Hi HN!<p>We're Gabriel & Viraj, and we're excited to open source TensorZero.<p>To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products.<p>1. Integrate our model gateway<p>2. Send metrics or feedback<p>3. Unlock compounding improvements in quality, cost, and latency<p>It enables a data & learning flywheel for LLMs by unifying:<p>• Inference: one API for all LLMs, with <1ms P99 overhead<p>• Observability: inference & feedback → your database<p>• Optimization: better prompts, models, inference strategies<p>• Experimentation: built-in A/B testing, routing, fallbacks<p>Our goal is to help engineers build, manage, and optimize the next generation of LLM applications: AI systems that learn from real-world experience.<p>In addition to a Quick Start (5min) [1] and a Tutorial (30min) [2], we've also published a series of complete runnable examples illustrating TensorZero's data & learning flywheel.<p>• Writing Haikus to Satisfy a Judge with Hidden Preferences [3] – my personal favorite<p>• Fine-Tuning TensorZero JSON Functions for Named Entity Recognition (CoNLL++) [4]<p>• Automated Prompt Engineering for Math Reasoning (GSM8K) with a Custom Recipe (DSPy) [5]<p>___<p>[1] <a href="https://www.tensorzero.com/docs/gateway/quickstart" rel="nofollow">https://www.tensorzero.com/docs/gateway/quickstart</a><p>[2] <a href="https://www.tensorzero.com/docs/gateway/tutorial" rel="nofollow">https://www.tensorzero.com/docs/gateway/tutorial</a><p>[3] <a href="https://github.com/tensorzero/tensorzero/tree/main/examples/haiku-hidden-preferences">https://github.com/tensorzero/tensorzero/tree/main/examples/...</a><p>[4] <a href="https://github.com/tensorzero/tensorzero/tree/main/examples/ner-fine-tuning-json-functions">https://github.com/tensorzero/tensorzero/tree/main/examples/...</a><p>[5] <a href="https://github.com/tensorzero/tensorzero/tree/main/examples/gsm8k-custom-recipe-dspy">https://github.com/tensorzero/tensorzero/tree/main/examples/...</a><p>We hope you find TensorZero useful! Feedback and questions are very welcome. If you're interested in using it at work, we'd be happy to set up a Slack channel with your team (free).