Golden Horizons
Built by Golden Horizons · AI Evaluation
Golden Eval
A NIST-aligned evaluation framework for LLMs. It tests language models for quality, safety, cost, and latency with statistical rigor, so the AI we ship is measured, not guessed.
This is live software, not a mockup, and you can use it right now.
Try it live at eval.goldenhorizons.io →What it took to build this
Most AI gets shipped on a gut feeling. Someone tries a few prompts, it looks good, it goes live. Golden Eval is the opposite of that. It's how we prove a model is actually good before it touches a client's work. Here's what's under the hood, and why it matters if you're trusting AI with anything that counts.
A rigorous, repeatable test method.
Golden Eval scores models across 34 dimensions and five difficulty bands, trivial through expert, into one weighted composite. The test cases are frozen and versioned (happy-path, adversarial, RAG, and edge), so a score means the same thing every time you run it. That's the difference between a real measurement and a vibe check.
A council of judges, not one opinion.
Instead of trusting a single model to grade the others, Golden Eval uses a council of seven diverse LLM judges with trimmed-mean scoring and 95% bootstrap confidence intervals. One judge can be wrong or biased. Seven, with the outliers trimmed and the uncertainty reported, give you a number you can actually defend.
Adversarial and safety testing.
It doesn't just check whether a model is smart. It checks whether it's safe, with jailbreak, prompt-injection, tool-abuse, and harm replays. Before any model goes near client work, we know how it behaves when someone tries to break it, not just when someone uses it nicely.
Built for release gating.
Golden Eval ships hard, soft, and trend thresholds with CI-ready exit codes, so a model that regresses on quality or safety fails the gate automatically. It also tracks cost (on the order of cents per thousand cases) and p95 latency across OpenAI, Anthropic, and 100+ models on OpenRouter, all against identical rubrics and golden sets. It's a release gate, not a one-off report.
What this means for your business
Golden Eval is built for LLM engineers shipping across model families, but what it really gives you is trust. Two ways that matters to your business:
Any AI we build for you is measured, not guessed.
When we build an AI for your business, we don't pick a model because it's the famous one. We test candidates on your kind of work for quality, safety, cost, and latency, then ship the one that earns it. You're not paying us to gamble on your behalf.
We can evaluate the AI you already trust.
If you're already running AI in production, or about to, we can put it through the same rigor: how accurate is it really, how does it hold up against jailbreaks and injection, what does it cost per request, how fast is it under load. You get a number you can defend before you bet your reputation on the output.
A safety net for AI that's allowed to make decisions.
The moment AI is doing more than drafting text (answering customers, routing tickets, touching real data) you need to know it won't break under pressure or get talked into something dumb. Golden Eval's adversarial testing and release gating are exactly that safety net, and we'd build it into anything we ship for you.
Golden Eval is how we keep ourselves honest, and it's live right now. When you hire us to build AI, you're hiring people who measure their work before they ask you to trust it.
READY TO START
Let's scope what we'd build for you
Start with a $99 AI Readiness Assessment. We'll look at where you're relying on AI (or about to) and tell you plainly what needs to be measured before you trust it in production. You'll leave with a real plan, whether or not you ever work with us again.
Want to see the rigor for yourself? Explore Golden Eval and how it scores models: eval.goldenhorizons.io
Book your $99 AI Readiness Assessment →