AI service

Custom AI Agents

We design and build custom AI agents that take a task from request to finished result, working inside the tools your team already uses.

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Definition

What is a custom AI agent?

A custom AI agent is software that uses a large language model to understand a goal, plan the steps and carry them out by calling your tools and systems. Unlike a chatbot, which only replies, an agent takes actions such as updating a record, sending an email or creating a ticket. It is built around one job in your business, with access limited to what that job needs.

Most teams lose hours to work that follows a pattern but still needs a person to read, decide and click. A custom AI agent takes that work on. It reads the request, pulls the context it needs, chooses the next step and carries it out through your systems. Growmerz handles AI agent development as an engineering job: clear scope, defined permissions, logging on every action and a human approval step wherever a mistake would be costly.

Use cases

What it can do for your team

  • Inbox and request triage

    Reads incoming emails or form submissions, classifies them, drafts a reply and routes anything unusual to the right person.

  • Lead qualification and follow-up

    Researches a new lead, scores it against your criteria, updates the CRM and sends a first response for review.

  • Customer support resolution

    Answers common questions from your knowledge base and completes simple requests such as status checks or booking changes.

  • Document processing

    Extracts fields from invoices, contracts or applications, checks them against your rules and enters the result in your system.

  • Internal operations assistant

    Lets staff ask for a report, a lookup or a routine update in plain language instead of opening several tools.

  • Research and summarising

    Gathers information from sources you approve and returns a short, structured brief with links back to the source.

Outcomes

What changes for you

  • Repetitive tasks get done without someone watching a queue
  • Faster responses to customers and to your own team
  • Fewer errors from copying data between systems
  • Your people spend their time on work that needs judgement
  • Every action is logged, so you can see what the agent did and why

How it works

From first call to a system you can rely on

  1. 01

    Map

    We walk through the task with the people who do it today and write down the inputs, decisions, tools and exceptions.

  2. 02

    Build

    We build the agent, connect it to your systems with the minimum access it needs and test it against real examples from your work.

  3. 03

    Launch

    The agent goes live with you in control. It starts with approvals on sensitive actions and works alone only where you allow it.

  4. 04

    Improve

    We review logs and feedback from real usage, fix the cases it handled badly and extend it to the next task.

Stack

Tools we commonly work with

We choose tools to fit the task and your existing systems, not the other way round.

Language models
OpenAI GPTAnthropic ClaudeGoogle GeminiOpen-source models
Agent frameworks
LangChainLangGraphCustom PythonCustom Node.js
Connections
REST APIsWebhooksEmail and chat platformsDatabases
Knowledge
Vector databasesRetrieval-augmented generation (RAG)

FAQ

Common questions

What is the difference between an AI agent and a chatbot?

A chatbot answers questions in a conversation. An AI agent also takes actions: it can look up data, update records, send messages and complete a task across several systems. Many agents have a chat interface, but the value comes from the work they finish.

Can an AI agent work with the software we already use?

In most cases, yes. If a tool has an API, a webhook or a database we can reach, an agent can read from it and write to it. During the free AI audit we check each system the task touches and tell you what is possible.

How do you stop an agent from making mistakes?

We limit what the agent can access, test it against real examples before launch, log every action and add a human approval step for anything sensitive, such as sending money or messaging a customer. Autonomy is widened only after the agent has proved reliable.

Which AI model do you use?

It depends on the task. We work with models from OpenAI, Anthropic and Google as well as open-source models, and choose based on accuracy, speed, running cost and your data requirements. The agent is built so the model can be changed later.

How much does a custom AI agent cost?

Cost depends on the scope of the task, the number of systems involved and how much human review is needed. We quote a fixed scope after the free AI audit, once we understand the work.

Other services

Find out what this could take off your plate

Book a free 30-minute AI audit. We map the manual work, tell you what can be automated and what it would involve.

Book a Free AI Audit