AI Integration
AI Integration embeds AI capabilities into your existing software and workflows via APIs and SDKs. We connect AI models — text, vision, speech — to your applications, tools, and data pipelines.
Our process.
Requirements & Integration Points
We identify the systems, tools, and workflows where AI can be integrated, and define technical requirements and success criteria.
Solution Architecture & API Design
We design the integration architecture — AI model selection, API endpoints, data flow, security, and scalability requirements.
Development & Integration
We build and integrate AI capabilities into your existing systems via APIs, SDKs, or custom middleware with proper error handling and monitoring.
Testing, Deployment & Optimisation
We test integration thoroughly, deploy to production, monitor performance, and optimise AI models based on real-world usage data.
What you get.
Questions we get asked.
What AI capabilities can be integrated?
Text (GPT, Claude, Llama), vision (image recognition, OCR), speech (transcription, text-to-speech), recommendations, search, classification, and more. We match capabilities to your use cases.
How complex is AI integration?
It ranges from simple API calls (days) to complex custom model deployment and fine-tuning (weeks). We scope the integration based on your requirements and existing infrastructure.
Do I need to host my own AI models?
Not necessarily. We use a mix of API-based AI services (OpenAI, Anthropic, Google) for most use cases, and self-hosted models when you need data privacy, customisation, or cost optimisation at scale.
Ready to start growing?
Free audit. No commitment. First results within 60 days or we fix it.