GraphBit
Rust-core, Python-first Agentic AI framework
5.0•21 reviews•1.5K followers
Rust-core, Python-first Agentic AI framework
5.0•21 reviews•1.5K followers
GraphBit is a high-performance AI agent framework with a Rust core and seamless Python bindings. It combines Rust’s speed and reliability with Python’s simplicity, empowering developers to build intelligent, enterprise-grade agents with ease.
GraphBit
GraphBit
Hey Product Hunt! 👋 Musa here, Founder of @GraphBit
I built GraphBit because I was tired of the same developer pain:
Juggling slow, brittle frameworks that crash under load
Choosing between Python’s simplicity or Rust’s speed- never both
Losing control of observability and scaling in enterprise builds
GraphBit solves that.
Rust under the hood for blazing speed, safety, and async concurrency
Python bindings for a dev-friendly, easy-to-learn interface
Enterprise-first features: real-time observability, crash resilience, multi-LLM orchestration
Our vision? Make building scalable, production-ready AI agents feel as natural as microservices- secure, performant, and developer-first.
🙏 I’d love to hear: What’s your biggest pain when building AI agents? Happy to get feedback, mid-launch or post-launch.
Thanks for being here, excited to build together!
— Musa
@musa_molla 🔥 Congrats on launching GraphBit! Love how you’ve combined Rust’s performance with Python’s accessibility — that’s a killer combo for AI agent frameworks. The enterprise-first angle (observability + resilience) really stands out since most tools ignore those until it’s too late. Curious — how do you see GraphBit handling complex workflows with multiple LLMs at scale? 🚀
GraphBit
@monir_zaman4 Thanks, Exactly- resilience has to come first. For multi-LLM, GraphBit’s lock-free scheduling lets you run models in parallel, so scaling complex workflows stays predictable
GraphBit
@monir_zaman4 Appreciate your question! To add, one of the things we obsessed over in GraphBit was making multi-LLM workflows not just scalable but stable. The lock-free scheduler + async Rust core means even as complexity grows, execution stays predictable without hidden bottlenecks. That’s where GraphBit really sets itself apart.
@musa_molla Really interesting launch! From a people standpoint, I see GraphBit easing one of the biggest organizational pain points: when teams scale, you often end up with developers split between different tech stacks and struggling with bottlenecks. A framework that combines Rust’s performance with Python’s accessibility could help companies onboard talent faster, reduce skill gaps, and keep dev teams more collaborative.
GraphBit
@md_tanzir_hossain Appreciate that, You’re spot on, part of our vision is making it easier for teams to scale without fragmenting across stacks. Rust gives us performance, Python keeps it accessible, and together it helps devs collaborate without the usual bottlenecks
GraphBit
@md_tanzir_hossainAbsolutely, that balance between performance and accessibility is exactly what we designed for. Teams shouldn’t have to choose between speed and collaboration, and GraphBit makes sure they get both.
🔥 This looks really promising, @musa_molla !
The balance between Rust performance and Python accessibility is exactly what a lot of AI teams are struggling with right now. I’m especially curious about the multi-LLM orchestration and how it handles real-world scaling challenges.
My pain point: most frameworks start strong in prototyping but collapse when moving into production workloads. If GraphBit can truly bridge that gap, it’s a game-changer. 🚀
Looking forward to testing it out!
GraphBit
@shoaib_hossain37 Thanks a lot, Shoaib. You nailed the core problem, too many frameworks stay stuck in “demo mode.” GraphBit was built with production workloads first, so multi-LLM orchestration, retries, and concurrency are baked into the execution layer. Excited for you to test it out
GraphBit
@shoaib_hossain37 Exactly, bridging the gap from prototype to production is where we wanted GraphBit to stand out. By making reliability and multi-LLM scaling native to the framework, teams don’t have to rebuild everything once they go beyond demos.
PicWish
@musa_molla Congrats on the launch Musa! Love how you’ve combined Rust’s speed with Python’s simplicity.
what’s been the most exciting use case you’ve seen so far with GraphBit?
GraphBit
@mohsinproduct Thanks so much, One exciting one: a team used GraphBit to run a code-analyzer agent that reviews PRs with multi-LLM orchestration- parallel checks, no crashes, and way faster than their old setup. Seeing it cut review cycles from hours to minutes has been a real highlight.
GraphBit
@mohsinproduct That PR review use case really shows what we’re aiming for, turning complex, multi-LLM workflows into something stable and production-ready. Watching teams save hours while gaining reliability has been one of the most exciting validations for us.
Sprinto
@musa_molla congrats on the launch!
GraphBit
@tuneerprod Thanks a lot, Appreciate the support!
GraphBit
Hey Product Hunt!, Rahmat here — Technical Director at @GraphBit
When we set out to build GraphBit, our focus was simple, Can we make agentic AI workflows both blazing fast and developer-friendly?
Too often, I’ve seen teams hit walls:
Frameworks that look good in demos but buckle at production scale
Debugging nightmares with no visibility into what agents are actually doing
Tradeoffs between raw performance and ease of use
With GraphBit, we refused to compromise.
Rust core → lock-free execution, async concurrency, near-zero CPU overhead
Python API → smooth developer experience without losing control
Enterprise-grade tooling → observability, crash resilience, multi-LLM orchestration
What excites me most? Watching early adopters scale prototypes into production systems without rewriting everything.
⚡ Our architecture is patent pending, but more importantly, it’s open for the community.
We’d love your feedback on where frameworks usually fail you.
👉 What’s the single hardest part of taking an AI project from toy demo to production-ready in your experience?
Let’s build the future of reliable agentic AI together 🚀
— Rahmat
GraphBit
Thanks for checking out GraphBit!
We built GraphBit because we kept running into the same wall while experimenting with agentic workflows: existing frameworks were either too rigid, too bloated, or not designed with research-grade flexibility in mind.
🔹 What it is: GraphBit is an agentic framework built around a graph-based architecture that makes it easy to design, orchestrate, and scale complex multi-agent systems.
🔹 Why it matters: Instead of juggling messy pipelines or hard-coding control logic, you can declaratively define agent behaviors, constraints, and flows as a graph. This makes your system both transparent and extensible.
🔹 Who it’s for: Researchers, developers, and startups who want to go beyond toy LLM apps and actually engineer robust agent ecosystems—whether for reasoning, retrieval, code generation, or domain-specific workflows.
🔹 What’s inside:
A modular core (Rust + Python bindings) for speed + safety.
Native support for graph-structured reasoning & execution.
Utilities for multi-step planning, tool use, and evaluation.
Docs, examples, and starter templates to get building fast.
This is just the beginning - we’re iterating fast and would love your feedback, ideas, and even wild use-cases.
The team behind Graphbit recently reached out to me, and I have to say. I’m impressed with what they’ve built.
Graphbit is a new LLM framework, positioned as a competitor to LangChain, Crew AI, and other similar solutions. Its core mission is to provide a faster, more stable, and truly enterprise-ready alternative to what’s currently available.
It's Built with Rust for performance and stability, and wrapped with Python to make it more accessible to developers.
Deliver 10x greater efficiency compared to existing frameworks, faster execution and lower memory usage.
If you're a developer try it out.
GraphBit
@byalexai Thank you so much, Aleksandar, for the kind words and for hunting GraphBit!
We built GraphBit because we saw how quickly agentic AI ideas can collapse in production when frameworks aren’t fast, stable, or enterprise-ready. Our Rust core + Python wrapper approach was designed to solve exactly that — giving developers a framework that’s not just easy to use, but also efficient enough to run reliably at scale.
For anyone curious, we’ve also published detailed benchmarks(you can check it in our github repo) comparing GraphBit with LangChain, CrewAI, and others, showing how we consistently achieve faster execution and dramatically lower memory usage.
We’d love for developers and teams to give GraphBit a try, share feedback, and help us shape the future of production-grade agentic AI frameworks. 💡
Congrats on the launch 🎉
GraphBit looks super solid - love how you’ve combined Rust’s performance with Python’s simplicity. The enterprise features + patent pending angle really stand out.
Excited to see how teams put this into production 👏
GraphBit
@abbas143official Thank you, We’re grateful for the support and confident GraphBit will set a new bar for agentic AI in production
GraphBit
@abbas143official Appreciate the kind words! Our focus has always been production-first, seeing teams adopt GraphBit for real-world, scalable use cases is what excites us the most.
This product targets the need for technology that significantly improves the AI Agent development process. I think they have a bright future.
GraphBit
@jberkowitz Thank you! That’s exactly the gap we’re focused on closing for AI agent builders. If you try it, I’m keen to know which parts resonate graph runtime, tool orchestration, or observability.
GraphBit
@jberkowitz Thank you, We believe better infra is the key to unlocking the next wave of agent innovation, glad that resonates
GraphBit
@jberkowitz Appreciate that! Our goal is to give builders the kind of infrastructure that makes agent development faster, safer, and production-ready from the start.
Jinna.ai
Congrats on the launch! As I understand, it lets me build AI workflows using python/rust. Does it have any capability when it comes to JavaScript?
GraphBit
@nikitaeverywhere Yes, the JavaScript (js) is in beta version currently in development, after final testing it also will be available ready to use
GraphBit
@nikitaeverywhere Great question! While Python & Rust are our primary focus, we’re actively working on expanding into JS so teams can plug GraphBit into more ecosystems without friction. Stay tuned!