Companies in the category 'MLOps'
These are companies that provide open source platforms and tools for MLOps, enabling the automation and management of machine learning workflows.
Kubernetes-native MLOps deployment platform
Seldon provides a Kubernetes-native MLOps platform for deploying, monitoring, and managing machine learning models and LLM applications in production. Its open-source framework, Seldon Core, enables teams to build composable, data-centric inference pipelines with real-time observability, A/B testing, and drift detection. The company also offers Alibi Explain and Alibi Detect, open-source libraries for model explainability and outlier detection, as well as an enterprise platform with governance and audit capabilities. Seldon was acquired by TrueFoundry in June 2026.
Declarative AI data infrastructure platform
Pixeltable is a declarative data infrastructure platform for multimodal AI applications that unifies storage, transformation, indexing, and orchestration of video, images, audio, and text under a single table interface. It uses computed columns to represent model inference and data transformations, enabling incremental updates, automatic data lineage tracking, and reproducible AI workflows without custom orchestration code.
ML/AI platform built on open-source Metaflow
Outerbounds is the company behind Metaflow, an open-source framework for building and managing ML and AI systems originally developed at Netflix. The company offers a fully managed enterprise platform built on Metaflow that enables data scientists and engineers to design, develop, and deploy production-grade ML and AI applications at scale. Outerbounds was founded in 2021 by former Netflix engineers and was acquired by Anaconda in April 2026.
AI orchestration platform built on Flyte
Union.ai is an AI development platform built on Flyte, an open-source orchestrator for building and running data and machine learning workflows at scale. The platform enables engineering teams to orchestrate, train, and serve AI systems, moving from experimentation to production with reproducible, fault-tolerant pipelines.
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ClearML is an open-source AI infrastructure platform that enables organizations to manage GPU clusters, orchestrate AI workloads, and streamline the full machine learning lifecycle from development to production. Its three-layer architecture comprises an Infrastructure Control Plane for GPU resource management, an AI Development Center for experiment tracking and model management, and a GenAI App Engine for deploying large language models at scale.
AI and agent engineering platform
Arize AI provides an AI and agent engineering platform for building, observing, and evaluating AI applications. It helps close the loop between AI development and production.
Open-source stack for industrial LLM apps.
TensorZero provides a platform for optimizing and deploying machine learning models. Its technology creates a feedback loop for building and improving LLM applications by unifying inference, observability, optimization, evaluation, and experimentation.
MLOps framework for infrastructure-agnostic ML pipelines
ZenML is an MLOps framework for infrastructure-agnostic ML pipelines, trusted by thousands of companies to standardize their AI workflows. It offers a unified MLOps + LLMOps platform, supercharges existing infrastructure, provides reproducible and reliable AI, and acts as a unified ML + LLM control plane.
AI infrastructure for model training/deployment
Tracel AI offers a full-stack solution for AI infrastructure, including high-performance computing, deep learning frameworks, and MLOps platforms. Their tools support efficient model development and deployment.
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