TensorZero

TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, optimization, evaluation, and experimentation. It helps developers build and deploy production-grade LLM applications.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is TensorZero?

TensorZero is an open-source LLMOps platform designed for building and deploying production-grade Large Language Model (LLM) applications. It provides a comprehensive stack that includes an LLM gateway for unified API access to various LLM providers, observability tools for monitoring LLM systems, and optimization features for refining prompts, models, and inference strategies. The platform also offers robust evaluation frameworks for benchmarking individual inferences and end-to-end workflows, alongside experimentation capabilities for A/B testing and managing deployments with confidence. TensorZero aims to streamline the development lifecycle of LLM applications, from initial setup to continuous improvement and scaling.

Best used for

Ideal for developers who need to manage LLM infrastructure, monitor LLM system performance, and optimize prompts and models. Especially valuable for those building production-grade LLM applications requiring robust observability, evaluation, and experimentation capabilities.

Common actions

manage LLM infrastructure

monitor LLM performance

optimize LLM applications

evaluate LLM models

experiment with LLM deployments

Capabilities

Key features

Unified LLM API gateway
LLM system observability
Prompt and model optimization
Inference and workflow evaluation
A/B testing and experimentation
Automated AI engineer (Autopilot)
Open-source platform

Target Audience

developer

Integrations

openai-sdkopentelemetryslackdiscordgithub

Pricing & Plans

Open Source

Not publicly disclosed. Check tensorzero.com for current pricing.

FAQs

What is TensorZero Autopilot?

TensorZero Autopilot is an automated AI engineer that analyzes LLM observability data, sets up evaluations, optimizes prompts and models, and runs A/B tests. It leverages the TensorZero LLMOps platform to improve the performance of LLM agents across various tasks.

What components are included in the TensorZero Stack?

The TensorZero Stack unifies an LLM Gateway for unified API access, Observability for monitoring, Evaluation for benchmarking, Optimization for improving prompts and models, and Experimentation for A/B testing. Users can adopt components incrementally and integrate with other tools.

How can I get started with TensorZero?

You can get started by reading the documentation and following the Quick Start guide, which demonstrates how to set up a production-ready LLM application with observability and fine-tuning in just 5 minutes. Support is available via Slack, Discord, or GitHub.

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