The RFP Theater
Enterprise AI vendor evaluations follow a script that everyone knows is broken but no one changes. You write an RFP with 200 requirements. Vendors respond with glossy documents claiming to meet all of them. You schedule demo days where vendors show their best scenarios with cherry-picked data. You build a feature comparison matrix. The vendor with the most checkmarks wins.
Six months later, you discover the vendor cannot handle your actual data, their "enterprise-ready" product crashes under load, and the features they demonstrated require custom development that was not in the contract.
We see this pattern repeatedly. Here is a better approach.
The One-Week Vendor Evaluation
Day 1-2: Define the test, not the requirements.
Instead of listing features, define a concrete test scenario using your actual data and your actual use case. Not a toy example. Your messiest, most representative real-world scenario. Send this test to three vendors (never more than three) with the instruction: "Show us your product handling this scenario on a live call. No slides. No demos with your data. Our data, your product, live."
This single step eliminates 80% of vendor evaluation waste. Most vendors cannot pass this test, and you learn that in hours rather than months.
Day 3-4: Evaluate what matters.
For the vendors that pass the live test, evaluate three things:
- Quality on your data: Not benchmarks, not case studies. How does the system perform on your specific data? If it is an LLM-based product, test it against your edge cases. If it is a prediction system, run it against your historical data. Measure precision and recall on your terms.
- Integration reality: How does the product connect to your existing systems? Not "we have an API" but "show me the API documentation, the authentication flow, the webhook support, and a working integration example." Ask to speak with their integration engineering team, not their sales engineers.
- Failure handling: Every AI system fails. How does this one fail? What happens when the model is uncertain? When the service is slow? When the input data is malformed? A vendor that has thoughtful answers to these questions has production experience. One that hand-waves has not shipped at scale.
Day 5: Reference calls with the right questions.
Forget generic reference calls. Ask specific questions:
- "What was the biggest surprise after you deployed?"
- "What does the vendor's support response time look like at 2 AM when something breaks?"
- "If you were starting over, would you choose the same vendor?"
- "What is the real total cost of ownership, including internal engineering time for integration and maintenance?"
Red Flags That Should End an Evaluation Immediately
"We can customize that for you." If the core product does not solve your problem, custom development promises are rarely delivered on time, on budget, or to specification.
Benchmark performance only. If a vendor can show you benchmark scores but not live performance on real-world data, they know their product does not perform as well in practice.
No production references in your industry. An AI product that works for retail may not work for financial services. Industry-specific nuances matter enormously.
Pricing that requires annual commitment before pilot. Any vendor confident in their product will offer a paid pilot with clear success criteria before requiring a long-term commitment.
A disciplined one-week evaluation produces better vendor decisions than a three-month RFP process. The key is testing with real data, evaluating live performance, and asking the questions vendors hope you will not ask.