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Generative AI Solutions that know your business, not just the internet.

A generic chatbot answers like the internet. A useful one answers like your best employee. We build generative AI systems grounded in your data, your tone and your rules, so the output is something you would put your name on.

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Definition

What are generative AI solutions?

Generative AI solutions are custom software applications built on large language models that produce text, answers and content specific to one business. They include customer-facing chat assistants, internal copilots, content generation systems, and retrieval-augmented (RAG) knowledge systems that answer from a company's own documents.

Deliverables

What we build.

Customer-facing assistants Support and pre-sales chat that answers real questions from your documentation and product data, hands over to a person gracefully, and never invents a policy.
Internal copilots Assistants for sales, operations, legal or HR that draft, summarise, search and answer from company knowledge, with access permissions respected.
Content systems Product descriptions, localised catalogues, reports and marketing drafts produced at scale, in your brand voice, with a person approving the output.
RAG platforms Retrieval-augmented generation done properly. Your documents indexed, cited and kept current, so every answer is grounded and checkable.
Model choice We work across OpenAI, Anthropic Claude, Google and open models, and choose per use case on accuracy, cost, speed and where your data is allowed to live.

Why grounded beats generic.

An AI that makes things up is a business risk, not a quirk. Our builds cite their sources, log every answer, stay inside their scope, and are tested against known answers before launch. When the answer is not in your data, the system says so and routes to a person.

Security and privacy first.

Your data trains no public model unless you choose that. We design for data residency where it is required, apply role-based access, and document everything for your compliance file, including EU AI Act readiness where it applies to you.

Pricing and questions

Frequently asked questions.

How do you stop the AI making things up?

By grounding every answer in your verified data, requiring citations, limiting the scope, testing against sets of known answers, and routing uncertainty to a person. Accuracy is measured before launch and monitored after it, not assumed.

Which AI models do you use?

The right one for each job. OpenAI, Anthropic Claude, Google Gemini and leading open-source models, chosen on accuracy, cost, speed and data residency requirements. You are never locked to one provider.

How long does a generative AI project take?

A grounded assistant built on existing documentation usually reaches a working pilot in 4 to 6 weeks. Production hardening, testing and roll-out follow, with the full timeline set out in the fixed quote.

Is our data safe?

Yes. Your data stays yours, trains no public model without your explicit choice, and is handled under the privacy rules that apply to you. We can host in a region of your choosing and provide a Data Processing Addendum before work starts.

Bring us one question your customers ask all the time.

We will show you the assistant that answers it.

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