AI Integration Services
We integrate AI capabilities into web applications: practical, production-ready features built on OpenAI and delivered within your existing systems.
AI is most valuable when embedded directly into the tools your business already uses, not sitting in a separate platform. We've integrated AI-powered search, document processing, structured content generation, and conversational interfaces into production applications, all using OpenAI APIs within .NET systems. We're not a data science company and don't build custom ML models: we design integrations that solve real problems cleanly.
What We Have Built
AI-Powered Semantic Search
Standard keyword search breaks down when users describe what they want in natural language. AI-powered semantic search understands intent, not just words.
We implemented this for a B2B electronics platform with 450+ specialist RF products: an LLM converts the query into optimised keywords, matched against an OpenAI Vector Store, so search works the way users actually think.
Document Processing & AI Scoring
Manually reading and evaluating documents is slow and inconsistent. AI can read uploaded files, extract what matters, and score against criteria you define.
We built this into a recruitment platform: the AI reads CVs, extracts candidate information, and scores against role criteria, giving recruiters structured data instantly instead of reading every CV manually.
Structured AI Content Generation
Sometimes AI is most useful as a generation engine: combining a user's input with your application's rules to produce structured output for the next step of a workflow.
We built this into a quiz platform and a career counselling tool, where the AI returns structured JSON that the application consumes directly: assessments, recommendations, personalised content.
Conversational Interface for Application APIs
A conversational interface lets users describe what they want in plain language, while AI figures out which API calls to make and returns a readable response.
We built a chat interface that reads an application's Swagger docs and uses OpenAI's tool-calling to execute the right API calls (including multi-step queries), turning any well-documented API into something non-technical users can query conversationally.
How We Approach AI Integration
Every AI integration we build has to work reliably in production, not just in a demo: designed around your data and existing system, not a technology looking for a use case. We work with OpenAI APIs inside .NET applications, the same stack as the rest of our work, handling prompt design, response validation, and error handling so AI feels native to the product. And we're honest about it: if conventional logic or search serves you better, we'll tell you.