Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here. today announced the close of an $11 million funding round to grow its data labeling and predictive insights platform. The money will be used to improve the platform and double the number of employees from 20 to 40 over the next year, CEO Jim Crowley told VentureBeat in a phone interview.

The company intends to hire additional engineers, AI scientists, and staff to bring its solution to market. works by hoovering up news, social media, websites, SEC regulatory filings, and other text-based information in the world and using it to train a general AI model. That model can then be combined with a customer’s data to serve up predictive insights and help them make better decisions.

“The challenge is solving, and the mountain we’re trying to knock down, is to allow that intelligent machines layer to perceive [an event] as it’s happening — just as you do as a human — and to reason across it so the algorithms and the data science layers can react as our particular customers feel fit to whatever problems they’re trying to solve,” Crowley said.

Once data is gathered and labeled, customers use it to power internal quantitative models and algorithms or supply insights for analysts so they don’t have to sift through Twitter feeds or follow every news story.

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“What was words can be turned into a structured, computation representation that can be used mathematically so folks can start to drive new forms of modeling. They can look at the world differently; they can look at risk differently. You can look at prescriptive analytics differently, and those are the things that our customers are doing,” he said.

A number of startups that focus on helping businesses structure data to prepare for AI training and inference have recently emerged, including Scale, which raised $18 million in August, and DefinedCrowd, which raised $11.8 million in July.

Last week, AWS launched SageMaker Ground Truth, an automated service for labeling data.

Going forward, plans to extend its datasets into voice and gain more clients in government, as well as financing clients like banks, hedge funds, mutual funds, and insurance companies.

The $11 million funding round was led by Underscore VC, with participation from Accomplice, Boston Seed Capital, Imagination Capital, and Project 11 Ventures. was created in January 2017 by Crowley and cofounders James Crowley and Jennifer Lum. The company is based in Boston.

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