An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.
LiteLLM is an open-source library that provides a single, unified interface to call over 100 LLMs using the OpenAI format. It includes a Python SDK whose completion() function uses the same arguments across providers and returns responses in the OpenAI Chat Completions format, plus a self-hosted gateway with virtual keys, cost tracking and an admin UI.
Quix is described as an agentic AI platform for hardware engineering. It turns test-rig and sensor data into real-time insight and is presented as automating engineering workflows across the V, from requirements through verification, validation and operation.
Pipeline Conversations is a podcast from ZenML featuring interviews with platform engineers, ML practitioners and technical leaders building production AI systems. Episodes cover MLOps and LLMOps topics including Kubernetes workflows, model fine-tuning and evaluation, LLM security, cost optimization, prompt engineering and agents in production.
Kubeflow is described as the cloud native AI platform, composed of modular open source projects forming a Kubernetes-native stack for data and AI workloads. Its subprojects include Kubeflow Pipelines for building and deploying portable machine learning workflows, Kubeflow Trainer for distributed AI training and LLM fine-tuning, Kubeflow Katib for automated machine learning, Kubeflow Notebooks for interactive development environments, and Kubeflow Hub for indexing models and metadata. It is a Cloud Native Computing Foundation project.
Amadeus Code provides music AI infrastructure spanning rights-cleared training data, audio supply and royalty management. Its products include MusicTGA for MIDI songwriting ideas, FUJIYAMA AI SOUND for music and sound materials, and Evoke Music, a royalty-free library. CONNECT is a royalty management platform for copyrights and master rights in Japan.
Agenta is an open-source workspace for AI agents. Agents are built through chat, improved with feedback, and shared with a team, either self-hosted or in the cloud. Integrations and messaging in Slack or Telegram are described on the site.
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LiteLLM is an open-source library that provides a single, unified interface to call over 100 LLMs using the OpenAI format. It includes a Python SDK whose completion() function uses the same arguments across providers and returns responses in the OpenAI Chat Completions format, plus a self-hosted gateway with virtual keys, cost tracking and an admin UI.
Quix is described as an agentic AI platform for hardware engineering. It turns test-rig and sensor data into real-time insight and is presented as automating engineering workflows across the V, from requirements through verification, validation and operation.
Pipeline Conversations is a podcast from ZenML featuring interviews with platform engineers, ML practitioners and technical leaders building production AI systems. Episodes cover MLOps and LLMOps topics including Kubernetes workflows, model fine-tuning and evaluation, LLM security, cost optimization, prompt engineering and agents in production.
Kubeflow is described as the cloud native AI platform, composed of modular open source projects forming a Kubernetes-native stack for data and AI workloads. Its subprojects include Kubeflow Pipelines for building and deploying portable machine learning workflows, Kubeflow Trainer for distributed AI training and LLM fine-tuning, Kubeflow Katib for automated machine learning, Kubeflow Notebooks for interactive development environments, and Kubeflow Hub for indexing models and metadata. It is a Cloud Native Computing Foundation project.
Amadeus Code provides music AI infrastructure spanning rights-cleared training data, audio supply and royalty management. Its products include MusicTGA for MIDI songwriting ideas, FUJIYAMA AI SOUND for music and sound materials, and Evoke Music, a royalty-free library. CONNECT is a royalty management platform for copyrights and master rights in Japan.
Agenta is an open-source workspace for AI agents. Agents are built through chat, improved with feedback, and shared with a team, either self-hosted or in the cloud. Integrations and messaging in Slack or Telegram are described on the site.
