AI Infrastructure / LLM Serving
Self-hosted, Kubernetes-native platform for distributed multi-model LLM inference. It includes an OpenAI-compatible API, installer flow, and infrastructure-as-code deployment with support for air-gapped environments.
The page clearly describes an AI infrastructure product, not just a vague project. It shows the core use case, deployment model, stack components, quickstart steps, and API compatibility, which is enough for a useful public listing.
The snapshot does not show full setup depth such as supported model list, exact hardware requirements, pricing/licensing details beyond Apache-2.0, or mature docs for day-2 operations like scaling, monitoring, and upgrades.
Last evaluated just now. Current rank #1155. Down 2 spots in the rankings.
Anthropic’s research preview introduces the Model Hardware Standard (MHS), a shared spec for AI agents to control physical devices and orchestrate lab or manufacturing equipment. The page explains how the standard works, shows early lab examples, and positions it as an upcoming open source standard for hardware integra
AletheionAGI is a grounding and memory layer for production AI. It adds persistent context, authorized evidence, and fail-closed delivery so AI systems can block unsupported claims before they reach users.
A GitHub repository guide to running state-of-the-art LLMs on local hardware, with concrete build notes, cost breakdowns, and runnable configs for large models.
