Choosing the right AI vendor can make or break your product. With hundreds of AI providers offering everything from foundation models to specialized APIs, making the right choice requires a systematic evaluation process. This template helps you evaluate vendors objectively and make defensible decisions.
Why AI Vendor Selection Is Different
Unique AI Vendor Challenges
Rapid Model Evolution
Models improve monthly; today's leader may be tomorrow's laggard
Pricing Volatility
Token pricing changes frequently; lock-in risks are real
Quality Variance
Performance varies by use case; benchmarks don't tell the full story
Data Privacy Concerns
Training data usage policies vary widely between vendors
AI Vendor Selection Template
Copy and customize this template for your AI vendor evaluations:
Contract Considerations Checklist
Key Contract Terms to Negotiate
Pricing & Commitment
- Price lock period (aim for 12-24 months)
- Volume commitment flexibility (+/- 20% buffer)
- Overage rates clearly defined
- Payment terms (monthly vs. annual)
Service Level Agreements
- Uptime guarantee (99.9% minimum)
- Latency SLAs (P50, P95, P99)
- Credit/refund mechanism for SLA breaches
- Planned maintenance windows
Data & IP Rights
- No training on your data without consent
- Data deletion upon termination
- IP ownership of fine-tuned models
- Audit rights for compliance
Exit & Termination
- Termination for convenience clause
- Data portability provisions
- Transition assistance period
- No lock-in penalties after initial term
Vendor Red Flags
Warning Signs to Watch For
Pricing Red Flags
- Unclear or hidden fees
- No volume discounts at scale
- Mandatory long-term commitments upfront
- Pricing changes without notice
Technical Red Flags
- No sandbox/trial environment
- Poor or outdated documentation
- No version pinning available
- Frequent breaking changes
Business Red Flags
- Unclear funding/runway situation
- Key personnel departures
- No reference customers in your industry
- Evasive about roadmap questions
Security Red Flags
- No SOC 2 or equivalent certification
- Trains on customer data by default
- No data residency options
- Unclear incident response process
Recommended Evaluation Timeline
Quick Decision Matrix
When to Choose Each Vendor Type
Choose Major Cloud Providers (AWS, GCP, Azure) When:
- You need enterprise-grade SLAs and support
- Compliance requirements are strict (healthcare, finance)
- You want consolidated billing with existing cloud spend
- Data residency requirements are non-negotiable
Choose Specialized AI Vendors (OpenAI, Anthropic) When:
- State-of-the-art model quality is critical
- You need the latest model capabilities quickly
- Your use case is language/reasoning heavy
- Speed of innovation matters more than stability
Choose Open Source / Self-Hosted When:
- Data cannot leave your infrastructure
- You need full model customization control
- Long-term cost optimization is the priority
- You have strong ML engineering capabilities