LLM gateway
TensorZero’s stated platform scope includes an LLM gateway for serving as a central layer in LLM application workflows.
TensorZero is an open-source LLMOps platform for building and operating production-grade LLM applications. Its stated scope combines an LLM gateway with observability, evaluation, optimization, and experimentation tools.
TensorZero is an open-source LLMOps platform for production-grade LLM applications. Its stated scope unifies an LLM gateway with observability, evaluations, optimization, and experimentation, covering both application operation and iterative model or prompt improvement.
The project documentation is organized into areas such as gateway, observability, evaluations, experimentation, optimization, integrations, and deployment. However, the official site states that TensorZero is no longer maintained, and the referenced GitHub repository is archived and read-only. It should therefore be evaluated as an archived project rather than an actively maintained platform.
TensorZero’s stated platform scope includes an LLM gateway for serving as a central layer in LLM application workflows.
The project includes observability as a core area, with documentation references to observability quickstarts and inference-related examples.
Evaluations are listed as a platform capability for assessing LLM application behavior, although the supplied evidence does not specify supported evaluators or evaluation outputs.
Optimization is included in the platform scope and repository structure for improving LLM application performance, but detailed methods are not established by the available source text.
Experimentation is identified as a separate project area for comparing or iterating on LLM application configurations; the supplied evidence does not provide further workflow details.
TensorZero is presented as open source and remains available on GitHub, while the official site notes that the project is no longer maintained.
Teams evaluating a shared gateway layer could use TensorZero’s documented platform scope as a starting point for consolidating LLM gateway and operational concerns.
Developers can review the project’s observability area and quickstart references when investigating how an LLM application records or examines inference activity.
Teams comparing LLM outputs may investigate the evaluations area to understand how the archived project approached systematic assessment.
Engineers exploring prompt, model, or application changes may examine the experimentation and optimization areas documented in the repository.
TensorZero is an open-source LLMOps platform described as combining an LLM gateway, observability, evaluations, optimization, and experimentation for production-grade LLM applications.
No. The official TensorZero site states that the project is no longer maintained. The referenced GitHub repository is shown as archived and read-only.
TensorZero remains available on GitHub, according to the official site. The supplied evidence does not establish an actively hosted or supported service offering.
No pricing details are established by the supplied sources. The referenced pricing page returns a 404-like page and does not provide plans or prices.
helicone.ai
An open-source AI gateway and LLM observability platform for developers building AI apps.
eachlabs.ai
each::labs provides a single API for orchestrating more than 600 AI models, with routing, fallback handling, observability, and usage-based pricing. It is designed for teams building and operating production AI applications across video, image, audio, and text workflows.
portkey.ai
Production AI platform with gateway, observability, guardrails, and prompt management for Gen AI teams.
apisix.apache.org
Apache APISIX is an open-source API gateway and AI gateway for routing, securing, observing, and governing API, microservice, and LLM traffic. It helps teams manage dynamic gateway policies through a plugin-based architecture built on NGINX and etcd.
www.newapi.ai
New API is an open-source, self-hosted AI gateway for developers and teams. It provides a unified OpenAI-compatible endpoint for connecting multiple AI providers, selecting models, configuring channels, and monitoring usage on their own infrastructure.
pydantic.dev
An AI engineering stack for type-safe apps, observability, evaluation, and model routing