Custom AI agents for business

Custom AI agent development, built around the tools you already use

A custom AI agent is a digital worker that does one job end to end: it reads, it uses your tools, and it prepares real output. A person approves the important steps. tigoLab builds yours in two to three weeks.

Built by a team that built the #1 agent on SWE-bench Verified. The same people who push the frontier of coding agents build your assistant.

What a custom AI agent actually is

An AI agent is software that can take a task and carry it through, not just answer a question. Give it a job like "chase the overdue invoices" and it finds the overdue ones, drafts a reminder for each, and lines them up for a person to approve. It uses the same tools your team uses. It is custom because it is built for your process, your inbox, and your files, not for a generic average of every business.

Agent versus chatbot

A chatbot waits for you to type and then replies with words. That is the whole loop. It cannot open your inbox, read an attachment, or update a sheet. An agent does the work. It reads the incoming email, pulls the right file, prepares the output, and hands it over for approval. The chatbot tells you how to do the task. The agent does the task.

This matters because the time your team loses is in the doing, not in the asking. A smarter chat window does not give you hours back. An agent that handles one repetitive job does.

How tigoLab builds your agent

1. We pick one job. It has to be repetitive, rule-based enough to trust, and big enough to matter.
2. We connect the agent to your existing tools: email, calendar, spreadsheets, and files. Nothing new to learn.
3. We build in the approval step. The agent prepares, a person checks, then it acts.
4. We ship the first version in two to three weeks, then tune it with you.

The approval step keeps you in control

Every important action waits for a person. The agent drafts the reply; your team member reads it and clicks approve. The agent flags the overdue invoice; a person confirms before the reminder goes out. You decide where the approval sits and how tight it is. Over time, as trust builds, you can loosen it for the low-risk steps and keep it tight on anything that touches a customer or a number.

Built around your tools, not a new platform

Your team does not log into a new dashboard and learn a new way of working. The agent works inside the tools they already open every day. The output shows up where they expect it. That is why adoption is not a fight: nothing changes for the team except that one job gets quieter.

Common questions

Explore the full picture: the done-for-you model, example jobs like invoice chasing and booking emails, or your estimated savings.