Why partner selection is now a board-level risk
Every LLM vendor promises accuracy and scale. Most deliver one or the other. By the time you notice latency drift, prompt-injection exposure, or inference cost spikes, your product team has already shipped the wrong abstraction.
We run this checklist before the first pilot. It has saved three clients from vendor lock-in and two from evals that would have silently regressed within weeks of launch.
The 12-point eval framework
1. Context-window pricing transparency. 2. Fine-tuning and continual-learning support. 3. Latency SLA compliance with P50/P99 targets. 4. Data residency and privacy posture. 5. Multi-modal roadmap if you need vision or audio. 6. Hidden costs around RAG and agent orchestration.
7. APIs versus managed-platform trade-offs. 8. Vendor lock-in metrics: proprietary formats, model-deprecation policy. 9. Security audits including SOC 2 and penetration testing. 10. Human-in-the-loop guardrails. 11. Eval tooling and model-versioning support. 12. Post-launch support and incident response.
What we look for first
We weight evals and data residency highest. A vendor that lets you freeze a model version and run your own eval suite in CI matters more than raw benchmark scores, and it is surprisingly rare.
We also insist on a costs-and-latency budget quoted upfront. If a vendor cannot give you P95 numbers for your workload shape, walk away.
Pricing, lock-in, and migration
Look for per-token pricing that degrades gracefully under volume, plus a quoted monthly ceiling. Avoid non-refundable minimums.
Lock-in shows up in prompt and embedding schema, not just API surface. Ask for exportable logs, prompt files, and vector-dump access before signing.
Production readiness checks
Demand a reference in your vertical. Billing and healthcare tolerate much thinner error budgets than e-commerce. Verify uptime claims against third-party monitoring instead of vendor dashboards.
How PaidNinjas helps
We run LLM architecture audits for clients before they commit. Our engagements have reduced inference costs by up to 40 percent and brought P95 latency under 320 ms. We also design migrations between vendors so your team keeps their existing abstractions.