Posts Tagged ‘Welltok’

IBM Invests in Welltok, a Health Platform Using the Power of Watson

welltok

Dan Primack of Fortune reports, “Last month, IBM committed to invest $100 million in tech startups that are leveraging Watson, the company’s famed cognitive computing platform. [Wednesday], IBM [announced] that the first portfolio company in its ‘Watson Fund’ is Welltok, a Denver-based health optimization platform. IBM is participating in Welltok’s new $22 million Series C funding round, which is being led by venture capital firm New Enterprise Associates. Also investing is Qualcomm Ventures and existing Welltok shareholders Emergence Capital Partners, InterWest Partners, Miramar Venture Partners and Okapi Venture Capital.” Read more

NLP Market Set For Growth; HealthCare Among Leading Early Adopter Industries

rsz_language_pixThe natural language processing (NLP) market is moving ahead at a steady clip. According to the recently released report, Natural Language Processing Market – Worldwide Market Forecast and Analysis (2013 – 2018), the sector is estimated to grow from $3,787.3 million in 2013 to $9,858.4 million in 2018. That’s an estimated 21 percent CAGR.

The report considers the market to factor in multiple technologies — recognition technologies such as Interactive Voice Response, Optical Character Recognition, and pattern and image recognition; operational technologies such as auto coding and classification and categorization technologies; and text analytics and speech analytics technologies; as well as machine translation, information extraction and question-answer report generation.

Driving the uptake, the report notes, is the need to enhance customer experiences, especially in an age when the smartphone rules, and Big Data predominates. Big-time industry adopters of the technology, it cites, are healthcare, banking and financial services, and e-commerce, where a big growth in real-time and unstructured customer data and transaction information can be taken in hand by NLP technology to analyze customer needs and then optimize responses to them, taking out some of the human labor costs of doing so.

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