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“Above the Trend Line” – Your Industry Rumor Central for 11/18/2019

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, industry partnerships, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide you a one-stop source of late-breaking news to help you keep abreast of this fast-paced ecosystem. We’re working hard on your behalf with our extensive vendor network to give you all the latest happenings. Heard of something yourself? Tell us! Just e-mail me at: daniel@insidebigdata.com. Be sure to Tweet Above the Trend Line articles using the hashtag: #abovethetrendline.

To all of our readers who’ve reached out in the past few months about how much you value “Above the Trend Line,” we appreciate your kind words! We love hearing about how you print out the often long list of industry news bits and take them with you to lunch, on the train, on the plane, and our favorite … to the gym to read in between sets. We love knowing insideBIGDATA is with you when you’re sweating it up. Nice!

Let’s start off this week with some M&A news … Directly, a leader in intelligent automation for customer support, announced the acquisition of AI start-up Kylie.ai. As part of the acquisition, both the Kylie.ai team and their proprietary technology will be brought under the Directly name, representing a tremendous expansion of conversational AI capabilities and use cases available to the market, such as processing refunds, returns, cancellations, and order tracking. Founded in 2014 by Jamasen Rodriguez and Sinan Ozdemir, Kylie.ai offers enterprise-grade AI that gives businesses the ability to automate customer conversations while simultaneously ensuring that all back-end processes are executed seamlessly and completely. The company has developed a proprietary approach to dialogue systems that allows its AI to tackle remarkably complex, transactional conversations with limited integration requirements. This, in turn, has enabled Kylie.ai clients to reduce digital support volume by as much as 50 percent, and phone volume by as much as 70 percent … ZoomInfo, the global leader in go-to-market (GTM) intelligence solutions, announced the acquisition of Seattle-area based technology startup Komiko, whose technology will integrate into the ZoomInfo Powered by DiscoverOrg platform. Designed to accelerate the sales pipeline with valuable analytics, Komiko’s AI-powered CRM automation, playbooks, and predictive analytics will be released as ZoomInfo InboxAI. Founded by Microsoft executives Hal Howard and Ami Heitner, Komiko utilizes machine learning and data science to better automate the CRM process. Now as a function of ZoomInfo InboxAI, the technology can capture contact and activity data buried deep in the email inboxes and calendars of sales representatives. That data is then populated within the CRM system of record — triggering alerts and generating analytics essential to supporting renewals, managing new business pipelines, and giving every organization a 360-degree view of customers, prospects, and partners.

In new funding news, we learned … Siren, the investigative intelligence platform, announced it has raised $10 million in Series A financing led by Atlantic Bridge. The latest round of investment includes DVI Equity Partners, LLC (DVI), a venture capitalist firm that specializes in areas such as national security, enterprise software, artificial intelligence, and data storage and analysis. Frontline Ventures and Enterprise Ireland, the Irish government agency responsible for the development and growth of Irish enterprises in world markets, also participate in this latest financing. In 2018, Siren raised $4 million in seed funding which has enabled it to expand its offering and target new markets … cnvrg.io, the data science platform simplifying model management and introducing auto-adaptive and continual machine learning to the industry, announced the completion of its seed and Series A funding rounds, totaling $8 million. Closely following a successful seed funding round led by Jerusalem Venture Partners (“JVP”), the Series A funding round led by Hanaco VC marks a total of $8 million raised within a year. Fueled by the overwhelming demand for the platform and rapid innovation, cnvrg.io is on track for tremendous growth. The $8 million raised will allow cnvrg.io to open offices in New York City and expand its sales and R&D efforts … Stradigi AI, a Montreal-based leader in Artificial Intelligence (AI), announced that it has closed a $53 million CAD ($40.3 million USD) Series A funding round that will accelerate the company’s expansion in the North American market and support continuous product innovation of their AI platform, Kepler. The Fonds de solidarité FTQ (the Fonds) and Investissement Québec (IQ) led the fundraising, collectively investing $26,4 million CAD. Series A investors also include Holdun Family Office, Segovia Capital Ltd., Cossette Inc., and Stradigi AI’s co-founders Basil Bouraropoulos and Curtis Gavura … Sigma Computing, an innovator in cloud business intelligence (BI) and analytics, announced a capital infusion of $30 million from existing investors, Altimeter Capital and Sutter Hill Ventures. This B2 round will expedite product innovation and help support the company’s rapidly expanding customer base. Previous investment from Series A and B rounds total $28 million.

We also heard of some new people movement news … Synup, the Intent Marketing Cloud powering customer acquisition, advocacy and loyalty for global brands, announced the hiring of Vasu Sundarababu as Head of Data Science. As one of the world’s leading authorities on the business applications of artificial intelligence and machine learning, Sundarababu will oversee the ongoing development of Synup AI and the big data infrastructure that will further advance the machine learning and predictive analytics capabilities of the Intent Marketing Cloud. Sundarababu joins Synup following the launch of the Intent Marketing Cloud and Synup AI, technologies that compile, analyze and make actionable the brand and business data most important for driving consumer intent and purchase consideration. Powering features like automated reputation management, customer acquisition, and business content recommendations, Synup AI will optimize first, second, and third-party data in the Intent Marketing Cloud to drive engagement and conversion for brands and their business locations.

In the new partnerships, alignments and collaborations category we learned … HVR, a leading independent provider of real-time cloud data replication technology, announced a partnership with Tableau Software, the leading analytics platform. Together, the two companies will provide businesses with powerful access to accurate, secure, real-time data to power their business intelligence (BI) analytics and reporting. With this partnership, HVR enables customers to integrate the complex data that powers Tableau’s interactive analytics platform in real-time from multiple on-premise and cloud-based sources. HVR continuously moves large volumes of data quickly, making it available for Tableau users to curate and analyze current data, uncovering insights that guide more informed business decisions … Satisfi Labs , an AI-powered Knowledge Management Platform, announced their work with NHL Seattle. The league’s 32nd franchise partnered with Satisfi Labs to improve the customer experience for seat selection, as well as to help front office staff handle all incoming questions as the team prepares for their 2021 debut. Satisfi Labs implemented their Answer Engine in early September 2019 to manage the team’s most frequently asked questions. The seat-selection assistant went live in October and helps manage incoming questions from the team’s 32,000 season ticket depositors. In addition to addressing general frequently asked questions, NHL Seattle will use the seat-selection assistant to specifically address the seat selection process for thousands of guests.

We also received commentary about the new AWS Data Exchange:

“Data challenges are routinely cited as the primary reason why 87 percent of data science projects don’t make it into production,” commented Matthew Habiger, Chief Data Scientist at TruFactor. “The typical data science team is overwhelmed with identifying what’s accurate and unbiased, normalizing and structuring data and other recurring tasks. Our vision at TruFactor is to democratize access to AI and unique telco-sourced data by delivering “application ready” intelligence, so teams can focus on delivering actual applied value. Consuming this intelligence via the AWS Data Exchange further accelerates the pace at which innovation can be delivered into production and makes it easier to incorporate this intelligence into workflows, tools, and applications.

2020 Trends/2019 Year-in-Review

ML gets operationalized – Companies adopt best practices to operationalize machine learning and go-live in production for mission-critical processes,” Monte Zweben, CEO of Splice Machine. “Teams – Silos are broken and multi-disciplinary teams emerge with data engineers, application developers, data scientists, and subject-matter experts. Process – Companies kill the data lake process and start focusing on applications. Tools – New tools to track data science workflow become the standard (e.g., MLFLow) and new comprehensive data platforms kill the Lambda Architecture.”

“Data Security Scientist: New data superheroes emerge,” commented Mark Cassetta, SVP Strategy at Titus. “A new breed of data scientist can elevate a company’s security strategies by analyzing the complete lifecycle of data with a critical eye to security implications. As this viewpoint doesn’t exist typically today, expect to see this role rise through the ranks to take on increasingly important profile in defining and deploying security policies.”

“As we move into 2020, data management will continue to advance and develop efficiencies that will make the job of having data ready for business purposes faster and more reliable than ever,” commented Todd Wright, Head of Data Management and Data Privacy Solutions at SAS. “While the Data Management space is a diverse field in its practices, there are four trends that will be forefront in 2020: Data Orchestration – The uniting of data integration, API integration, and data movement to support DataOps techniques. This involves combining multiple technologies to deliver a single data flow application to orchestrate data-related activities across varied locations on-premises or in the cloud. Data Discovery – Acknowledged as important “glue” to enterprise software, delivery of a common catalog for finding, provisioning, securing and understanding data and other objects is important to customers. Further, this discovered insight through application of advanced analytics delivers the ability to automate mundane data management tasks and find value in data that previously had been too difficult to discern. Data Preparation – To expand data manipulation activities to a wider audience, development of advanced data transformation using AI to automate cleansing and blending will empower non-technical users. Model Management – The market will see growth in model management – not just management of proprietary or open source models on their own, but managing those models together within one application. With most analytical models never making it into production or possibly outliving their usefulness (known as model decay), organizations will need the ability to easily register, modify, track, score, publish, govern and report on analytical models.”

“One Machine Learning framework to rule them all. Machine learning with models has reached a turning point, with companies of all sizes and at all stages moving towards operationalizing their model training efforts,” commented Haoyuan Li, founder and CTO of Alluxio. “While there are several popular frameworks for model training, a leading technology hasn’t yet emerged. Just like Apache Spark is considered a leader for data transformation jobs and Presto is emerging as the leading tech for interactive querying, 2020 will be the year we’ll see a frontrunner dominate the broader model training space with pyTorch or Tensorflow as leading contenders.”

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