Follow Datanami:
March 9, 2016

Startups Seek Big Data Leverage with Machine Learning

It’s well understood that machine learning is eating the software world, so it’s no surprise to see tech startups like Cosmify and LodgIQ emerging from stealth today with plans to leverage big unstructured data for a competitive advantage.

San Francisco-based Cosmify came out of stealth today with a new solution that uses machine learning to jumpstart knowledge discovery across a range of information sources.

The company’s solution is designed to scan, analyze, and visualize unstructured data sources, such as documents, tweets, user data, chat logs, and photographs. Machine learning algorithms create a model of the data sources, and then maps all relevant relationships between them based on individual words or properties, according to Cosmify. Users can then explore the model to find outliers, discover behavioral trends, and predict future results.

The company was founded by some the folks behind Summly, the groundbreaking company that was acquired by Yahoo (NASDAQ: YHOO) in 2012. Summly used natural language processing and machine learning algorithms to summarize and condense news stories for consumption on mobile devices, and quickly became a hit.cosmifylogo

Cosmify founder and CEO Eugene Ciurana, who was formerly the CTO of Summly, wants to help companies  do away with “big data shamans” and expensive infrastructure. “Existing players

in the market are too expensive or take a long time to provide relevant results,” he says. “We have found a fantastic balance between relevance, cost, and time essentially being far more efficient than other machine learning platforms out there.

Cosmify initially plans to target cloud-based service providers with its knowledge mining tool. With the volume of the world’s digital data set to grow to a mind-boggling 40 zettabytes by 2020–and 90 percent of that data projected to be unstructured in nature—there is clearly a need for tools like Cosmify to help companies out from under the data deluge.

“Organizations and teams collect too much data to store or to analyze,” says Ross Mason, the founder of Mulesoft and an investor in Cosmify. “Unstructured data like documents, images, emails, and videos, and structured data like tables, and sheets make up the majority of data that is stored these days.”

Meanwhile, New York City-based LodgIQ today also took the wraps off a new service called LodgIQ RM that’s designed to help companies inlodgiq the hospitality industry get top-dollar for their rooms. The service aims to enable organizations to extract meaningful signals by using a wider variety of data sources than is typically used, and by using advanced machine learning and artificial intelligence capabilities.

The company, which used Dato‘s machine learning software to build LodgIQs, pulls in data from sources like market demand information, competitive rates and reviews, customer shopping intent, flight arrivals, vacation rental demand and rates, exchange rates, events, weather, and real-time news feeds.

“Traditional forecasting and optimization algorithms have stayed static for decades, and are only able to take hotel-specific trends into account,” the company says. “LodgIQ RM incorporates deep machine learning and artificial intelligence techniques to extract all relevant signals about evolving demand patterns and price-elasticity that are necessary to optimize revenues and profitability.”

LodgIQ CEO Ravneet Bhandari says that by using “intelligent, self-learning technology,” the software can adapt to hotel properties of any size and any location. “LodgIQ RM was built to de-mystify big data, and convert it into actionable analytics and optimal recommendations, without any hype or buzzwords,” he says in a statement.

Related Items:

How To Avoid the Technical Debt of Machine Learning

How Machine Learning Is Eating the Software World