Ghita here, CEO and Co-Founder of ZeroEntropy (YC W25).
We built ZeroEntropy to help developers deploy more accurate retrieval systems, faster. Using our API, you can upload documents of any type, and retrieve accurate and relevant information from your knowledge base, in just a few lines of code.
We just released a new open-weight reranker that outperforms models like Cohere's rerank-3.5, or even Gemini Flash used as a reranker. You can check out the performance here.
At ZeroEntropy we also take the same ELO-based system we used to train our rerankers, use it annotate your data so that you have observability and clear retrieval metrics!
If you want us to bring an extremely robust evaluation framework to your retrieval pipeline message us at founders@zeroentropy.dev or join our slack!
Really impressed by how ZeroEntropy takes AI search to a whole new level—retrieval feels almost human now, kudos to the team for pulling this off so seemlesly!
Theoretically I can guess at the likely positive results but theres an upfront friction to witness those results and I'm not sure of the ROI. It would be good to see a side by side comparison, The POST requests in the docs are good but I imagine something even easier to show the comparative value would be very compelling.
this looks like something I could actually use. Does it work out of the box with existing vector DBs like Pinecone or Weaviate, or does it require its own setup?
That sounds like a solid resource for developers working with AI systems. For those integrating payroll features into their tools, using a paycheck calculator free can be really useful to simplify payment computations and visualize net pay. I found this calculator helpful—it supports various pay structures and deductions without complicating the process
Tried the new ZE ranker as an experiment the other day after half a day debugging the retrieval of ChatGPT's reranker, and was instantly blown away :-D
Congrats on YC W25. The retrieval accuracy problem is definitely real for developers building RAG systems. How does ZeroEntropy handle edge cases with complex document structures? @ghita_houir_alami
Replies
ZeroEntropy (YC W25)
Hey guys!
Ghita here, CEO and Co-Founder of ZeroEntropy (YC W25).
We built ZeroEntropy to help developers deploy more accurate retrieval systems, faster. Using our API, you can upload documents of any type, and retrieve accurate and relevant information from your knowledge base, in just a few lines of code.
We just released a new open-weight reranker that outperforms models like Cohere's rerank-3.5, or even Gemini Flash used as a reranker. You can check out the performance here.
If you want to give it a try, you can check out our documentation, and get an API Key on our dashboard.
Happy Searching!
@ghita_houir_alami
At ZeroEntropy we also take the same ELO-based system we used to train our rerankers, use it annotate your data so that you have observability and clear retrieval metrics!
If you want us to bring an extremely robust evaluation framework to your retrieval pipeline message us at founders@zeroentropy.dev or join our slack!
Congrats for the launch! Upvoted.
As support, I'm giving you a free website audit: you can check there the grammar mistakes, improvements, GDPR/CCPA compliance and it might increase your conversion rates.
https://www.fastaudit.io/audit-report/98bd2f37b3cd24f6543b5299db6490111693c1d085e3cce4f3d172442407af89
Good luck!
ZeroEntropy (YC W25)
@radulepy Thanks a lot! Will check it out!
BestPage.ai
Really impressed by how ZeroEntropy takes AI search to a whole new level—retrieval feels almost human now, kudos to the team for pulling this off so seemlesly!
ZeroEntropy (YC W25)
@joey_zhu_seopage_ai Thanks! We also just released a reranker model that is state-of-the-art and beats models like Cohere's rerank-3.5.
You can try it here! https://docs.zeroentropy.dev/models
BestPage.ai
@ghita_houir_alami are those kind of a new replacement of the old RAG techs？
Linkinize
Congrats on the release 🚀
ZeroEntropy (YC W25)
@naderikladious Thank you so much!
Great work team! Reranker was smooth to integrate and has drastically improved our AI agent's accuracy!
ZeroEntropy (YC W25)
@mahima_manik Thanks a lot! You can check out the docs at https://docs.zeroentropy.dev!
Velocity
Theoretically I can guess at the likely positive results but theres an upfront friction to witness those results and I'm not sure of the ROI. It would be good to see a side by side comparison, The POST requests in the docs are good but I imagine something even easier to show the comparative value would be very compelling.
ZeroEntropy (YC W25)
@kevin_mcdonagh1 Hey Kevin! Makes sense, for our reranker, you can see a full benchmarking write up on our blog here: https://www.zeroentropy.dev/blog/announcing-zeroentropys-first-reranker
this looks like something I could actually use. Does it work out of the box with existing vector DBs like Pinecone or Weaviate, or does it require its own setup?
ZeroEntropy (YC W25)
@sandra_addison Hey! It works out of the box with an integrated vdb! There is a cookbook explaining everything step by step here: https://github.com/zeroentropy-ai/zcookbook/tree/main/guides/index_and_query_quickstart
Onlook
Awesome work team!
@flyakiet thanks!
Ntropy
best RAG company (and team) out there. not even close
this is actually something we could use, managing our search hasn't been as easy as we thought
So excited for this launch!
Happy users of ZE here 🙋♀️
10xlaunch.ai
Congrats on the launch @ghita_houir_alami 🚀
That sounds like a solid resource for developers working with AI systems. For those integrating payroll features into their tools, using a paycheck calculator free can be really useful to simplify payment computations and visualize net pay. I found this calculator helpful—it supports various pay structures and deductions without complicating the process
Been using ZE for months in Lucy my edtech startup live at Harvard, UPenn and others, best retrieval you could get believe me!!!!
Tried the new ZE ranker as an experiment the other day after half a day debugging the retrieval of ChatGPT's reranker, and was instantly blown away :-D
Awesome product! Excited to see what's next :)
Downloaded from Hugging Face!
Smoopit
Congrats on YC W25. The retrieval accuracy problem is definitely real for developers building RAG systems. How does ZeroEntropy handle edge cases with complex document structures? @ghita_houir_alami