Laminar
p/laminar-2
Open-source all-in-one platform for engineering AI products
Robert Kim
Laminar — Open-source all-in-one platform for engineering AI products
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Laminar is an open-source platform where you can trace your LLM app, run evaluations, label production data and use it to improve your prompts. Laminar is fast, reliable and offers best-in-class DX. It’s written in Rust and built on top of a modern tech stack.
Replies
Robert Kim
Hey there 👋, I’m Robert, co-founder and CEO of Laminar (YC S24) -> https://www.ycombinator.com/comp... Good AI engineering is all about data and it boils down to three things – collect data, analyze data, use data. Laminar enables teams to do all of that in a single platform. > Unbelievable alpha in looking at data ©️ Hamel Husain (https://x.com/HamelHusain/status...) Collect data – Tracing - Trace every execution step of your LLM application by adding just 2 lines of code. - Laminar automatically traces common LLM SDKs (OpenAI, Anthropic …), and popular LLM frameworks (Langchain …) - We support images, and soon audio! Analyze data – Labeling - Laminar provides tools for your team to efficiently label the data and analyze human labels distribution. - Use this labeled data to better align LLM-as-a-judge with your app requirements. - Use labels as filters to separate “good” and “bad” data. Use data – Evaluations and Datasets - Run custom evaluations locally, from terminal, code, or as part of CI/CD. Visualize and compare results in Laminar UI. - Run hosted online evaluators (LLM-as-a-judge or Python scripts) as production traces come in. - Store golden datasets in Laminar and run evaluations on them. - Collect “good” examples in datasets and then retrieve most relevant ones via API to use as few-shot examples in your prompts. Laminar is fully open-source, built for scale, and production-ready. You can easily self-host it or use our managed version for production. Laminar is extremely fast, reliable, and built on top of a modern stack. Our frontend is in Next.js, backend is written in Rust🦀, trace ingestion is done over gRPC, messages are sent across services through RabbitMQ and analytics is managed by ClickHouse. Join the ranks of our contributors and star ⭐ our repo here → https://github.com/lmnr-ai/lmnr (we have lots of exciting things to do!) Get started with a managed version today → https://www.lmnr.ai (use our ProductHunt discount to get 3 months free of pro version).
Jonny Miles
unbelievably solid looking platform! congrats on the hard work paying off!
Robert Kim
@jonnymiles Thank you!
Aidar Nugmanoff
Although I am not building on AI as of now, Laminar is the only viable way that I envision for myself when I will finally do! Amazing product and even more amazing team, congrats on the launch! Alga!!
Casey Traina
Have over 45k pipeline runs with Laminar -- love these guys
Ant Wilson
yes! brilliant product, brilliant team.
Robert Kim
@antwilson Thank you Ant, couldn't have done it without Supabase :)
Germán Merlo
Great job team! Really congrats
Aditya Lahiri
ah a data flywheel for LLMs. Sick!
Max
Go lmnr team 🔥🚀
Robert Kim
@mxcrbn Thank you Max!
Sumanyu Sharma
Incredible product and team!
Robert Kim
@sumanyu_sharma thank you Sumanyu!
Ivan Tsybaev
This looks very exciting! I've just sent this to our engineering team to use.
Robert Kim
@ivan_tsybaev Awesome, thank you Ivan!
Philipp
Congrats on the launch @skull8888888 We're currently evaluating a few players in this space and laminar looks perfect! Awesome work!
Robert Kim
@hadjimina Thank you! Ping me anytime, would love to help you onboard!
Ilia Semenov
Product that all of us need! Great job!
Robert Kim
@iliasemenov thank you!
Bon
Congrats on your launch, team Laminar! I'm fond of the name and logo, is there a story behind them?
Robert Kim
@bonvisions Thank you! Name comes from laminar flow, which is essentially stable flow as a oppose to turbulent flow. If you ever turned on the tap and water looked like it was frozen, it is a laminar flow. Logo represents exactly that! I went through many iterations with it, this is the latest, cleanest one.
Andy Li
Congrats on launching guys! The product looks very polished
Robert Kim
@andydy25 Thank you Andy 🙏, next basketball session when?
Huzaifa Shoukat
Huge congrats to the Laminar team on today's launch! I love how you're streamlining AI product engineering into one open-source platform. Quick question: How do you envision developers leveraging Laminar to improve their LLM app prompts - are there any specific use cases or success metrics you're excited to see emerge from the community?
Din Mailibay
@ihuzaifashoukat thanks! There are two things we are looking forward to – human-aligned llm-as-a-judge and dynamic few shot examples. First is that LLM-as-a-judge is of no use, and may even be harmful, unless it is aligned to quality human labels. Second is that few shot examples work much better if they are relevant to the current input. And you can use Laminar for both!
Olena Variacheva
I recommend Laminar for developers working with AI products and large language models. This open platform offers all the tools you need to track your LLM applications, run estimates, label production data, and optimize queries.
Johannes Danielmeyer
Hey @skull8888888 @din_mailibay I’m genuinely impressed by how you’re helping developers trace and improve LLM applications. The way you approached the challenge of making this process so accessible and effective really stands out. We’re working on something for founders that could really benefit from insights like yours. Sent you both an email (founders@lmnr.ai) with a bit more context if you’re open to it. Cheers, Johannes
Manu Hortet
Congrats on the launch guys! I love to see the progress - it looks so easy to setup now 👀
Tommy He
Congrats lmnr team! I can attest to it being the only reliable and performant LLM monitoring platform I've tried. Founding team is great to talk to and super responsive.
Robert Kim
@tommy_he1 Thank you Tommy! We love working with you!
Joel Kek
Looks incredible, congrats team!!!