176 Interest Score
52 Discussions
0.30 Engagement
Sep 2023 Launched
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Evaluate your AI applications with Braintrust: the enterprise-grade stack for building high quality AI products. From experiment tracking, to prompt playground, to data management, we take uncertainty and tedium out of shipping AI.

What the Community Said

Thanks so much for hunting us @rrhoover We're excited to introduce Braintrust, a platform for running and tracking AI evaluations (“evals”) [1]. At my previous startup Impira and leading AI at Figma, we had this recurring problem where we never knew if changes we made to our products would improve or regress key user scenarios. We built some tooling to solve this problem and after talking to other developers learned that it was a widespread issue. Specifically, it’s challenging to establish a gr

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We're seeing a massive shift in how some software products are built, which of course introduces new challenges not covered by incumbent infra. Braintrust is worth watching, founded by @ankur_goyal, former Head of ML Platform at Figma (by way of acquisition).

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Oh, this is intriguing! Your platform seems incredibly powerful. Congratulations on the successful launch, and keep up the excellent work! Dania from True Nation

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We've been early users of @braintrustdata at @zapier and is has been instrumental in our efforts to measure and improve our AI features while avoiding regressions! Definitely recommend checking them out!

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I've built user facing interfaces with AI backends before and I see exactly what Braintrust is doing! Clear pain point here, I've faced it way too many times! Awesome idea :)

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Frequently Asked Questions

A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.

Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.

Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.

The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.

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