TensorZero
TensorZero creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.
It’s fully open source.
- Integrate our model gateway
- Send metrics or feedback
- Optimize prompts, models, and inference strategies
- Watch your LLMs improve over time
It provides a data & learning flywheel for LLMs by unifying:
- Inference: one API for all LLMs, with <1ms P99 overhead
- Observability: inference & feedback → your database
- Optimization: from prompts to fine-tuning and RL (& even 🍓? →)
- Experimentation: built-in A/B testing, routing, fallbacks
Who are we?
We’re a small technical team based in NYC.
Viraj Mehta (CTO) recently completed his PhD from CMU, with an emphasis on reinforcement learning for LLMs and nuclear fusion, and previously worked in machine learning at KKR and a fintech startup; he holds a BS in math and an MS in computer science from Stanford.
Gabriel Bianconi (CEO) was the chief product officer at Ondo Finance ($14B+ valuation in 2024) and previously spent years consulting on machine learning for companies ranging from early-stage tech startups to some of the largest financial firms; he holds BS and MS degrees in computer science from Stanford.
Get started
Start building today. Check out our Github, Quick Start, or Tutorial.
Questions? Ask us on Slack or Discord.
Using TensorZero at work? Email us at hello@tensorzero.com to set up a Slack or Teams channel with your team (free).