Based on years of research at Carnegie Mellon, Truera helps Data Scientists analyze machine learning to improve model quality, address unfair bias and build trust.
Truera, which provides the Model Intelligence platform, emerged from stealth to launch its technology solution that removes the “black box” surrounding Machine Learning (ML) and provides intelligence and actionable insights throughout the ML model lifecycle. The platform is already deployed at and delivering value to a number of early Fortune 100 customers in banking and insurance.
The company also announced it has raised a $5.1M first round of funding, led by Greylock with additional investors including Wing VC, Conversion Capital, and Aaref Hilaly.
While the use of ML is exploding, ML models are still black boxes. They are created by algorithms that automatically learn complex patterns from the data on which they are trained. As a result, even the data scientist who uses these algorithms to create the model doesn’t know exactly how it works.
This black box problem makes it challenging for data scientists to build high quality models that not only achieve test accuracy hurdles but also generalize and perform well in the real world. Business partners, regulators, operators and customers find it harder to trust and adopt ML-powered applications. Black box models raise societal concerns about fairness, bias and transparency. It’s harder to maintain black box ML model performance and trust over time when new data changes from the training data used to create the model – a challenge called “concept drift” that is top of mind during the current Coronavirus pandemic.
Truera’s Model Intelligence platform has been designed from the ground up to solve these black box problems. Standard Chartered, a leading international bank who is an active proponent of the responsible use of AI, is one of Truera’s early adopters. According to Vishu Ramachandran, Group Head, Retail Banking at Standard Chartered, “The effective use of data and analytics within the Bank is not just a competitive advantage, but also a key enabler of our strategy to better serve our clients. As we scale up our use of artificial intelligence and algorithmic decision making, we want to ensure we continue to do so in a fair, transparent and responsible way. We see Truera as an essential partner in how we do this and in how we build and operationalize higher quality, trusted AI models faster and more efficiently.”
Two of Truera’s founders, Anupam Datta and Shayak Sen, were pioneers in the development of AI Explainability technology for the past six years at Carnegie Mellon where Datta is a professor and Sen earned his PhD. In parallel, Will Uppington was leading product and customer facing teams at a previous startup where he experienced the black box challenges of ML and observed how a lack of model intelligence negatively impacted model development, selling and customer success. Datta, Sen and Uppington joined forces in 2019 to create a model intelligence solution to solve the industry’s black box problem and make sure AI was implemented responsibly and in a way that makes the world better for everyone.
Truera’s AI.Q technology – the basis for its platform – is the best enterprise-class AI Explainability technology in the market. It performs sophisticated sensitivity analysis that enables data scientists and non-data scientists to understand exactly why a model makes a prediction. Current alternatives are less accurate, significantly slower and do not meet all of the enterprise and regulatory explainability requirements.
The Truera platform can be deployed on-premise or in a company’s private cloud in hours, to help customers:
Analyze and explain Machine Learning. Truera’s enterprise-class AI explainability enables data scientists to explain model predictions, and gain new insights into model behavior that can improve the development and operationalization of models.
Improve model quality. Achieving business results with ML requires building high-quality models that are accurate, stable, reliable, explainable and fair. Truera helps data scientists analyze and improve model quality so that models deliver better business results.
Build trust, reduce risk. Trusting black box ML models is hard. ML projects are also risky, subject to high rates of project failures, delays, over-budget spending, and compliance risks. Truera helps data science teams increase trust and address ML project risks.
Operationalize and monitor with confidence. AI applications need new monitoring and management oversight as operational data can “drift” from training data. Truera enables data scientists to address these unique monitoring and management challenges.
“Truera’s Model Intelligence platform and its AI.Q technology are fundamental breakthroughs in AI,” said Jerry Chen, Partner at Greylock, who led Truera’s first funding round. “Removing the black box problem of machine learning is essential to build effective and responsible ML applications. The Truera team has the unparalleled research, engineering and business experience to solve this problem. We are excited to partner with Anupam, Shayak and Will in transforming the way machine learning models are built, governed and operationalized.”
“We are very excited to partner with Standard Chartered and our other customers, and thrilled to have earned support from Greylock, Wing and Conversion Capital,” said Will Uppington, CEO and Co-Founder of Truera. “Our vision is to create software that helps every data scientist analyze, improve and build trust in their models so that the world responsibly embraces AI.”