Alegion Raises $12 Million to Expand Active Learning Capabilities Within Its ML Data Labeling Platform
Funding Will Enhance Alegion’s Ability to Capitalize on Growing Momentum in the Enterprise ML-Ops Marketplace
Alegion, the Gold Standard Data Labeling Platform for enterprise data science teams, announced it has completed a $12 million Series A-2 round of funding led by RHS Investments. Alegion will use the capital to accelerate the integration of Active Learning and other strategic technologies into its Machine Learning Data Labeling Platform.
.@Alegion closes a $12 million Series A-2 #funding round to accelerate its #machinelearning data labeling platform and support growing enterprise #AI projects.
Traditional, human-only approaches to data labeling are often unaffordable when training at scale or when interacting with sophisticated datasets. Paying human workers to label increasingly large amounts of data results in diminishing returns and plateaued model confidence.
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Alegion’s platform blends human and machine intelligence to provide highly accurate labeled data used to train or validate customer’s machine learning models. As demand for ML training data increases exponentially, human judgment alone is not a viable mechanism for labeling and scoring. Active Learning enables the platform to learn while observing the human workers, eventually supplementing or even replacing human judgement with ML inference.
“Just as assembly lines incorporate power tools and robotics to enable scale, ML model development will require machines training machines to achieve the highest levels of model confidence,” said Nathaniel Gates, CEO and founder of Alegion. “Our customers can first leverage human judgement to train their model and then watch as newly trained machines are incorporated that allow unprecedented scaling.”
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The company’s latest round of funding comes at a time when the data labeling market is beginning to enjoy rapid growth and consolidation. The sector is also seeing sizable investments in technology, as the increasing demand for machine learning data outpaces the capabilities of traditionally labor-intensive providers. “Artificial Intelligence’s insatiable demand for accurate training data can’t be provided through human power alone,” says Hank Seale of RHS investments. “Alegion’s ability to supplement human effort with machine learning is strongly differentiating.”
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