MLOps Community supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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An open-source platform for tracking ML experiments, evaluating models and prompts, deploying models, and adding LLM observability. opensource.
Version and deploy your ML models following GitOps principles.
Full-stack AI platform focused on multimodal agents and consumer-scale deployment.
Milvus is open source vector database for production AI, written in Go and C++, scalable and blazing fast for billions of embedding vectors.
Metorial supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Helps teams build, deploy, observe or operate machine-learning systems.
Ship AI agents that reason, remember, and act in TypeScript. Mastra provides memory, tools, MCP, and observability to go from prototype to production.
Observability and prompt management platform for LLM-based apps. Take your LLMs to the next level.
A model gateway and unified interface for multiple model providers.
Algorithms for learning and inference with discrete probabilistic models.
A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
Neural network inference from the command line, implemented in CHICKEN Scheme.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
LLM Ops platform with Analytics, Monitoring, Evaluations and an LLM Optimization Studio powered by DSPy.
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Open-source all-in-one platform for engineering AI products. Traces, Evals, Datasets, Labels.
KubeStellar Console supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Kubeflow makes deployment of ML Workflows on Kubernetes straightforward and automated.
Standardized Serverless ML Inference Platform on Kubernetes.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open source MLOps project that eases model handoffs between data scientist and DevOps.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Kubernetes custom resource definition for serving ML models on arbitrary frameworks.