Overview
TensorZero is an open-source framework designed to help developers build, ship, and improve production-grade LLM applications with confidence. Instead of stitching together an LLM gateway, logging, evaluation, and optimization tools, TensorZero unifies these capabilities in a single, coherent platform. You can connect to multiple LLM providers, define routing and fallback strategies, and manage model configuration as code.
With built-in observability, TensorZero automatically captures requests, responses, latency, and errors across your LLM stack, giving you full visibility into real-world behavior. Its evaluation and experimentation workflows make it straightforward to compare prompts, models, and configurations using offline test sets and live traffic. You can track quality, safety, and business metrics over time, then promote the best-performing variants into production.
TensorZero is built for modern engineering teams: it integrates with CI/CD pipelines, supports versioned experiments, and offers APIs and SDKs that fit naturally into existing services and microservice architectures. Whether you are building chatbots, copilots, RAG systems, or internal automation tools, TensorZero provides the infrastructure to move from prototypes to reliable, maintainable, and continuously improving LLM applications.
Pricing
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Use Cases
- Productionize chatbots and support assistants with robust logging, evaluation, and guardrails across multiple LLM providers.
- Build AI coding copilots that safely combine prompts, tools, and models while tracking developer productivity and error rates.
- Operate RAG and knowledge assistants with continuous offline evaluations and online experiments to improve answer quality.
- Standardize LLM infrastructure across microservices, enabling shared gateways, policies, and observability for all teams.
- Run controlled experiments on prompts and models before rolling changes out to mission-critical AI features.
Features
Unified multi-provider LLM gateway
End-to-end LLM observability
Built-in evaluation and test suites
Experimentation and A/B testing
Routing, fallback, and safety controls
Config-as-code and versioning
Production-ready SDKs and APIs
Open-source and extensible design
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FAQ
What is TensorZero and who is it for?
TensorZero is an open-source framework for building production-grade LLM applications. It is built for software engineers, ML engineers, and platform teams who need reliable infrastructure for LLM gateways, observability, evaluation, and experimentation.
Is TensorZero free to use?
TensorZero is open-source, so you can use and self-host the core framework for free under its license. For any commercial offerings or managed hosting, please refer to the latest information on the official website.
Which LLM providers does TensorZero support?
TensorZero is designed to work with multiple LLM providers via a unified gateway. You can connect to popular APIs and extend support through its open, extensible architecture. Supported providers may evolve over time, so check the documentation for the current list.
Can I integrate TensorZero with my existing CI/CD and monitoring stack?
Yes. TensorZero is built to integrate with modern engineering workflows. You can manage configuration as code, plug it into CI/CD pipelines, and export metrics and logs to your existing monitoring tools.
How does TensorZero help improve LLM quality and reliability?
TensorZero provides observability, offline evaluations, and live experimentation so you can measure latency, errors, and quality metrics. You can run A/B tests, compare prompts and models, and safely roll out the best-performing configurations to production.