Tredence, a leading AI engineering and analytics services company, is powering innovation in artificial intelligence with the launch of its state-of-the-art machine learning operations platform, ML Works. The community launch targeted at data scientists, engineers and analysts will allow them to register and explore ML Works for free. Enterprise launch will follow in September. Industry-wide, companies are struggling with AI projects that fail to make it into production due to bias in data, algorithms or the teams managing them. ML Works is designed to help companies solve complex challenges in ML operations with automated workflows, pre-built solutions to track model degradation and code workflow management.
With ML Works, data scientists can shift their focus from managing machine learning and mitigating risks to augmenting AI innovations. “AI only delivers value if machine learning models are deployed in production, which is why we created ML Works to help enterprises make the most of their machine learning investments,” said Soumendra Mohanty, COO, and Chief Innovation Officer, Tredence. “Breakaway companies across the globe are focused on driving AI-led innovation and faster value realization, and ML Works will help enterprises of all sizes make that leap.” Based on extensive experience in managing several AI customer engagements, Tredence developed ML Works to scale thousands of machine learning models, reduce outages and simplify model monitoring.
Further, the platform monitors the health of models to mitigate bias and detect anomalies, which can be expensive and disruptive for companies employing AI. “First and foremost, ML Works is designed to help data scientists enjoy greater efficiencies without having to worry about monitoring and managing machine learning models in production,” added Sumit Mehra, Chief Technology Officer, Tredence. “This cutting-edge platform will accelerate the machine learning lifecycle, which will be a game-changer in the industry.” ML Works includes data drift analysis for continuous monitoring of production model accuracy, custom metrics and explainable AI to help non-technical users with model predictions.
