AI integration

AI Integration

AI integration for your software and websites: we connect large language models like OpenAI, Anthropic, and Google AI to your systems with optimised prompts, robust error handling, and production-ready code. Practical, reliable AI features, not hype.

OpenAI · Anthropic · Google AI RAG & vector search Streaming & agents
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Provider-agnosticOpenAI, Anthropic, Google
Fits your stackWeb, desktop, or server
Cost-awareCaching and usage caps
You own itFull source, with docs

Our AI integration stack

We add AI integration end to end, from a single chatbot to multi-provider pipelines. A selection of what we deliver:

LLM & chat integration

We connect OpenAI, Anthropic, Google AI, or open models to your app with clean, maintainable code.

Prompt engineering

We design, test, and version prompts so outputs stay accurate, on-brand, and reliable.

RAG & knowledge search

We ground answers in your own data with retrieval-augmented generation and vector search.

Chatbots & assistants

Customer-facing or internal assistants with streaming replies and conversation memory.

Monitoring & cost control

Usage dashboards, token and cost tracking, rate limiting, and caching to keep spend predictable.

Security & guardrails

Input validation, output filtering, and data-privacy controls to keep your AI features safe.

Our Process

1

Discovery & use cases

We map where AI adds real value, define success metrics, and choose the right providers and approach for your use case.

2

Solution design & provider selection

We design the integration architecture, select models, and plan for cost, latency, and data privacy from the start.

3

Integration & prompt engineering

We build the integration, engineer and test prompts, and wire in retrieval, streaming, and structured outputs.

4

Testing & evaluation

We evaluate quality with regression and benchmark tests, then harden error handling, rate limiting, and caching.

5

Deployment & monitoring

We deploy to production, set up usage and cost monitoring, hand over documentation, and provide 30 days of bug fixes.

Request a Quote

Tell us about your AI integration project. No obligation, just honest technical guidance from our UK-based engineering team. We respond within one business day.

Tell us briefly what you are planning. We respond within one business day.
Thank you! Your quote request has been sent. We will get back to you with a tailored quote shortly.
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F.A.Q About AI Integration

What is AI integration?
AI integration means adding capabilities like chat, summarisation, classification, or retrieval to your software using large language models and other AI services, wired into your app with reliable, production-ready code.
Which AI providers do you work with?
We work with all the major providers, including OpenAI, Anthropic (Claude), and Google AI, as well as open models. We are provider-agnostic and recommend the best fit for your use case, budget, and data requirements.
Can you add AI to our existing application?
Yes. Most of our work is adding AI integration to existing web, desktop, and server applications. We assess your current stack and integrate cleanly without rebuilding what already works.
What can AI realistically do for our business?
Common wins include customer-support assistants, document and email summarisation, search over your own knowledge base, content drafting, data extraction, and classification. We focus on use cases with clear value rather than novelty.
What is RAG and do we need it?
Retrieval-augmented generation (RAG) grounds the AI in your own documents and data so answers are accurate and specific to your business. If you need the AI to answer from your content rather than general knowledge, RAG is usually the right approach.
How do you control AI costs?
We design for cost from the start: choosing right-sized models, caching responses, setting usage and rate limits, and monitoring token spend so you get predictable, controllable bills.
How do you keep our data private and secure?
We use providers and configurations that do not train on your data, add input validation and output filtering, and apply sensible access controls. Where needed we can discuss self-hosted or open models for sensitive data.
How accurate and reliable are the results?
We engineer and test prompts, add guardrails, and where appropriate use retrieval to ground responses. We also set up evaluation so quality is measured, not assumed, before anything goes live.
How long does an AI integration project take?
It depends on scope. A focused integration can be quick, while multi-provider or RAG systems take longer. After an initial consultation we give you a realistic timeline with clear milestones before any work begins.
Will we own the code?
Yes. On final payment you own all the custom code and intellectual property we build for you, delivered with full source and documentation.
Do you provide ongoing support?
Every engagement includes 30 days of bug fixes after delivery. Beyond that, we offer ongoing support, monitoring, and enhancements on a package or per-project basis, which matters as AI models evolve.
How does the quote process work?
Tell us about your project and pick the option that fits. We review it and send you a tailored, fixed-scope quote, usually within one business day. It is free and there is no obligation.

Related reading

Guides to help you plan, budget, and adopt AI integration for your business.

AI Integration for UK SMEs - A Practical Guide for 2026

Read article

AI Software Development - A UK Business Guide for 2026

Read article

Prefer to Talk First?

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We respond to all messages within 24 hours.

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