We add AI to the software you already run or sell. From AI search and assistants inside your platform to automated document processing in your CRM or ERP, we connect proven AI models to your data and workflows securely, starting with a small proof of concept so you see results before committing to a larger build.
- Proof of concept first
- Works with your existing systems
- UK GDPR-aware design
- You own the integration
AI that fits into your platform, not a separate tool
Most businesses don't need to build an AI model from scratch. The quickest value usually comes from connecting today's capable AI models to the systems and data you already have: your product, customer records, documents and workflows.
That's what AI integration means. We design the use case, connect the right model to your data through secure APIs, add guardrails and testing, and build the feature into your existing interface so your users and staff actually use it.
Building a new AI product instead? See our AI development agency services.
AI integration vs AI development
| AI integration | Custom AI development | |
|---|---|---|
| What it is | Connecting proven AI models to your software and data | Building or training your own models |
| Time to value | Weeks | Months |
| Cost | Lower upfront, plus usage costs | Higher upfront |
| Data needed | Your existing documents and records | Large, labelled training datasets |
| Best for | Most business use cases | Unique problems that general models can't solve |
Our AI integration services
Practical AI features built into your platform, CRM, ERP or internal tools.
LLM and generative AI integration
Large language models connected to your product for drafting, summarising, rewriting and answering questions.
AI search over your data
Retrieval-augmented generation (RAG) so AI answers from your documents, policies and product data, with sources.
AI assistants and copilots
In-app assistants that help users complete tasks, find information and take actions in your software.
Document processing
Extracting data from invoices, forms, contracts and emails, then routing it into your systems.
Predictions and recommendations
Machine learning for forecasting, scoring and recommendations using your historical data.
AI workflow automation
AI agents and automations that classify, triage and complete routine steps, with human approval where it matters.
Customer-facing chatbots
Support and sales assistants connected to your knowledge base and systems.
CRM and ERP AI features
Lead scoring, email drafting, call summaries and demand forecasting inside the tools your teams use.
Evaluation, monitoring and support
Accuracy testing, cost tracking, model updates and ongoing improvements after launch.
Adding AI to your SaaS product or platform
If you run a software product, these are common AI features we integrate for your customers.
- Natural-language searchUsers ask questions in plain English and get answers from your platform's data.
- Smart summariesLong records, tickets or reports summarised in seconds.
- Drafting assistantsEmails, descriptions and reports drafted in your product's context.
- Auto-tagging and categorisationIncoming data organised automatically.
- Insights and anomaly alertsUnusual patterns flagged for users to review.
- Usage-based AI pricingCredits or plan limits to keep AI costs aligned with revenue.
Building or scaling a SaaS product? See our SaaS development services.
How to choose an agency for AI integration into your platform
Whoever you hire, ask these questions before you sign.
- Do they start with use cases and data? A good partner asks what problem you're solving and what data you have before recommending a model.
- Will they run a proof of concept? A short, low-cost trial on your real data shows whether the idea works before a full build.
- How will they measure quality? Ask how accuracy, hallucinations and edge cases will be tested and monitored.
- How will they control running costs? AI usage is billed per request, so ask about model choice, caching and usage limits.
- How is your data protected? Look for enterprise AI services that don't train on your data, UK or EU processing where needed, and help with a DPIA.
- Can they work with your existing stack? Integration skills with your APIs, database, cloud and front end matter as much as AI knowledge.
- Who owns the result? You should own the code, prompts and configuration, and avoid being locked into one supplier.
Our AI integration process
Discovery
Use cases ranked by value, feasibility and risk.
Data review
Data sources, quality, access and privacy checked.
Proof of concept
A focused trial on your real data in 2 to 4 weeks.
Build and integrate
APIs, interface, guardrails and permissions built into your software.
Evaluate
Accuracy, safety, speed and cost tested against agreed measures.
Launch
Staged rollout with monitoring and human oversight.
Improve
Ongoing tuning, model updates and new features.
Models, platforms and systems we integrate
| Area | Examples |
|---|---|
| AI models | OpenAI, Anthropic, Google and open-weight models such as Llama |
| Cloud AI platforms | Azure AI, Amazon Bedrock, Google Vertex AI |
| Retrieval and data | Vector databases, PostgreSQL with pgvector, search engines, data warehouses |
| Business systems | Salesforce, HubSpot, Microsoft Dynamics 365, SAP, Xero, custom platforms |
| Development | Python, Node.js, .NET, React, REST and GraphQL APIs |
Integrating with Salesforce? See our Salesforce development services.
Security, UK GDPR and responsible AI
AI features often touch personal or commercially sensitive data, so privacy and safety are designed in from the start. We follow ICO guidance on AI and data protection, and if you serve EU customers we'll flag where the EU AI Act may apply.
AI can make mistakes, so we design features with clear limits, sources where relevant, and human review for important decisions.
- Business or enterprise AI services that don't train on your data
- UK or EU data processing where required
- Only the data needed is sent to the model
- Role-based access and audit logs
- Guardrails against harmful or off-topic output
- Support with Data Protection Impact Assessments
AI integration costs in the UK
Indicative ranges, excluding VAT. Your quote depends on use cases, data, integrations and security needs.
| Project | Typically includes | Typical cost | Timeline |
|---|---|---|---|
| Proof of concept | One use case tested on your data | £5,000 – £15,000 | 2 – 4 weeks |
| Single AI feature | Production feature integrated into one system | £10,000 – £30,000 | 4 – 8 weeks |
| Multi-feature integration | Several features, retrieval over your data, multiple systems | £25,000 – £75,000 | 2 – 4 months |
| Enterprise programme | Organisation-wide AI, governance, multiple integrations | £75,000 – £150,000+ | 3 – 6 months+ |
Plus running costs for AI model usage, hosting and monitoring. For a full breakdown, see our AI development cost guide.
Start with a proof of concept
Tell us where AI could help your platform or team. We'll suggest the highest-value use case and a fixed-price trial on your real data.
AI projects from our portfolio
A selection of AI-powered products our team has built.
Ways to work with us
Fixed-price proof of concept
A clearly scoped trial with agreed success measures.
Project delivery
We build and launch the integration end to end.
AI integration FAQs
What are AI integration services?
AI integration services add artificial intelligence to software you already use or sell, such as your SaaS platform, CRM, ERP or internal tools. Typical examples include AI search, assistants, document processing, summarisation, classification and predictions, built on proven AI models and connected securely to your data and workflows.
How do I choose an agency for AI integration into our platform?
Look for an agency that starts with use cases and data rather than technology, can show working software it has built, proposes a small proof of concept before a large build, explains how it will measure accuracy and control costs, and has a clear approach to UK GDPR, security and human oversight. You should also own the code and integration you pay for.
How much does AI integration cost in the UK?
As a guide, a proof of concept typically costs £5,000 to £15,000, a single production AI feature £10,000 to £30,000, a multi-feature integration with retrieval over your data £25,000 to £75,000, and enterprise-wide programmes £75,000 to £150,000 or more. You will also have running costs for AI model usage, hosting and monitoring.
How long does AI integration take?
A proof of concept usually takes 2 to 4 weeks, a single production feature 4 to 8 weeks, and larger integrations across several systems 3 to 6 months, depending on data readiness, integrations and testing.
What is the difference between AI integration and AI development?
AI integration connects proven AI models and services to your existing software and data. AI development builds or trains custom models, often for new AI products. Most businesses get value fastest from integration, and move to custom models only where off-the-shelf models can't meet their needs.
Which AI models do you work with?
We work with leading models from providers such as OpenAI, Anthropic and Google, and with open-weight models such as Llama, accessed directly or through cloud platforms like Azure, Amazon Bedrock and Google Vertex AI. We choose models based on accuracy, cost, speed and data requirements for your use case.
Is our data safe when we integrate AI?
It can be, with the right design. We use business or enterprise AI services whose terms don't use your data for training, choose UK or EU data processing where required, limit the data sent to models, and apply access controls and logging. For personal data, we help you complete a Data Protection Impact Assessment where one is needed.
Will we own the AI integration?
Yes. You own the code, prompts, configuration and documentation we create for you. Third-party AI models and cloud services remain subject to their providers' terms.
Ready to add AI to your platform?
Tell us about your software, data and goals. We'll recommend practical use cases and send an itemised GBP quote for a proof of concept.
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