Exit planning

Topic: Avoid vendor lock-in
All topics334

Inference

Keep your coding tools14Lower inference cost23Model library39Run models without infra work35Scale without limits17Switch models safely24

GPU compute

Keep GPU jobs running32Lower GPU cost34Pick the right GPU25Secure GPU capacity30

Both

Avoid vendor lock-in15Meet EU requirements46

7 articles in Exit planning

Articles

26 August 2026

AI Vendor Risk Assessment: A Procurement Checklist

Standard third-party risk questionnaires miss AI-specific vulnerabilities like model data retention and training rights. Here is the exact checklist procurement teams need to vet AI infrastructure vendors, complete with our own honest answers.

22 September 2026

Multi-Provider Inference Failover: Two Endpoints, One Codebase

If your product stops when one inference provider does, this guide puts a second endpoint behind the same code path. Learn how to configure multi-provider fallback, handle rate limits versus timeouts, and avoid breaking EU data residency during failover.

15 September 2026

Self-Hosting vs Managed EU Inference: The Independence Trade-Off

Compare processing location, provider access, portability and operational control before choosing managed inference or self-hosting. Match the deployment and contract to your actual requirements.

20 August 2026

Model Deprecation Risk: Version Pinning & Notice Periods

When an API provider retires or silently updates a model, the resulting breaking changes force a rapid, unplanned migration. Discover how version pinning, rigorous regression testing, and transparent Service Level Agreements protect your infrastructure from deprecation risk.

1 September 2026

AI Pilot Exit Criteria: Making Reversibility a Requirement

A staggering of enterprise generative AI pilots fail to deliver measurable business impact. Defining explicit exit criteria and choosing a reversible infrastructure stack ensures you can stop a proof of concept cleanly without stranded costs or vendor lock-in

25 August 2026

Porting Fine-Tunes and LoRA Adapters Between Providers

The true value of your fine-tune is the knowledge embedded in its weights. By extracting your LoRA adapters as portable artefacts and avoiding proprietary serving layers, you can freely migrate your custom models across any infrastructure without vendor lock-in.

21 May 2026

Multi-Cloud GPU Strategy: How to Avoid AI Infrastructure Vendor Lock-In

A Parallels-commissioned survey reports that 94 percent of organizations are concerned about vendor lock-in. Architect an open-stack, multi-cloud GPU strategy that keeps your AI workloads portable and cost-effective.

All articles

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