OpenAI integration,
built into your product.
We integrate OpenAI's APIs, GPT-4, Assistants, Vision, Embeddings, and Whisper, into production software. Not demos. Not prototypes. Features your users actually rely on, with the latency, error handling, and cost controls that production requires.
OpenAI features that are actually useful, not just impressive in demos
We've shipped AI features into products people pay for. The gap between a working demo and a production-ready AI feature is where most integrations fail. We've navigated it.
AI Chat & Assistants
Context-aware chat interfaces with memory, tool use, and structured outputs. Assistants API for complex multi-step conversations, with proper streaming, error handling, and fallbacks.
RAG, Retrieval-Augmented Generation
AI that answers questions from your own content, documents, knowledge bases, product catalogues. We build the embedding pipeline, vector store, retrieval layer, and generation chain.
AI Content Generation
Structured content generation with output validation, product descriptions, reports, emails, and summaries, built on OpenAI's API stack.
Vision & Document Analysis
GPT-4 Vision for image understanding, invoice processing, document extraction, photo analysis. Combined with structured outputs for clean, reliable data extraction.
Production AI is an engineering problem, not just an API call
Calling the OpenAI API is easy. Building an AI feature that's fast, cheap, and reliable in production is the actual work. Here's what we focus on.
Latency and streaming
Users don't wait for AI features. We implement streaming responses, intelligent caching, and background pre-computation to make AI features feel instant, not like waiting for an API.
Cost controls from day one
Token usage compounds fast at scale. We build token budgeting, context compression, model routing (using cheaper models where quality is sufficient), and usage dashboards that prevent surprise bills.
Structured outputs and validation
LLMs hallucinate and produce unexpected formats. We use OpenAI's structured outputs, JSON mode, and Zod/Pydantic validation to ensure AI responses are always in the shape your application expects.
Fallbacks and error handling
OpenAI has rate limits and occasional outages. We build retry logic, model fallbacks (GPT-4 → GPT-3.5 for non-critical paths), and graceful degradation so your product keeps working.
What we build OpenAI integrations with
The full stack behind production OpenAI features, not just the API call.
When should you choose OpenAI specifically?
We work with OpenAI, Anthropic, and Gemini, the right provider depends on the task, not a default preference.
OpenAI makes sense when
- You want the most mature tooling and widest library/ecosystem support
- The Assistants API's built-in tool use and structured outputs fit your use case
- You need multimodal features like vision-based document analysis
Consider alternatives when
- Your task is long-context or requires more nuanced reasoning, Claude often performs better
- Multimodal strength across image/video is the priority, Gemini is worth evaluating
- You want provider redundancy, we can build a multi-provider setup with routing
Hire an OpenAI Developer
Skip the full build. Get a vetted OpenAI developer working inside your existing team, on your stand-ups and your roadmap.
Hire an OpenAI Developer →OpenAI integration in production
🇬🇧MeBag
We built MeBag — an AI-powered universal cart that lets shoppers save, track prices, and buy products from any store in a single checkout. One account, one dashboard, any retailer. The engagement is currently on hold, resuming in September 2026.
Read case study →
🇬🇧Tecknow Solutions
We built Tecknow — a modern IT service delivery platform that replaces legacy ITSM tools with a streamlined, intelligent system for ticket management, resolution tracking, and employee experience. Fast to deploy, designed for high-performing IT teams.
Read case study →Built by AI-native engineers, because this is what we do
OpenAI work is core to our practice, not a side offering. We ship AI into products that generate revenue and reduce operational cost, with the engineering discipline that keeps it reliable in production. It is how our own products, Tully AI and Mebag, were built.
OpenAI, Anthropic, or Gemini picked per task, with cheaper models for classification and routing.
A well-built retrieval pipeline beats fine-tuning for most domain use cases, at a fraction of the maintenance cost.
Evaluation datasets and automated quality checks so a model update cannot silently break something.
See the full picture of how we build AI. Our AI development →
Common questions about OpenAI integration
Straight answers on stack fit, working in your codebase, cost, and how we start.
How do you handle data privacy with OpenAI?
For sensitive data, we implement data anonymisation before sending to OpenAI, use OpenAI's Zero Data Retention option where available, or recommend using Azure OpenAI Service (which has stronger enterprise data agreements). We'll map out the right approach for your compliance requirements.
Can you integrate OpenAI with our existing application?
Yes, this is the most common engagement. We integrate OpenAI features into existing Node.js, Python, .NET, or PHP backends. The integration pattern depends on your existing architecture, which we assess before scoping.
How do you control OpenAI API costs?
Through model routing (using cheaper models for lower-stakes tasks), semantic caching (returning cached responses for similar queries), context compression (trimming conversation history intelligently), and token budgets with hard limits per user/tenant.
What's the difference between using OpenAI directly vs Anthropic or Gemini?
We work with all three. OpenAI has the most mature tooling and the widest library support. Anthropic (Claude) performs better on long-context and nuanced tasks. Gemini has multimodal strengths. We'll recommend the right model for your specific use case, or build a multi-provider setup with routing.
Hire OpenAI Integration Developers
Need OpenAI engineers embedded in your team rather than a full project handoff? Our OpenAI Integration Developers join your existing workflow (your tools, your stand-ups, your roadmap) while we handle employment, payroll, and HR. Add one developer or a full team, scale up before a release and back down after, and keep everything they build.
Want to add AI features to your product?
We've shipped it. Not just prototyped it.
Tell us what you're trying to build with AI. We'll tell you honestly what's feasible, what'll cost you at scale, and whether OpenAI is the right tool for it.