MLOps™ Makes Machine Learning Work in Production
ParallelM’s MLOps moves ML pipelines into production, automates orchestration, and guarantees machine learning performance 24/7. It is the single solution where data scientists, IT Operations, and business analysts come together to automate, scale, and optimize machine learning across the enterprise.
Automate Deployment
ML Health
MLOps Center Dashboard displays ML Health, alerts, and key performance indicators
Deep diagnostic templates with data & model snapshots ensure rapid problem resolution & ML continuity

MLOps is powered by IONS – Intelligence Overlay Networks – a new paradigm for machine learning management

ParallelM has developed patent pending innovations in production model management and collaboration, automated analytics of live ML prediction quality, ML orchestration, and heterogenous engine/language support.

More technology information will be released soon. Stay tuned or contact us to learn more!

System Components
MLOps Center is the primary workspace for Operations & Data Science collaborating to ensure ML success in production. It includes intuitive dashboard views, ML Health indicators, KPIs, and advanced visualization and diagnostic tools.
MLOps Server Orchestrates ML Applications and pipelines via the Agents. It executes policies, manages configuration, and sends data to the MLOps Center. MLOps Server enables automation of all the key tasks related to deployment and management of ML.
MLOps Agents triggers analytics engines and manages local ML pipelines. It provides visibility into the activity of the pipeline and sends alerts, events, and statistics to MLOps Server. Compatible with popular analytic engines including Spark, TensorFlow, and Flink
Flexible Deployment Options MLOps can be deployed in the cloud, on-premise, or in hybrid scenarios. It also works across distributed computing architectures that include inter-operating, diverse analytic engines (Spark, TensorFlow, Flink, PyTorch). ParallelM works with you to define the best deployment configuration for your specific needs.
MLOps leverages your existing tools. Maximize the benefit from investments you have already made in your machine learning infrastructure