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MOKOM 01
Development & Implementation

AI Implementation. From Proof of Concept to Production.

Integration with CRM, ERP and web platform. GDPR-compliant architecture.

Service

Four weeks to a decision. Fixed price, clear exit criteria.

  1. The challenge

    Most AI projects don't fail on the technology, but on what comes after the prototype. Integration with existing systems, GDPR data protection requirements, scaling under real usage conditions and ongoing operation are problems an isolated PoC doesn't solve. Anyone buying AI as a consulting service gets recommendations. Anyone needing implementation needs a team that also knows the systems.
  2. Our approach

    Four weeks. Fixed price. One clearly defined use case.
    Every AI project starts with a structured proof of concept: a measurable success criterion, a real usage context, a clear path to production. No PoC without exit criteria, after four weeks there's a basis for decision, not an open agenda.
    GDPR compliance isn't a later check but part of the architecture from the start: records of processing, a data protection concept and technical measures are developed in parallel with the implementation. After the PoC comes integration into existing infrastructure (CRM, ERP, web platform or internal tools), without dependence on a single AI provider. For ongoing operation, model monitoring and continuous optimisation there's a direct transition into our AI Managed Services.
  3. Deliverables

    —
    Proof of concept (four weeks, fixed price) with success measurement and recommendation
    —
    System integration into existing infrastructure with documented interfaces
    —
    GDPR-compliant architecture with data protection concept and records of processing
    —
    Technical documentation for operation, maintenance and further development
    —
    Structured handover to AI managed services or an internal operations team
Case in point

In practice

  1. Industry

    Enterprise / Financial services
  2. Challenge

    An internal AI chatbot existed as a prototype. Built with a cloud tool, without a GDPR concept, system integration or operational documentation. Going live was blocked by legal and IT security review.
  3. Approach

    PoC in four weeks with a new architecture approach (Anthropic Claude API, on-premise deployment option), GDPR concept developed in parallel, full integration into CRM and intranet after PoC approval.
  4. Result

    Live after 12 weeks, GDPR sign-off by the legal team, operated continuously in the AI managed services model.
FAQ

Frequently asked questions

  • The four-week PoC is offered on a fixed-price basis. Scope and price are set before the start. The full implementation after the PoC is also offered on a fixed-price basis, based on the PoC findings. No open budgets, no ongoing hourly billing without a cap.

  • Start the AI readiness score or book an initial call directly. In the call we clarify the use case, data situation and GDPR requirements, and whether a PoC is the right first step or an AI potential audit would make more sense.

  • AI systems need ongoing care: models drift, requirements change, new use cases emerge. The direct next step is our AI managed services, with the same team that knows the implementation.

Every delayed AI project is a month in which competitors build operational advantages —and the gap doesn't grow linearly.