AI and agents

AI that does real work inside your business, and shows its working.

LLM applications, assistants and agents that answer from your own documents and data, take actions in your systems, and hand over to a person when they should.

What we do

What this covers.

  1. 01

    Assistants and chatbots

    Support, sales and internal assistants that answer from your content and cite their sources.

  2. 02

    AI agents

    Agents that read, decide and act: triaging tickets, updating records, drafting replies, with guardrails and approval steps.

  3. 03

    Document AI

    Extraction and summaries from contracts, invoices, reports and forms, checked against rules before anything is saved.

  4. 04

    Automation

    Multi-step workflows that combine AI with your existing systems, so routine work moves without someone pushing it.

A support assistant console: conversations, an answer with policy citations, and a handover to a person.

Typical projects

The kind of work we take on.

  • A support assistant that resolves common questions and hands over the rest
  • An internal knowledge assistant over policies and manuals
  • Invoice or contract extraction into your ERP
  • An agent that triages inbound email and drafts replies for review
  • Lead qualification on your website
  • Meeting and report summaries delivered to the right people

Technology

Typical stack.

  • Amazon Bedrock
  • Azure OpenAI
  • Google Vertex AI
  • Google Gemini
  • Claude and other LLMs
  • Python
  • FastAPI
  • Vector search
  • AWS Lambda
  • Azure Functions
  • Evaluation suites
  • and whatever fits your stack

How we work

Small steps, each with a clear decision.

  1. Discover

    A short discovery to agree the problem, the users and what a good result looks like.

  2. Pilot

    A working first version on your real data or with real users, at a fixed scope and price.

  3. Build

    If the pilot earns it, the full system, released in small steps your team can try.

  4. Run or hand over

    We keep it running and improving, or hand it over with the code and documentation.

Ready-made solutions

Start from something we have already built.

Where one fits, a ready-made solution gets a project to a working first version sooner.

All ready-made solutions

Questions

What people ask first.

Which AI models do you work with?

Claude and other models on Amazon Bedrock, OpenAI models on Azure OpenAI, and Google Gemini on Vertex AI. We choose per job, on cost, speed, quality and where your data needs to stay.

How do you stop it making things up?

Answers are built from retrieved passages and show their sources. When the content does not cover a question, the assistant says so and hands over.

Is our data used to train models?

No. Neither we nor AWS Bedrock use your prompts or documents to train models.

Start with a conversation

Tell us what's slowing your operation down.

A 30-minute call with the people who would build it. You leave knowing whether a pilot makes sense, and what it would cover.