AI development

AI development

An AI development company for the part after the strategy deck: bespoke applications, agents, and chatbots, built on your data and shipped into production.

Overview

We build the thing

Shipshape Data provides AI development services for UK organisations: bespoke AI application development, AI agent development, and custom chatbot development, all built on a governed data foundation and integrated into the systems your teams already use.

The industry loves a pilot. Pilots love staying pilots. The gap between a promising demo and a production system is real engineering: data preparation, evaluation, governance, observability, and integration. That gap is where we live. Everything we build is scoped to production from day one, which changes what gets built and how.

It also means we'll sometimes tell you not to build. If the data underneath can't support the application yet, a bespoke build on top of it is an expensive way to find out. We check first.

AI development diagram showing the gap between a promising demo and a production system, bridged by data preparation, evaluation, governance, and integration
The gap between a demo and a production system, and the engineering that crosses it.
What we build

What our AI development covers

AI agent development

Agents that take real actions in your systems under governance, with humans in the loop where risk warrants it. See workflow automation & agents.

AI chatbot development

Bespoke chat on your data, in your tone, inside your workflows. The full picture is on conversational platforms.

Bespoke AI applications

Custom applications where AI is the engine, not a bolt-on: document intelligence, search, forecasting, and the interfaces around them.

AI integration

AI features embedded in the software you already run, connected through the Model Context Protocol (MCP) so models reach governed data without losing control of it. See MCP & connections.

Proof

Proof it works

We're a truly digital business. And our customers come from more than 100 different countries across the world. We can't possibly provide the level of high-touch service to everyone but at the same time, we want to deliver a consistent experience.

Jan Sulaiman, VP Global Solutions, 1NCE
Read the 1NCE case study

60% of tickets

handled to a human standard by the AI support system we built for 1NCE.

11 languages

answered around the clock by Slimstock's documentation assistant. No new headcount.

4 to 6 weeks

from concept to production for most bespoke chat and retrieval systems.

Method

How a build runs

  1. Scope the value

    What the application must do, for whom, and what that's worth. If the numbers don't clear the cost of building, we say so.

  2. Check the data

    The build is only as good as the data underneath it. We assess readiness before writing application code, and fix the foundation first if it needs it.

  3. Build and evaluate

    Domain-tuned models, retrieval pipelines, or classical machine learning, chosen for the job. Output quality is measured continuously, never assumed.

  4. Integrate where work happens

    Into your CRM, portal, support desk, or product, rather than another destination your team has to remember to visit.

  5. Run and improve

    Observability, governance, and iteration on live usage. We stick around past go-live, so production doesn't wobble the day after handover.

Custom builds

A custom AI software development company

Most AI software development companies start from the model and work outward: pick an API, wrap an interface around it, ship. It demos beautifully and degrades quietly, because the hard problem was never the model. It's the data the model answers from, and the systems the answer has to live in.

We build custom AI the other way round. AI application development starts with the data foundation and the workflow the software must fit, then the model is chosen to suit both. That's as true for a focused AI app, a quoting tool, a document processor, a support assistant, as it is for a full platform. Bespoke means built for your business, and the build is only bespoke if it knows your business from the data up.

The stack is boring on purpose: governed warehouse underneath, evaluation and observability around the model, and integration into the software your teams already use. Boring is what production-grade looks like.

Agents

AI agents for business

Agents are the part of AI development where the stakes change: software that doesn't just answer, it acts. Raises the ticket, updates the record, chases the invoice, books the engineer. Useful exactly in proportion to how much you can trust it.

That trust is an engineering deliverable, not a hope. Our AI agent development puts every action behind governance: agents reach data through the Model Context Protocol (MCP) with access rules enforced in the platform, actions are logged and auditable, and a human stays in the loop wherever a mistake would be expensive. Start with one agent on one workflow, measure it in production, then widen its remit as it earns it.

AI agents for business work best on the boring, high-volume work nobody wants to do by hand: triage, routing, data entry, chasing, reconciliation. If you're weighing up where an agent would pay for itself first, that list is where we'd start the conversation.

FAQ

Questions we hear most

What does an AI development company do?

An AI development company designs and builds AI software for your business: applications, agents, chatbots, and the integrations that connect them to your systems. At Shipshape Data every build stands on a governed data foundation, which is what keeps the output trustworthy in production.

Why bespoke AI development rather than an off-the-shelf tool?

Off-the-shelf tools answer from generic data and stop at the edge of your workflows. Bespoke AI development builds on your data, your rules, and your systems, so the result knows your business and works where your team already works. The trade-off is honest: it takes a build, and it depends on your data being ready.

Do you build AI agents?

Yes. AI agent development is a core service: agents that take real actions in your systems under governance, with humans in the loop where the risk warrants it. See our workflow automation and agents page for how they're deployed.

How long does AI application development take?

Most bespoke chat and retrieval systems go from concept to production in 4 to 6 weeks. Larger applications take longer; we scope honestly before we start, and we'd rather tell you a number now than surprise you later.

Which models and stack do you build on?

We're model-agnostic: domain-tuned large language models, retrieval-augmented generation pipelines, and classical machine learning where it fits better. The data layer runs on Snowflake, Databricks, Google BigQuery, or Microsoft Fabric, connected through the Model Context Protocol (MCP) where agent access needs governing.

What does AI development cost?

It depends on what we're building and the state of the data underneath it, so we price per engagement as a fixed, scoped outcome. The scoping conversation is free and ends with a straight answer, including whether we think the build is worth doing at all.

Plenty of AI software development companies will quote you a build. Fewer will check whether your data can hold it up, and tell you if it can't. That check is where every engagement of ours starts. Talk to us about what you want to build.

Next steps

What happens when you get in touch

  1. You tell us what you want to build

    A few lines through the form is plenty. We reply personally, usually within one working day.

  2. A scoping conversation

    Thirty minutes on the application, the data behind it, and the systems it has to live in. No deck, no pitch.

  3. A straight answer

    What we'd build, what it depends on, and what it costs, in writing. Including "don't build this yet" if that's the honest call.

Not ready to talk yet? The free AI readiness assessment scores where you stand in about three minutes, no contact details required. Or see a build from the inside: the 1NCE case study covers AI support at scale.

Start at your core.

Tell us where your data is today and what you want AI to do. We'll come back with a straight answer on what your foundation needs and where the quickest real win is.

Talk to us