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AI

AI integration services

Add AI features to your existing web application. We build tools that draft summaries and replies, sort enquiries and find information. Your team checks the results before relying on them.

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What AI integration can do. Useful AI features inside the software you already have

Summaries Draft summaries of emails, case notes and reports for your team to check.
Drafting First drafts of replies, letters and reports, ready for a person to check.
Classification Sort enquiries, applications or tickets and send them to the right person.
Data extraction Pull names, dates and figures out of documents and forms into your system.
Smarter search Find records by meaning, not just exact keywords.
Human oversight Review steps and permissions built into every workflow.

How an AI integration project runs. Small, measured steps with your data protected throughout

  1. 01Discover1–2 weeksWe find the tasks where AI saves real time and agree how we will measure success.
  2. 02Prototype1–2 weeksA working version on a sample of your data, tested by the people who will use it.
  3. 03BuildReleases every two weeksThe feature is built into your system with logging, permissions and review steps.
  4. 04MeasureOngoingWe track accuracy, time saved and cost, and improve the feature over time.

What you get. AI you can inspect, explain and control

Start with AI discovery
  • Source code and prompts in your own repository
  • A written record of what the AI can and cannot do
  • Tests that check answers against real examples
  • Activity logs with access and retention agreed for your project
  • Usage and cost reporting
  • A handover session for your team

Proven technologies. Laravel is home ground; everything else is chosen to fit your team and hosting

  • Laravel
  • Livewire
  • Vue
  • Tailwind CSS
  • ASP.NET Core
  • PostgreSQL
  • MySQL

Questions about AI integration

How do you use AI safely with our data?

We agree what data AI can access, keep it in UK or EU hosting where required, and never use your data to train public models.

Which AI models do you use?

We use leading large language models from established providers, chosen for each job on accuracy, cost and where data is processed. We can switch models later without rebuilding your system.

Can AI make mistakes?

Yes. AI can produce confident but wrong answers. That is why we keep a person in the loop for important decisions, show sources where possible and test answers against real examples before launch.

How much does it cost to run AI features?

Running costs depend on how often a feature is used and which model it uses. We estimate them during discovery and set up usage reporting, so there are no surprises.

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Where could AI save your team time?

Send a short brief and you’ll hear back from Khaled within two working days, with a clear next step.

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