SynthesisLogic

What does an AI agent development project look like, step by step?

It starts with one job, not the whole company. We map that job with the people who do it, test a first version on your real past cases, build it into your systems with approvals on every action, go live beside your team, and then look after it as your processes change. Each step ends with something you can check before the next one starts.

Updated 8 November 2026.

This page answers

  • How does working with an AI agent development company work?
  • Can you help me build the system from scratch?
  • How do I start an AI agent project?
  • What happens after an AI agent goes live?

Four steps

  1. Scope one job

    A call and a short workshop with the people who do the work: inputs, systems, rules, exceptions, volumes, and what a correct result looks like.

  2. Pilot on your data

    A first version runs on a sample of your real past cases, without touching live systems. You see the results case by case.

  3. Build and connect

    The agent is written in code and connected to your systems through accounts with narrow rights, with approval steps and a log.

  4. Go live beside your team

    It prepares and a person approves. Routine cases go automatic only when you decide.

After launch

Systems change: a supplier changes an invoice layout, an API gets a new version, a new product line arrives. We watch failures and the share of cases sent to a person, fix what breaks, and add the next job when you want. You get a regular summary of what the agent did.

What we need from you

  • One person who knows the job and can answer questions for an hour or two a week.
  • A sample of real past cases: documents, emails or messages, with the result your team produced.
  • Access to test accounts or a copy of the systems, then narrow production access.
  • Your rules for approvals: which actions, which amounts, which people.

What you get

  • An agent written in code that works in your existing systems.
  • Approval steps and limits you set, enforced in the code.
  • A log of every input, decision and action.
  • Test results on your own cases before go-live.
  • Hosting in your cloud account or on your own servers, if you need it.
  • The source code, written in Python, with documentation. It is yours: you can run it, change it or hand it to another team.

Who owns it, where it runs

Code
You own the source code we write for your project, and you receive it with documentation.
Data
Your data stays yours. The agent reads it from your systems and keeps only the logs you decide to keep.
Hosting
Your cloud account or your own servers. Nothing depends on a no-code platform or on our accounts.
Upkeep
Optional. If you want us to look after the agent and add the next jobs, upkeep is quoted once the agent is live.

Questions

Do we have to automate everything at once?

No. One job first; the next ones reuse the connections and rules already built.

What if the pilot does not work well enough?

Then you know before paying for the full build, and you have the results on your own cases to decide with.

Do you work remotely?

Yes, with companies in several countries. Workshops and reviews happen in online calls.

Want an agent built for this?

We build AI agents in code, connected directly to your systems, with no per-task fees. Write a few lines about the work you want to automate and the systems you use; we reply to set up an online intro call.

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