ParallelM provides the fastest and safest path to AI value by automating the deployment, orchestration, and management of Machine Learning (ML) in Production. ML presents unique challenges in production due to its non-deterministic nature and continuously changing behavior. Further, without proper controls and safeguards, inaccurate predictions from ML algorithms can create significant business risk.
Through its ML Ops Center software solution, ParallelM is pioneering the new discipline of ML Ops - Machine Learning Operations Management. ML Ops Center reduces the time and resources required to deploy and manage ML pipelines in production while at the same time ensuring that they scale and work properly. It helps organizations transform their Machine Learning initiatives into a repeatable, automated, and optimized lifecycle. It empowers Ops teams to manage ML in production while freeing Data Scientists to focus their efforts on building better models. By combining sophisticated code instrumentation, distributed data correlation, and advanced ML analytic algorithms, ML Ops Center provides insight into ML prediction quality in real-time, alerts on issues, and drives corrective action.
ParallelM solves the Operations side of the Machine Learning Application Lifecycle while complementing and integrating with existing ML development platforms and analytic engines.