Big Data startup Everstring has acquired $12 million in funding which it intends to utilize in enlisting more data scientists to assist enterprises in identifying prospective sales leads and new clients through predictive analytics. The round was led by Lightspeed Venture Partners, with participation from existing investors Sequoia Capital and IDG Ventures.

EverString puts software agents into customers’ CRM systems to get information about existing leads, essentially names and websites. Then, it goes around the web to gather information about these businesses. “We use natural language processing to crawl the web and convert the unstructured data into structured data,” said EverString’s CEO Vincent Yang.

To determine the attributes of current customers EverString “track[s] 10,000+ indicators”. some of the indicators being, employee size, company revenue, product offering, location, social status, technology, and management bio. The next step is to use machine learning to build models based on the known good customers and bad customers from the clients. “In the machine learning space, we do our proprietary machine learning algorithms by Ph.Ds in neuroscience division at Stanford,” said Yang. With the profiles built Everstring then uses the profile of the client to find them new customers and generate new leads.

EverString uses a subscription based Software as a Service (SaaS) model. Its cloud is hosted on Amazon Web Services (AWS). Founded in 2012, it’s headquarter is in San Mateo, California. The company has 28 people right now and “is comprised mostly of neural network scientists, natural language processing scientists and distributed computing experts,” according to the company.

EverString will use the new funding to hire more data scientists and enterprise sales people. It aims to double its number of employees in one year.

Read more here

(Image Credit: NASA Goddard Space Flight Center)

Previous post

Storm Becomes an Apache Top-Level Project

Next post

Continuent Tungsten 3.0 Pairs Clustering & Replication in One Solution