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ChorusGraph
Native agent runtime with semantic cache one pip install
ChorusGraph is a native agent graph runtime (Apache-2.0) — BSP scheduler plus a local semantic cache that skips redundant LLM calls when similar routing already happened. One pip install; not a LangGraph wrapper. this is an alternative with amazing benefits over LangGraph! https://insightitsgit.github.io/ChorusGraph/benchmarks.html see the numbers and never use langgraph to save your llm cost. https://insightitsgit.github.io/ChorusGraph/
Hey Product Hunt — I'm Amin, maker of ChorusGraph at Insight IT Solutions.
Quick context: we're relaunching today as ChorusGraph — yesterday's listing pointed at the wrong product. This page is the native agent runtime, not our separate PrismGuard firewall.
What ChorusGraph is: Apache 2.0 agent graph runtime — not a LangGraph wrapper. BSP engine + PrismCache semantic routing to skip redundant LLM calls, plus a native Route Ledger (per-hop audit without LangSmith).
We publish paired benchmarks vs LangGraph — same prompts, tools, model on Azure:
→ Finance single (n=300 heavy): ~73% lower mean latency, ~76% fewer LLM calls
→ Healthcare multi: +15pp success, ~79% cache hits, abstain 3% vs 15%
→ We disclose where we tie: HC2 p95 wall-clock ~even at heavy scale
Try it:
pip install chorusgraph
chorusgraph-demo
Chroma RAG walkthrough:
github.com/insightitsGit/ChorusGraph/tree/master/chorusgraph/examples/chroma_local_rag
Full report:
github.com/insightitsGit/ChorusGraph/blob/master/benchmark/results/azure_heavy_20260708_140300/mvp_scenarios/heavy_20260708_140300/COMPARISON_REPORT.md
I'd love feedback on:
1. Where ChorusGraph fits vs your current LangGraph graphs
2. Cache hit patterns on your real agent traffic
3. What you'd need to pilot this on one production workflow
I'll be here all day — ask anything.
Really cool to see a non-LangGraph option that actually ships with benchmarks instead of vague claims. The BSP scheduler plus semantic cache combo makes sense for cutting redundant calls on routing-heavy flows.
pip install and it just worked, the semantic cache skipping repeated calls actually showed up in my logs right away. nice to see a graph runtime that isn't wrapped around langgraph
the semantic cache hitting on redundant routing is genuinely clever, that's the kind of thing that adds up fast in real agent workloads
How does the semantic cache actually decide when two prompts are similar enough to skip the LLM call? Curious if that ever bites you with subtle differences in routing intent.
How does the semantic cache actually detect similarity across different prompt phrasings, and what's the hit rate you're seeing in real workloads versus the benchmarks?
pip install was painless and the semantic cache actually cut repeat routing calls on my agent loop, pretty noticeable drop in token spend.
About ChorusGraph on Product Hunt
“Native agent runtime with semantic cache one pip install”
ChorusGraph was submitted on Product Hunt and earned 7 upvotes and 12 comments, placing #95 on the daily leaderboard. ChorusGraph is a native agent graph runtime (Apache-2.0) — BSP scheduler plus a local semantic cache that skips redundant LLM calls when similar routing already happened. One pip install; not a LangGraph wrapper. this is an alternative with amazing benefits over LangGraph! https://insightitsgit.github.io/ChorusGraph/benchmarks.html see the numbers and never use langgraph to save your llm cost. https://insightitsgit.github.io/ChorusGraph/
ChorusGraph was featured in Open Source (68.6k followers), Developer Tools (515.9k followers) and Artificial Intelligence (473.7k followers) on Product Hunt. Together, these topics include over 196.7k products, making this a competitive space to launch in.
Who hunted ChorusGraph?
ChorusGraph was hunted by Amin Parva. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how ChorusGraph stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Amin Parva