AI implementation guides

Compare approaches, prepare your requirements and see where custom AI is worth building. Start with the decision in front of you.

Choosing an AI Implementation Partner

Choose an AI implementation partner with clear scope, credible evidence and ownership terms. Compare delivery risks, costs and handover.

Decide where AI agents belong in your workflow. Assess support tasks, approval rules, integration needs and operating costs before buying.

Choose between document extraction and RAG, assess legacy integrations and define source access, validation and operational ownership.

Compare custom AI applications with standard software. Define a useful proof of concept, production requirements, ownership and lifecycle costs.

Evaluate AI for tender responses, proposals and clarification notes. Compare options using source evidence, review controls and a realistic pilot.

Plan AI integration with CRM, ERP and legacy systems. Compare access, workflow design and acceptance tests before committing to a build.

Buy computer vision inspection with clear defect definitions, representative images and line trials. Set acceptance criteria before rollout.

Assess AI for industrial, logistics and maritime workflows. Define evidence, operator control and acceptance tests before selecting a partner.

Take AI-generated software from prototype to production. Scope code review, security testing and release evidence for a governed build.

15 minutes. No pitch deck. Just a conversation about what AI can do for your team.

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Prototype in 7 days