Put AI to workin your business.

Not necessarily. Modern LLMs like GPT-4 and Claude come pre-trained on vast knowledge. For most use cases, such as chatbots, document processing, summarisation, and content generation, we can build something valuable with your existing documents, product data, or business logic. Custom model training is only needed for very specific tasks.

OpenAI and Anthropic models (GPT-4, Claude) are the right choice for most production systems. They're reliable, well-documented, and improve over time. Open-source models (Llama, Mistral) make sense when you need to keep data fully on-premise, want to avoid API costs at scale, or need fine-tuning control. We'll recommend the right choice for your specific constraints.

Anything rules-based and repetitive is a candidate: data entry and migration, document review and summarisation, email classification and routing, lead qualification, invoice processing, report generation, customer support tier-1 responses, and internal knowledge retrieval. We start with an automation audit to identify your highest-ROI opportunities before writing any code.

We build with data security as a first-order concern. This includes prompt injection protection, input/output filtering, no training on your data without explicit consent, and choosing API providers with enterprise data agreements. For sensitive industries we can build on-premise or use models that guarantee zero data retention.

A focused AI integration such as a chatbot, document processor, or automation pipeline typically takes 3 to 6 weeks. A more complex AI product with custom agents, RAG systems, and production infrastructure runs 8 to 14 weeks. We scope tightly and deliver incrementally so you see value quickly.