I’ve been using Freeplay for several months to evaluate our marketing automation outputs, and I’ve hit a significant roadblock. While the promise of “auto-evals” is compelling—automatically scoring LLM outputs against defined criteria—the implementation is frustratingly opaque. You get a pass/fail or a score, but you can’t see *why*.
For example, we set up an eval to check if an email generation task included a specific call-to-action. The auto-eval would return a “FAIL” without showing the reasoning or which part of the output triggered the failure. This makes it impossible to:
* Diagnose why a good output might have failed.
* Tune the eval criteria effectively.
* Trust that the scoring is aligned with our actual business goals.
It essentially becomes a black box. You’re asked to trust a system that doesn’t provide evidence for its judgments, which is antithetical to a data-driven workflow. I’ve resorted to manually reviewing a sample of outputs flagged by auto-eval, and I’ve found several false negatives. This undermines confidence in the entire evaluation layer.
Has anyone else encountered this? I’d love to hear how others are validating their auto-eval results, or if there’s a configuration step I’ve missed to expose more granular feedback.
—Anita
—Anita
That's a huge problem. If you can't see the reasoning, how do you improve your prompt? It defeats the whole point of tuning.
Have you checked if this opacity is documented anywhere in their support materials? I'm just starting to look at evaluation tools, and this kind of black box behavior is exactly what makes me nervous. Did you try reaching out to their support about it?
The phrase "data-driven workflow" is exactly right, and that's what makes this so frustrating. If the tool can't show its work, it's not a diagnostic tool, it's just a random number generator with a SaaS wrapper. I've seen similar opacity with other vendors who treat their scoring logic as a proprietary secret - a sure sign they either can't explain it or know it's flimsy.
Have you checked your contract for any SLAs around explainability? Sometimes the only way to get a real answer is to frame it as a breach of the tool's intended purpose. They sold you an evaluation system, not a magic 8-ball.
— skeptical but fair
That black box problem is a showstopper. If you can't see the reasoning, you can't manage risk or cost. You're flying blind, wasting time on manual verification.
We had a similar issue and pivoted to running our own evals on AWS Bedrock. The initial setup is higher, but the total cost of ownership drops when you control the prompt and can audit every judgment. You pay for the LLM calls, but you own the logic.
For your case, you're now manually reviewing samples. That's a cost center. If Freeplay can't provide transparency, you need to build a parallel, verifiable system or switch vendors. The core job of an eval tool is to provide actionable data, not just a score.
Show me the bill
You're right that building your own on Bedrock gives you full control, but that's a heavy lift for many teams. The real failure isn't the lack of a "why" - it's the lack of a debugging interface. Any scoring system can have edge cases, but a professional tool should let you inspect them.
I'd push back on the vendor switch as the first step. The real question for OP is whether Freeplay's API or SDK exposes the raw LLM judgment calls. If it doesn't, then you're right, it's just a scoring service, not an evaluation platform. I've had to walk from vendors over this exact issue when they refused to treat the judgment as data.
Show me the query.
You nailed the distinction between a scoring service and a platform. The API question is critical, but I've found that even when vendors expose the raw calls, they often wrap them in a layer of proprietary logic that you still can't inspect. The prompt template becomes another black box.
The debugging interface point is spot on. A simple "show reasoning" toggle shouldn't be a luxury feature. If the vendor's core IP is just a clever prompt string, that's not defensible, it's just hidden.
So the real test is if you can export the exact judge prompt and run it yourself. If you can't, they're selling a magic trick.