Average proven productivity gain in deploying ML models
100K
Monthly active nodes
Accelerate Model Deployment
Supercharge your deployments with:
Production-Ready Inference Servers optimized for popular ML frameworks
Advanced Experimentation and Traffic Splitting including multi-armed bandits, A/B tests, shadows and canaries
Optimize Infrastructure Resource Allocation to cost-effectively manage deployed models
Manage Models & Risk
Gain insights into operational behavior then track, and respond with:
Custom Alerts when certain metrics or conditions deviate so teams can respond to unexpected behavior
Model Versioning and Rollback to maintain multiple versions of a model and switch easily between them to mitigate unforeseen risks
Address Governance & Compliance
Safeguard against risks and ensure accountability with:
Advanced User Management for granular policies and regulatory compliance
Intuitive Audit Trails, Logging and Alerts that go beyond regulatory requirements and quick troubleshooting
Measurable Return on Spend
By serving models to production with Seldon, our customers benefit from faster of deployment, increased efficiency and a reduction of infrastructure and cloud costs.
Reduced deployment time from months to minutes
“With our Model as a Service Platform running on Seldon, we’ve gone from it taking months to minutes to deploy or update models.”
11x ROI in six months from faster deployments
“Seldon Enterprise Platform gave us the flexibility we needed to be able to manage the disparate policy data we had.”
Measurable Return on Spend
By serving models to production with Seldon, our customers benefit from faster deployment, increased efficiency and a reduction of infrastructure and cloud costs.
Reduced deployment time from months to minutes
“With our Model as a Service platform running on Seldon, we’ve gone from it taking months to minutes to deploy or update models.”
11x ROI in six months from faster deployments
“Seldon Enterprise Platform gave us the flexibility we needed to be able to manage the disparate policy data we had.”