Production AI built into real products

The cost depends on the complexity of the feature, the data infrastructure it requires, and whether we're integrating with your existing product or building from scratch. A single focused AI feature is a different scope from a full data pipeline and analytics platform. We scope projects in detail after a discovery call and give you a fixed-price proposal.

We build evaluation in from the start. Every AI feature we ship has a defined accuracy benchmark, a test set of real inputs, and monitoring in production. For RAG systems and chatbots, retrieval grounding anchors outputs to your data, which significantly reduces hallucination risk. We also give users confidence signals so they know when to verify an output.

In almost every case, we can add AI to your existing product without a rebuild. We integrate via API with your current stack, adding AI features as new endpoints or services. A rebuild is only necessary when the underlying data architecture makes integration impractical, and that's a conversation we have openly in discovery.

Anyone can call the OpenAI API. The work is in the retrieval system that grounds the model in your data, the evaluation pipeline that catches bad outputs, the cost controls that keep it financially viable at scale, and the monitoring that tells you when accuracy drifts. That's what we build: the engineering around the model, not just the model call.

We use data minimisation by default: we send only what the model needs to complete the task, not raw database exports. We review each AI provider's data retention and training policies before recommending them for your use case. For sensitive data, we evaluate on-premise or private model deployments where appropriate, and we build access controls so data doesn't leak between users or sessions.

A focused AI feature: a document Q&A chatbot, an automated data extraction pipeline, or an intelligent search upgrade, is realistic in 8 to 12 weeks. The critical factor is a clear problem definition and access to the relevant data before we start. We help you identify the highest-impact feature first rather than trying to build everything at once.

We're product engineers who build AI into products, not consultants who produce reports. Every AI feature goes through the same engineering rigour as any other production code: tested, monitored, and built to stay accurate over time. And because we also build the web platforms and mobile apps, we can embed AI directly into the products we build for you.