We built cognee to give AI agents a better memory.
Today, most AI assistants struggle to recall information beyond simple text snippets, which can lead to incorrect or vague answers. We felt that a more structured memory was needed to truly unlock context-aware intelligence.
We give you 90% accuracy out of the box
The best part is that you can do it in just 5 lines of code!
If you're curious to test it out firsthand, try cognee and give us a ⭐ on GitHub! We’d also love to chat about all things AI memory in our lively Discord – join in to:
Share feedback
Discuss features you want to see next
Learn from our awesome community (+300 members)
If you feel inspired to help shape cognee’s future and build the best AI memory layer out there while sharpening your skills, contribute to our open-source codebase. We have plenty of open issues you can start with!
I love Open-source! Giving AI agents structured memory through knowledge graphs is genius. How do you measure the 90% accuracy claim – is it benchmarked against specific datasets or use cases?
@desmond_ren1 Hi Desmond. We have an entire evaluation framework where we benchmarked cognee using F1, EM, LLM as Judge metrics and Human eval (meaning we went over responses and checked manually) on HotPot. We used standard benchmark, but we also ran benchmarks with our clients.
I'm impressed by this product, would be a game-changer I think. Just one consideration, what are the trade-offs of 5 lines of codes, how can we achieve such simplicity (Sorry I don't have deep dive knowledge on this).
@tomcao2012 Great question! With 5 lines of code you get our default pipeline that works in most general cases. If you have some specific domain knowledge you need to map, you would need to add your rule set and build your own logic, but we provide tooling for this
Congrats on the launch team. Memory is probably the most important component of modern AI systems and what you’re doing with knowledge graphs is a very smart way to solve for it!
cognee
Hey Product Hunt Community! 👋
We built cognee to give AI agents a better memory.
Today, most AI assistants struggle to recall information beyond simple text snippets, which can lead to incorrect or vague answers. We felt that a more structured memory was needed to truly unlock context-aware intelligence.
We give you 90% accuracy out of the box
If you're curious to test it out firsthand, try cognee and give us a ⭐ on GitHub!
We’d also love to chat about all things AI memory in our lively Discord – join in to:
Share feedback
Discuss features you want to see next
Learn from our awesome community (+300 members)
If you feel inspired to help shape cognee’s future and build the best AI memory layer out there while sharpening your skills, contribute to our open-source codebase. We have plenty of open issues you can start with!
Curious how cognee might fit into your business?
📅 Book a 1:1 with me
@vasilije_markovic1 Congrats V. This sounds cool to use and Open Source. Great Combo. Will try for sure!
Manna
I love Open-source! Giving AI agents structured memory through knowledge graphs is genius. How do you measure the 90% accuracy claim – is it benchmarked against specific datasets or use cases?
cognee
@desmond_ren1 Hi Desmond. We have an entire evaluation framework where we benchmarked cognee using F1, EM, LLM as Judge metrics and Human eval (meaning we went over responses and checked manually) on HotPot. We used standard benchmark, but we also ran benchmarks with our clients.
For the standard benchmark, results and how to replicate them check here: https://github.com/topoteretes/cognee/tree/main/evals
I'm impressed by this product, would be a game-changer I think. Just one consideration, what are the trade-offs of 5 lines of codes, how can we achieve such simplicity (Sorry I don't have deep dive knowledge on this).
cognee
@tomcao2012 Great question! With 5 lines of code you get our default pipeline that works in most general cases. If you have some specific domain knowledge you need to map, you would need to add your rule set and build your own logic, but we provide tooling for this
@vasilije_markovic1 ah I see bro, thanks for your response.
AIThumbnail.so
I love how cognee bring RAG to the next level! very impressive team and product! Looking forward what is next :) @vasilije_markovic1
MotherDuck
So much progress in short amount of time, congrats team!
cognee
Thank you@mehdi_ouazza!
The 2025 state of AI Development
cognee
@anitakirkovska Thank you Anita for your support!