your systems.

04

Answers from your own documents

An assistant that answers staff questions from your manuals, policies and procedures, and cites the source for every answer.

05

Multi-step workflow automation

Agents that carry a task across several systems: look something up, fill in a record, draft a reply and flag exceptions for a person.

06

Not sure yet?

Describe the workflow that eats your team's time. We'll tell you plainly whether an agent is the right fit, or whether simpler automation would do the job.

How we build it

An agent is only useful if people trust it. We build that trust in from the start, then measure it.

  • OpenAI & Claude APIs
  • Python
  • Next.js
  • AWS
  • A human in the loop for every decision that carries real risk
  • Recommendations come with reasoning and sources, not just an answer
  • Accuracy tested against your real past cases before launch, and on every change after
  • Clear limits: the agent says when it is unsure and hands off to a person
  • Logging and monitoring so you can audit what it did and why
  • Model providers and settings chosen so your data is not used for training

How an engagement works

Start small, prove the value, then grow. Every phase has a written scope and a fixed quote.

Step 1

Workflow review

A free consultation to map the workflow, the rules behind it and where an agent would save the most time.

Step 2

Pilot

A working agent for one workflow, tested on your real cases and used by a small group, so you see results before committing further.

Step 3

Production & support

Hardening, integration with your systems, monitoring and handoff, with an optional support plan to keep it accurate as things change.

What you receive

You own everything we build. No lock-in, no black box.

  • Source code in your repository
  • The test set and accuracy report
  • Infrastructure as code for your cloud account
  • Documentation and a runbook for your team
  • A walkthrough session for the people who use and maintain it

Questions

Will an AI agent make decisions without anyone checking?

Only where you decide it should. Most agents we build recommend the next step and show their reasoning, and a person approves anything that matters. Fully automatic handling is reserved for low-risk, well-defined cases.

What happens to our data?

We pick model providers and settings that do not train on your data, keep data in your own cloud account where possible, and log only what you need for review and auditing.

How do we know the agent is accurate?

Before launch we build a test set from your real past cases and measure the agent against it. The same tests run on every change, so accuracy is tracked rather than assumed.

Can it work with the systems we already use?

Yes. Agents connect to existing tools through their APIs, databases, shared inboxes or file drops. If a system has no API, we find the safest practical integration point.

What would you automate first?

Tell me about the workflow. I'll reply within one to two business days with an honest take on whether an agent is the right tool.

Start a project