For teams building AI in high-stakes domains, Scorecard combines LLM evals, human feedback, and product signals to help agents learn and improve automatically, so that you can evaluate, optimize, and ship confidently.
Incredible story, love how you turned a near-disaster into a framework for reliability. Does Scorecard simulate edge cases automatically, or do teams define them manually?
Congrats on the launch! Love the simple workflow and side by side comparison. Curious if you import eval datasets like llm_benchmarks and support local models via Ollama/llama.cpp?
Congrats on the launch! Scorecard looks super useful especially for keeping performance data transparent and easy to understand.
Quick question though: how do you make sure the scoring system stays fair and can’t be easily gamed?
I think it’d be great if users could see a breakdown of how each metric affects their overall score that extra bit of clarity could make it even more valuable.
Darius congrats buddy good launch. Does scorecard offer integrations with Data ETL prods like snowflake?
This feels like one of those products that makes everything else better. Wishing you all the best!
Well that’s exactly what serious AI teams need. Combining human feedback with product metrics kinda closes the loop perfectly. Does it support continuous evaluation in production environments too?
Hey Product Hunt, Darius here, CEO of Scorecard 👋
I almost shipped an AI agent that would've killed people
I built an EMR agent for doctors. During beta testing, it nailed complex cases 95% of the time. The other 5% it confused pediatric and adult dosing and suggested discontinued medications. And the problem wasn't just my agent. My friend's customer support bot started recommended competitors, another founder's legal AI was inventing case law. We were all playing whack-a-mole with agent failures, except we couldn't see the moles until customers found them.
At Waymo, we solved this differently
I helped ship the Waymo Driver, the first real-world AI agent. The difference? Every weird edge case becomes a test. Car gets confused by a construction zone? We built a platform to simulate 100s of variations before the next deployment. We still played whack-a-mole, but we could see ALL the moles first.
That's why we built Scorecard - the agent eval platform for everyone
Now your whole team can improve your agent without the chaos. Here's what Scorecard unlocks:
🧪 Your PM runs experiments without begging engineering for help
🔍 Your subject matter expert validates outputs without Python
🛠️ Your engineer traces which function call went sideways
📊 Everyone sees the same dashboard of what's working
After running millions of evals, the signal is clear: teams using Scorecard ship 3-5x faster 📈 because you can't improve what you don't measure. Checkout how leading F500 companies like Thomson Reuters are shipping faster using Scorecard 🚀
🎁 [Exclusive PH Offer!] Get hands-on help setting up evals today
Product Hunters building AI agents today drop your worst agent horror story below. First 20 teams get me personally helping set up your evals (fair warning: I will get too excited about your product). Stop shipping on vibes and start shipping with confidence.
Love the details you added and features for the agents! Congrats to launch!
Beautiful website meanwhile!