Most devs start with one LLM (say GPT-4) works fine for a demo.

But in production:

• Different tasks need different models (e.g., reasoning vs. summarization).

• Vendor lock-in is risky (pricing, reliability, downtime).

• Switching between APIs becomes spaghetti code fast.

Hey Hunters! We re gearing up to launch GraphBit an agentic AI framework with a Rust-powered core and a Python-simple API for building dependable, multi-step AI workflows.

September 11, 2025 at 12:01 AM PDT (09:01 CEST)

Product Hunt: [https://www.producthunt.com/prod...

At InfinitiBit, we re building GraphBit, an Ultra Efficient enterprise-grade LLM framework that helps teams deploy agentic AI reliably and at scale, without the headaches of brittle pipelines.

Here s what makes GraphBit different:

• Scalability Built with atomic reference counting for safe, concurrent execution of complex AI workflows.

• Reliability Workflows are fully serializable and deserializable, so you can pause, resume, or recover without losing state.

• Efficiency & Speed Rust core with Python bindings ensures high performance and low latency.

• Enterprise-Grade Designed for async, parallel execution with multi-LLM and vector database support, observability, and robust error handling.