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The external scoring tool that deploys a trained model's scoring artifact into a system you already run, such as Snowflake or Amazon SageMaker, with no new endpoint to operate.
H2O MLOps serves models on the platform. eScorer runs them inside a system your team already operates and governs.
eScorer and H2O MLOps are both ways to put a model into production. You pick one per use case by where the scoring has to run, not both in sequence. Highlighted: Observability, and MLOps, the tool eScorer sits beside.
Same platform either way: the same capabilities, the same governance, and the same audit trail. The choice stays open, so you can switch between them as the business changes, without rebuilding what runs on top.
The H2O AI Cloud for Government has achieved FedRAMP High Certification, delivering the highest standard of cloud security so federal agencies can harness predictive and generative AI without compromising data sovereignty or compliance.
H2O MLOps serves models on the platform and monitors them, with drift monitoring and alerts. eScorer runs the scoring artifact inside a system your team already operates, such as Snowflake or SageMaker. You pick one per use case by where the scoring has to run; they are not steps in one pipeline. eScorer can import models from the MLOps registry.
We will show a scoring artifact deployed into Snowflake or SageMaker, side by side with an H2O MLOps endpoint.