Service AI agents & chatbots

Software that does the work, not just the talking.

Most "AI features" summarize things. An agent finishes things: it reads the inbox, updates the system, chases the invoice, answers the customer — inside the tools you already run, measured against a number you agree on before we start.

Book a free discovery call FROM $2,000 · TYPICALLY LIVE IN 2–4 WEEKS

01 What we build

Six shapes this usually takes.

Inbox & ticket triage

An agent reads incoming mail, classifies it, extracts the details that matter, and routes or replies — so the first ten minutes of every request happen without a human.

Data entry & reconciliation

Orders from email into your system, invoices matched against statements, spreadsheets kept in sync. The work nobody wants, done continuously instead of on Fridays.

Support chatbot on your docs

A customer-facing assistant grounded in your real documentation, with citations, escalation to a human, and honest "I don't know" behavior instead of invention.

Internal copilot

A private assistant that answers from your handbooks, contracts, and past projects — the institutional memory your team keeps re-asking each other for.

Document intelligence

PDFs, scans, and forms turned into structured records: quotes parsed, specs extracted, compliance fields filled and flagged for review.

Workflow orchestration

Multi-step processes across several tools — CRM, helpdesk, sheets, storage — run by an agent that knows the sequence and reports what it did.

02 How it works

Anatomy of an agent that survives production.

A demo agent needs a model and a prompt. A production agent needs the four things around it — which is the entire difference between a toy and a tool.

TRIGGER new email, form, schedule, webhook THE AGENT LOOP plan / decide frontier model act via tools your APIs, CRM, DB observe result → adjust grounded in your docs (retrieval), not guesses GUARDRAILS allowed actions, limits, confidence floor HUMAN escalation when unsure or high-stakes OUTCOME reply sent, record updated, task done AUDIT LOG + METRIC every decision recorded and every run scored against the number agreed before the build — tickets deflected, hours saved, errors caught

Fig. — A production agent: trigger, loop, guardrails, human escalation, and an audit trail scored against one agreed metric.

03 The build

From "we waste hours on this" to shipped.

Pick the metric

Before a line of code: what number are we moving? Tickets deflected, hours returned, errors avoided. If we can't name it, we tell you not to build it.

Map the real workflow

We watch how the work actually happens today — including the exceptions people handle without noticing. Those exceptions are where naive agents break.

Build with guardrails first

Allowed actions, confidence floors, and escalation rules go in before capability. An agent that can do less, safely, beats one that can do everything, occasionally.

Shadow run

The agent runs alongside your team without acting, so you can compare its decisions to theirs on real traffic. It goes live only when the comparison is boring.

Launch and score

Live, with the audit log and dashboard. We report against the metric from step one — and you own the code, the prompts, and the keys.

04 Fit

This is for you if…

  • Someone on your team spends hours re-typing data between two systems.
  • Your support inbox answers the same twenty questions forever.
  • You're about to hire a coordinator whose job is mostly routing and chasing.
  • Quotes, specs, or invoices arrive as PDFs and leave as manual spreadsheet rows.
  • You tried an off-the-shelf AI tool and it didn't know anything about your business.
  • You need the AI to be auditable — every action explainable to a client or regulator.
Starting price$2,000
Typical timeline2–4 weeks
You receiveCode, prompts, keys

05 Questions

What clients ask first.

What if the AI gets something wrong?

That's what the confidence floor and escalation path are for: below a threshold, the agent hands off to a human instead of guessing. And because every action is logged, a wrong decision is findable and fixable rather than mysterious.

Does our data get used to train models?

No. We build on business-tier APIs where your data isn't used for training, and we scope what the agent can see to what it actually needs. If you have residency or compliance requirements, tell us on the call and we'll design around them.

Which model do you use?

Usually Claude, sometimes others — chosen per task and swappable, because the model is the cheapest part to change. The valuable part is the workflow around it, and that's yours.

Can it work with our existing tools?

Yes — that's the normal case. Agents connect through the APIs of what you already run: helpdesk, CRM, sheets, storage, databases. We meet your stack rather than asking you to move.

What happens if we want to change it later?

You own the repository, so any developer can. Many clients take it in-house; others keep us on a Partner plan for ongoing tuning as the workflow evolves.

06 Related

Often built together with:

Tell us what's eating the hours.

Describe the workflow in a couple of sentences. You'll get an honest read on whether an agent is the right answer — and a fixed quote within 48 hours if it is.

Book a free discovery call