Expert Artificial Intelligence and ML Development Services

Capital Compute builds custom AI platforms, generative AI applications, LLM fine-tuning pipelines, autonomous agent systems, RAG chatbots, and AI-powered workflow automation. We also provide AI consulting, model selection guidance, token-cost projections, security boundary planning, and compliance-focused architecture for businesses that need production-ready systems rather than experimental prototypes.

Yes. Capital Compute designs AI solutions that can run inside private cloud environments, helping businesses reduce exposure of sensitive data while maintaining control over infrastructure. This approach is especially valuable for regulated teams that need secure pipelines, controlled model access, encrypted data flows, and clear separation between internal systems and third-party AI services.

GDPR compliance is considered during discovery and architecture planning, not left until launch. Capital Compute scopes data handling, access controls, model boundaries, storage, audit requirements, and integration risks early. The goal is to design AI systems that protect personal data, reduce regulatory risk, and support UK businesses operating in sensitive sectors.

A RAG chatbot uses Retrieval-Augmented Generation to answer questions using your own trusted data sources, such as documentation, CRM records, knowledge bases, or vector databases. Instead of relying only on a general model, the chatbot retrieves relevant context first, helping it deliver more accurate, business-specific responses for customers or internal teams.

Yes. Capital Compute can fine-tune open-source models such as Llama or Mistral on custom datasets where fine-tuning is the right technical choice. We also assess whether fine-tuning, RAG, prompt engineering, or a hybrid approach will deliver the best balance of accuracy, cost, security, and maintainability for your use case.

Capital Compute provides fixed-price estimates in 2 business days for suitable AI projects after reviewing the core requirements, workflow goals, data sources, integration needs, and risk factors. Larger or more complex engagements may begin with a structured discovery process to confirm feasibility, define the right scope, and avoid unnecessary build costs.

All services are delivered through Capital Compute’s internal engineering team, with no subcontracting. Senior engineers are involved from the start, including early architecture decisions and sprint planning. This creates stronger accountability, more consistent technical quality, and a smoother handover because the people designing the system understand how it will be built and maintained.

After completion, clients receive full ownership of the source code, technical documentation, and a handover package suitable for internal teams or future development partners. Capital Compute’s approach is designed to prevent vendor lock-in, with documented APIs and architecture choices that support long-term maintenance beyond the initial engagement.