Where the system creates leverage
Local and open-source AI is strongest for offline, air-gapped and controlled self-hosted scenarios using Ollama, vLLM and separately licensed models. A pilot should use a recurring task with visible inputs and a reviewable output.
Werkverstand separates product function, model capability and integration. That makes it clear which component creates an improvement or risk.
Data and enterprise controls
Local does not automatically mean secure or compliant. Authentication, encryption, patching, monitoring, backups and model licences become operator responsibilities.
Before rollout we document data classes, permitted accounts, connector permissions, retention, approvals and the manual fallback. A generic claim such as 'GDPR compliant' is not enough.
A dependable implementation path
- Define one workflow and one measure
- Resolve accounts, data and permissions before the pilot
- Test realistic cases and document failures
- Roll out only after quality and governance gates
Decision matrix
| Criterion | Resolve before pilot | Operating evidence |
|---|---|---|
| Task | One clear, recurring output | Quality sample |
| Data | Class, source, rights, retention | Approval and audit trail |
| Operations | Owner, cost, failure path | Monitoring and review date |
Keep it verifiable
Primary sources
- Ollama quickstartSource checked:
- Ollama API authenticationSource checked:
- vLLM OpenAI-compatible serverSource checked:
- Hugging Face model cardsSource checked:
