Why MLWorks?

                              With the current business challenges and uncertainty, it has become imperative that AI/ML models driving an organization’s business decisions continue to do so effectively. In today’s ever-changing landscape, model and data drift are both very real, and AI/ML models thus need to be monitored on a real-time basis to ensure they stay relevant. When ML models fail in live production, not only do they require valuable data scientists time to fix and redeploy them, they also disrupt the organization’s day to day operations and put it at risk of lapsing on regulatory requirements. The MLWorks accelerator provides customers with a visual provenance graph for an end to end model visibility and pipeline traceability, as well as persona-based dashboards to make real-time model monitoring easy for all personas from data engineers to business users. It also allows continuous monitoring of production models for accuracy and relevance, with auto-triggered alerts in the event of model and data drift.

                              DIFFERENTIATORS

                              MLOps
                              Graph

                              Visual Provenance graph for an end to end model visibility and pipeline traceability, allowing easy troubleshooting of production issues and root cause analysis

                              Persona-Based
                              Dashboards

                              Relevant metrics for Business users, Data scientists, ML engineers, and Data engineers, with a persona-based monitoring journey to make monitoring easy for all personas

                              Model and Data
                              Drift Analysis

                              Analysis of data and model drift with auto-triggered alerts, enabling continuous monitoring of production models for accuracy and relevance

                              Lineage
                              Tracking

                              Provenance review from dashboard metrics all the way back to base models, ensuring full visibility into model operations, including training data

                              Governance
                              and Support

                              Centralized access control, traceability and audit logs to manage multiple user personas & ensure regulatory compliance across platforms, as well as maintenance and uptime governance through an SLA driven response and resolution process

                              Platform-Agnostic Advisory and Development

                              Cross-platform and open source setup and support models to cater to myriad business requirements

                              MEET THE TEAM

                              Pavan Nanjundaiah

                              Associate Principal – Head of Solutions

                              Experienced in building machine learning based solution platforms and delivering Data Engineering projects on Microsoft Azure & AWS. Managed the build and delivery of accelerators at Tredence.

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