We're model-agnostic and choose based on your requirements. GPT-4 and Claude are excellent for most business use cases. For cost-sensitive or latency-critical applications, we evaluate open-source models like Llama 3 or Mistral deployed on your own infrastructure.
Data security is central to every design decision. We can deploy on your own cloud infrastructure using API configurations that opt out of training. For highly sensitive data, we default to on-premise or private cloud deployments. All systems are GDPR-compliant with full audit trails.
We use RAG (retrieval-augmented generation) to ground the model in your data, implement confidence scoring, define explicit refusal behaviour for out-of-scope queries, and always include human-in-the-loop checkpoints for high-stakes decisions.
Yes. Integration with your existing stack is a core part of every engagement — CRMs, ERPs, databases, communication tools, and custom internal APIs. We design agents as tool-calling systems with well-defined interfaces that fit into your existing workflows.
Ongoing inference costs vary by model, volume, and deployment type. We model this for you during scoping — typically anywhere from a few hundred to a few thousand pounds per month for most business-scale deployments.