AI for mid-market companies: use cases, costs and rollout 2026

In our 250+ projects, three categories pay back fastest: (1) document processing and extraction, (2) internal assistants on company data (RAG), and (3) camera-based quality checks in production. All three can go live in 3–6 months with measurable relief.

Predictive maintenance, computer-vision quality checks, production planning on real order data, and documentation assistants for maintenance and CE files—when training data and approvals are in place.

Order quantity optimisation, route planning, customer-service bots, and automated order capture from email or scans—provided ERP/WMS data quality is checked upfront.

RAG knowledge bases on internal documents, faster quote and protocol drafting, IT ticket classification, and HR onboarding assistants—often combined with our AI knowledge base service.

Typical net ranges: quick pilot €12,000–25,000 (one use case), integration pilot €25,000–55,000 (RAG + ERP/CRM), full rollout €55,000–150,000. Running model and hosting costs are often €400–2,500/month. See our AI cost overview at /en/costs/artificial-intelligence.

With a clear scope and existing data, break-even is often 6–18 months. We define KPIs before build—hours saved, error rate, revenue per case—not only model accuracy.

German programmes such as go-digital and ZIM can cover a significant share of consulting and rollout. We support grant applications where timelines fit your project.

Privacy by design: documented data flows, EU hosting or on-premise options, DPAs, and no blind routing to US APIs where your policy forbids it.

Most internal assistants and document AI are low or limited risk. We classify each use case and document the outcome—see our EU AI Act consulting service.

Yes—open models (Llama, Mistral, Phi) on your infrastructure or a German data centre when data must not leave your network.

Use-case workshop (fixed price), proof of concept on real data, pilot with test users, controlled rollout, handover and monitoring—developed in Germany, no offshore handoffs.

Reachable data (even if messy), a domain owner for requirements, and a budget frame. You do not need an in-house AI lab—we provide engineering and operations patterns.

Yes—maintenance, SLAs, drift monitoring, and model updates. We document systems so your IT team is not locked into a black box.