Put AI to work inside your existing software

Grootan engineers take a single AI use case from the first conversation all the way to production, and wire it into the systems you rely on.

Services

Our AI Engineering services

RAG Knowledge Assistants

An assistant that draws on your documents, business systems and data, cites each source and only shows people what they are allowed to see.

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Use cases

Where it helps

IT and service desks

Tickets arrive already sorted, with a suggested first reply waiting for an engineer to approve.

Finance and back office

Invoices and incoming paperwork are extracted, validated and passed to the person who handles them.

Sales teams

Reps get a short account history built from CRM records and email threads, and quotes start life as drafts.

Customer support

Common questions are handled sooner, and agents have the relevant facts in front of them mid-call.

Legal and contract review

Lawyers can search across contracts and legal papers and line them up against each other.

People teams and internal knowledge

Staff questions about policy are answered from your handbooks, so nobody digs through shared drives.

Not sure which of these fits? We'll work it out with you on a first call.

Process

How we work

  1. 01

    Talk it through

    We review what you want to achieve, the data you hold and the systems involved, then tell you plainly which use case deserves to go first.

  2. 02

    Build a proof of concept

    Under realistic conditions and a fixed scope, we deliver something working that your team can try out.

    Two to six weeks, fixed scope

  3. 03

    Launch

    The solution is wired into your systems, with access limited to what each user and tool should see. Your teams start using it day to day.

  4. 04

    Operate

    If you choose, Grootan runs it, watches it and improves it, so a single team stays answerable for it.

Proof

What we've built

BARN's

Voice AI built for retail. Shoppers place an order and check out just by talking.

AI for contact-centre agents

An assistant that helps agents live, while they are handling a customer, running on Amazon Connect.

Working on something similar?

Technologies

Technologies we work with

Retrieval and search

  • Retrieval-augmented generation (RAG)
  • Vector search
  • Knowledge graphs

Agents and workflows

  • AI agents for multi-step tasks
  • Workflow orchestration
  • Model Context Protocol (MCP)

Quality and control

  • Guardrails
  • Evaluation of answer quality
  • Usage and cost tracking

Our engineers hold certifications from AWS, Azure, MongoDB, Anthropic and Elasticsearch.

Security

Security and data handling

  • A data processing agreement (DPA) is available to every client who needs one.

  • Nothing you share with us goes into training an AI model.

  • You decide where the system is hosted: in a region that suits your rules, or on infrastructure you own.

FAQ

Questions we hear

How much time does a proof of concept need?

Usually two to six weeks. Where it lands in that range depends on what you want to prove and how many systems are involved, and the scope is locked before work begins.

How is pricing worked out?

Three things set the price: what you want the AI to do, which of your systems we integrate, and whether you want us to operate it later. After the first call we put scope and price in writing, and nothing starts until you agree.

Our data is messy. Is that a problem?

Not to begin with. Checking which data exists, and how much of it the use case truly needs, is part of our first call and of the PoC itself.

Will it plug into the tools we already have?

Yes. ERP, CRM, document stores and ticketing tools are typical examples we integrate with.

What happens after launch?

That is up to you. Grootan can take over the day-to-day running after launch, track how it performs and fix what needs fixing.

Let's work out where AI will pay off first

Tell us what you're working on and we'll suggest where to start.