AI development

AI development

We are an AI development company that creates custom applications, agents, and chatbots. We employ your data to develop these tools and transition them to production once the strategy phase is finished.

Overview

We produce the product

Shipshape Data builds AI software for UK organisations. We develop bespoke AI applications, AI agents, and custom chatbots. These tools are constructed on governed data foundations and connect with your existing business systems.

Companies often run pilot projects that never reach the production stage. Moving from a demonstration to a functional system requires engineering tasks such as data preparation, evaluation, governance, observability, and integration. Our work concentrates on bridging that gap. We design every project for production use from the outset. This approach shapes our development process and the final results we deliver.

We will also advise you against building in certain cases. If your underlying data cannot support the application, creating a custom build is an expensive way to discover that limitation. We verify the data first.

AI development diagram showing the gap between a promising demo and a production system, bridged by data preparation, evaluation, governance, and integration
The technical differences between a demonstration and a production system, and the engineering work required to transition between them, are significant.
What we build

Our AI development services

AI agent development

Agents perform actions in your systems according to your governance rules. Humans take part in the process when the level of risk requires it. See workflow automation & agents.

AI chatbot development

Custom chat using your data, tone, and workflows. You can find more information 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 are built into your existing software. They use the Model Context Protocol (MCP) to access governed data while maintaining control over that information. See MCP & connections.

Proof

Proof that it works as intended

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 development to deployment for most custom chat and search systems.

Method

How a build runs

  1. Define the value

    We define the functions of the application, the target users, and the projected value. If the estimated value is lower than the development costs, we report that finding.

  2. Verify the data

    The quality of a build depends on the underlying data. We evaluate data readiness before we write application code. If the foundation requires changes, we fix it first.

  3. Create and assess

    We select domain-tuned models, retrieval pipelines, or classical machine learning based on the specific task. We measure output quality continuously rather than assuming it is accurate.

  4. Integrate where work happens

    Integrate with your CRM, portal, support desk, or product, instead of adding another place your team needs to check regularly.

  5. Execute and refine

    We provide observability, governance, and iteration based on live usage. Our team continues to work on the project after the launch to ensure that production remains stable following the handover.

Custom builds

A custom AI software development company

Most artificial intelligence software companies begin with a model and build around it. They select an application programming interface, create a user interface, and release the product. This approach creates effective demonstrations but fails over time. The primary challenge is not the model itself. The difficulty lies in the data the model uses and the systems where the results are integrated.

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 is 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.

We designed this stack to be predictable. It uses a governed warehouse for data storage, includes evaluation and observability tools for the model, and integrates with your existing software. This structure is intended to meet the requirements of a production environment.

Agents

AI agents for business

Agents are the part of AI development where the stakes change: software that does not 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.

Trust is a technical requirement rather than an expectation. Our AI agent development places every action within a governance framework. Agents access data through the Model Context Protocol, and the platform enforces specific access rules. All actions are logged for auditing purposes. We require human intervention for any task where an error would result in high costs. You should begin by deploying a single agent for one workflow. Measure its performance in a production environment and increase its responsibilities only after it demonstrates reliable results.

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 are weighing where an agent would pay for itself first, that list is where we would start the conversation.

FAQ

Frequently asked questions

What are the functions of an AI development company?

An AI development company designs and builds AI software for your business, including applications, agents, chatbots, and the integrations to connect them to your systems. At Shipshape Data, every project is built on a governed data foundation, which ensures reliable results when the software is in use.

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 create AI agents?

Indeed. AI agent development is one of our main services. We create agents that act inside your systems while following established governance. Human involvement stays in the loop whenever the risk level demands it. Details on how these agents are deployed are available on our workflow automation and agents page.

What is the timeline for developing an AI application?

Most custom chat and retrieval systems progress from development to production in 4 to 6 weeks. Larger applications need additional time. We deliver realistic project scopes before starting work, as we aim to give accurate timelines early rather than cause later delays.

Which models and technology stack do you use for development?

We are model-agnostic: we use domain-tuned large language models, retrieval-augmented generation pipelines, and classical machine learning when they are a better fit. The data layer operates on Snowflake, Databricks, Google BigQuery, or Microsoft Fabric, linked via the Model Context Protocol (MCP) whenever agent access must be governed.

How much does it cost to develop AI?

Our pricing varies according to the particular project and the quality of the underlying data. We offer a fixed price for each engagement based on a defined scope. The initial scoping discussion is provided at no cost. After that conversation we give a clear decision on the project, including our assessment of whether the build represents a viable investment.

Many AI software development companies will give you a build quote. Fewer will verify whether your data can support it and inform you if it cannot. That verification is the starting point for every one of our engagements. Talk to us about what you want to build.

Next steps

What to expect when you contact us

  1. Please describe the project you intend to build

    Complete the form briefly. We will send a personal reply, usually within one working day.

  2. A discussion to define the scope

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

  3. A direct reply

    We provide a written document that details what we would build, the project dependencies, and the total costs. It also includes a recommendation such as "don't build this yet" if that reflects our honest assessment.

Not ready to talk yet? The free AI readiness assessment rates your position in about three minutes, without requiring contact details. Or view a build from the interior: the 1NCE case study describes 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