Launched this week
TensorZero
Open-source stack for industrial-grade LLM applications
4.9•14 reviews•650 followers
Open-source stack for industrial-grade LLM applications
4.9•14 reviews•650 followers
Build industrial-grade LLM applications: one API for every LLM, observability, optimization (prompts, models, etc.), evaluations, and A/B testing — all open source. Turn metrics and human feedback into smarter, faster, and cheaper LLMs. Get started in minutes.
TensorZero
Hi Product Hunt - we're the team behind TensorZero, an open-source LLM infrastructure project.
What is TensorZero?
TensorZero is an open-source stack for industrial-grade LLM applications:
Gateway: access every LLM provider through a unified API, built for performance (<1ms p99 latency)
Observability: store inferences and feedback in your database, available programmatically or in the UI
Optimization: collect metrics and human feedback to optimize prompts, models, and inference strategies
Evaluation: benchmark individual inferences or end-to-end workflows using heuristics, LLM judges, etc.
Experimentation: ship with confidence with built-in A/B testing, routing, fallbacks, retries, etc.
Take what you need, adopt incrementally, and complement with other tools.
Why should you use a tool like this?
Over time, these components enable you to set up a principled feedback loop for your LLM application. The data you collect is tied to your KPIs, ports across model providers, and compounds into a competitive advantage for your business.
Here are some recent blog posts we wrote that illustrate some of the benefits:
Reverse Engineering Cursor's LLM Client
Fine-tuned Small LLMs Can Beat Large Ones at 5-30x Lower Cost with Programmatic Data Curation
We hope TensorZero will be useful to many of you Hunters!
How is TensorZero different from other tools?
1. TensorZero enables you to optimize complex LLM applications based on production metrics and human feedback.
2. TensorZero supports the needs of industrial-grade LLM applications: low latency (thanks to Rust 🦀), high throughput, type safety, self-hosted, GitOps, customizability, etc.
3. TensorZero unifies the entire LLMOps stack, creating compounding benefits. For example, LLM evaluations can be used for fine-tuning models alongside AI judges.
And it's all open source!
How much does TensorZero cost?
Nothing. TensorZero is 100% self-hosted and open-source (Apache 2.0). There are no paid features.
("But really, how do you plan to make money?" PH sneak peek: next year, we're planning to launch an optional, complementary paid service focused on automated LLM optimization, abstracting away all the GPUs needed to handle that. The developer tool we're working on today will remain open source.)
How can I help?
We'd love to get your feedback: features you like, features that are missing, anything confusing in the docs, etc.
TensorZero is 100% open source, so feedback from the builder community helps us prioritize the roadmap, improve the developer experience, fill any gaps in the docs, and so on.
Thank you! Please let us know if you have any questions or feedback.
Congrats on the launch! It's cool how easy TensorZero makes fine tuning - I think a lot of people skip fine tuning today because setting up data collection/curation/evaluation is such a headache.
TensorZero
@k_kelleher Thank you! Yes, we often hear people want to fine-tune but struggle to do it. TensorZero makes it super easy. And results can be very good!
Fine-tuned Small LLMs Can Beat Large Ones at 5-30x Lower Cost with Programmatic Data Curation
TensorZero
@k_kelleher Thanks! I think we can do a lot more with the same tools that are set up to work well together. Hope to make your LLM engineering workflows more frictionless over time.
Agnes AI
Unifying all LLM providers into one super-fast API is just genius, tbh—no more hacky integrations or crazy latency. Open-source too? This is wild, team!
TensorZero
@cruise_chen Thank you! Hope this is helpful for Agnes AI.
TensorZero
@cruise_chen thank you!