What is Multi-Model Serving and How Does it Transform your ML Infrastructure?
Multi-model serving (MMS) was a prominent part of the release of Seldon Deploy Advanced at the end of last year. This is […]
Introducing MLServer 1.0: Modern and flexible model serving for machine learning at scale
Introducing ML Server In our mission to democratise access to machine learning (ML) we are pleased to announce the full release of […]
Adaptive Batching & Kubernetes Infrastructure Robustness – Seldon Core 1.11.0 Released!
The Kubernetes MLOps ecosystem continues to evolve at breakneck speed, however it is critical to ensure the foundational features and functionality of […]
Performance Optimizations and MLFlow Integrations – Seldon Core 1.10.0 Released!
Performance of machine learning models is key when teams and organisations are looking to deploy models at scale. Achieving optimal performance for […]
Working at the forefront of AI and powering open source
Calling all software engineers – we’re hiring! Over the last month, we’ve been working hard to shape the future of Seldon by […]
New Machine Learning Monitoring & Interactive Drill-Down Features – Seldon Deploy 1.3 Released!
The lifecycle of a machine learning only begins once it’s deployed to production. This is why this release of our enterprise product […]
SLO-Driven Progressive Rollouts for Machine Learning – Seldon Core 1.9 Released!
Organisations have a growing need to adopt architectural patterns that allow them to deploy, promote and monitor their models at scale. This […]