Enterprise AI Integration

• Use cases prioritized by business value and technical feasibility
• A working first prototype with real data in 4–8 weeks
• One partner for business, data and technology
• Technology-agnostic advice across all major cloud platforms
• The right LLM for your privacy, cost and performance requirements
• A solution that runs in production, not a lab prototype
• Monitoring, support and improvement within an agreed operational scope
• Ongoing advice on new GenAI developments and use cases

Case studies from document processing, smart inbox, knowledge management and product data — from proof of value to production operation.

Which starting point fits your decision?

• Free Use Case Review: Initial orientation based on your process and goals. You receive an assessment of open questions and a recommended next step, not technical validation or a binding ROI calculation.
• AI Due Diligence: An agreed assessment of data readiness, feasibility, integration effort and risks for an investment decision. The output documents assumptions, prioritized actions and next steps. No prototype is included. Fixed price: €19,900.
• Proof of Value: A prototype for one bounded use case, tested with agreed data and success criteria. The prototype and evaluation support a decision to proceed, adjust or stop. Planned timeframe: 4–8 weeks; fixed-price proposal from €24,900 after scoping. Full production operation is not included.
• MVP and integration: A separately scoped expansion for a limited production user group, including the required interfaces, acceptance and operational handover. Scope and schedule depend on assessment results.

If you first need an AI strategy, we discuss readiness assessment, prioritization and roadmap needs in the initial conversation. Data access, contacts, deliverables and dates are agreed before commissioning.

Agree quality and responsibility before rollout

The agreed project scope includes verifiable quality criteria: together, we define acceptable answers or process steps and when a person must take over. A representative test set from your use case helps compare quality and errors before and after changes.

We document relevant data flows, access roles and responsibilities. With your IT security and privacy stakeholders, we clarify requirements for model providers, data processing and logging. This does not replace a legal assessment.

Before production, we agree how incorrect answers are reported, changes evaluated and releases approved. Specific deliverables and acceptance criteria are defined before the engagement.

After go-live: who keeps the solution working?

Before production starts, we agree which tasks your team owns and which Aclue supports. Ongoing support is scoped separately.

• Handover: Operating documentation, responsibilities and training for the agreed components. Together we clarify access, escalation routes and transfer to your team.
• Monitoring: We define which technical failures, quality signals, usage and costs are observed and who responds. Business reviews and user feedback help detect quality changes.
• Changes: Model, prompt and data changes are checked against agreed test cases before release. For critical changes, we define fallback options and release owners.
• Support and improvement: Covered components, service hours, response targets and capacity are set out in the proposal. New use cases and larger extensions are prioritized and priced separately.

Running costs depend on model calls, data volume, hosting, licenses and support needs. Cost ownership, budgets and handling of excess usage are agreed before operations begin. Coverage follows the agreed scope; round-the-clock support is not automatically included.