mlops and llmops platform
Real-time machine learning deployment with enhanced observability for any AI application or system, managed your way
Real-time machine learning deployment with enhanced observability for any AI application or system, managed your way
Deploy and scale any AI model or monitoring component across any cloud or on-premise so you’re never limited by vendor lock-in or integration gaps.
Seldon Core 2 standardizes complex AI deployments with Kubernetes-native pipelines, making GenAI and ML applications production-ready out-of-the-box.
Seldon provides real-time monitoring, drift detection, and explainability, so your AI systems stay transparent, reliable, and compliant at scale.
With out-of-the-box features like multi-model serving and overcommit, consolidate workloads to slash infrastructure cost while keeping latency low and throughput high.
A/B testing to shadow deployments, made simple, scalable, and disruption free for seamless real time machine learning.
+Orchestration Framework
Put models into production at scale faster no matter your projects’ requirements, model types, or data source.
+Support and Modules
Our business is your success. Stay ahead with accelerator programs, certifications, hands-on support with our in-house experts for maximum innovation.
Tailored recommendations to optimize, improve, and scale through bespoke, data-driven suggestions.
A dedicated Success Manager who can support your team from integration to innovation.
Don't wait for answers with clear SLAs, customer portals, and more.
Customized enablement, workshops, and certifications.
Simplify the deployment, support for common design patterns (RAG, prompting, and memory) and lifecycle management of Generative AI (GenAI) applications and LLMs.
Includes
Model Performance Metrics (MPM) Module enables data scientists and ML practitioners to optimize production classification & regression models with model quality insights.
Includes
Add powerful explainability tools to your production ML pipelines, including a wide range of algorithms to understand model predictions for tables, images, and text covering both classification and regression.
Includes
Add powerful explainability tools to your production ML pipelines, including a wide range of algorithms to understand model predictions for tables, images, and text covering both classification and regression.
Includes
+Support and Modules
Our business is your success. Stay ahead with accelerator programs, certifications, hands-on support with our in-house experts for maximum innovation.
Simplify the deployment, support for common design patterns (RAG, prompting, and memory) and lifecycle management of Generative AI (GenAI) applications and LLMs.
Model Performance Metrics (MPM) Module enables data scientists and ML practitioners to optimize production classification & regression models with model quality insights.
Includes
Add powerful explainability tools to your production ML pipelines, including a wide range of algorithms to understand model predictions for tables, images, and text covering both classification and regression.
Add powerful explainability tools to your production ML pipelines, including a wide range of algorithms to understand model predictions for tables, images, and text covering both classification and regression.
Finally get real-time applications into production and unlock new opportunities for innovation and growth.
“With our Model as a Service’ platform (MaaS) running on Seldon, we’ve gone from it taking months to minutes to deploy or update models.”
“Seldon has made huge difference to how we scale and deploy our inference Ecosystem.”
“Seldon enables us to productionize models at speed while also adding explainers into every one we productionize. It’s pivotal to our mission of becoming the most advanced AI Factory in the industry.”
Finally get real-time applications into production and unlock new opportunities for innovation and growth.
“With our Model as a Service’ platform (MaaS) running on Seldon, we’ve gone from it taking months to minutes to deploy or update models.”
AI adoption has surged in recent years, but the cost of deploying and scaling models in production now dominates the machine learning lifecycle. This blog explores the biggest cost drivers in production AI and practical strategies to make inference more efficient without sacrificing performance.
Seldon’s modular architecture extends to our pricing, so you can budget accurately and only pay for what you need.
An Open Source lightweight inference server for your machine learning models, built to deploy ML models in simple environments.
A Modular framework with a data-centric approach, built to put models into production at scale, especially for data-critical, real-time use cases (e.g., search, fraud, recommendations).
Accelerator programs including hands-on support plus add-on modules, to ensure your machine learning projects are set up and maintained efficiently.
Module Add Ons
Seldon’s modular architecture extends to our pricing, so you can budget accurately and only pay for what you need.
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