SVP, Corporate Development
John is an experienced executive who has worked with global brands to drive collaboration, new business, and results across organizations at all levels, including companies like Microsoft, Google, AWS, Deloitte, Samsung, American Express and others. He holds a BA from Tufts University and an MBA from Wharton.
As a member of Sight Machine’s executive team, John leads corporate development, which includes alliances, M&A and other activities that keep us growing and sailing smoothly. He is invested in creating a positive team and work culture where people inspire and are inspired to achieve their best. How we play the game really does matter — and it can and should be challenging and fun while we do it.
Chief Revenue Officer
Keith is a senior sales leader with a proven track record of global sales execution and strategy in the business application space including ERP, Field Service Management, CRM Sales and Service, Supply Chain, and Human Capital Management.
A results-driven leader who has built and managed high-performing teams by leading from the front.
A review of Sight Machine’s visibility and analytics tools.
Director, Platform Engineering
Daya Vivek is Director, Platform Engineering at Sight Machine. She has a a 20 year track record in delivering enterprise software products and engaging customers to meet diverse market and user needs. Previously, Daya had 17 year career at IBM spanning multiple roles: an Engineering Manager for the Watson Discovery Service hosted on the IBM cloud, a Solution Architect for the Customer Enablement team for IBM’s Big Data Solution (Infosphere Biginsights), and a software developer in pureQuery (a data access platform for database clients) and IBM’s database engine DB2. Daya has a Master’s in Computer Science from Arizona State University and an MBA from Santa Clara University.
DevOps Engineering Manager
Josh Brown is an Engineering Manager focusing on infrastructure and tooling for Sight Machine. For the last 15 years, Josh has worked to help scale multiple startups across many different industries, from fashion to mobile messaging. Josh uses his experience from previous startups to solve nuanced problems that span well beyond the implementation of technology.
In his personal life, Josh has also been involved in multiple humanitarian efforts, in Mexico and Haiti, and enjoys exploring the world with his family.
VP of Marketing
Ed Jimenez is VP of Marketing for Sight Machine. Previously, Mr. Jimenez led Cisco’s Enterprise and Industry Marketing teams. He also worked as a senior consultant helping Cisco’s largest customers understand how disruptive technologies affect the customer experience. Prior to joining Cisco, Mr. Jimenez led Gartner’s Retail & Consumer Products Practice. He also spent a number of years in the retail and manufacturing industries with positions in technology transformation and operations.
Mr. Jimenez has published a number of papers on retail & manufacturing technology trends and was a regular host for the NBC Morning News Technology Report.
Mr. Jimenez earned his M.B.A. from the University of Illinois.
Director of Product
Harry Wornick is the Director of Product for Sight Machine. For the past several years, Mr. Wornick has led Sight Machine’s product efforts, from infrastructure and data pipeline, to visualization and analytics. Previously, Mr. Wornick was the Senior Product Manager at Support.com, leading the development of cloud-based customer support software.
Mr. Wornick earned his B.S. in Engineering from Harvey Mudd College, where he spent several years working with national laboratories on renewable energy research.
Product Engineering Manager
Ajay Nayak is the Product Engineering Manager for Sight Machine. Previously, he was VP of Engineering for Bakround, a startup focused on improving the recruiting process for hiring managers and candidates using machine learning. Prior to that, he led an engineering team for Insightly, an SMB-focused CRM. He also has consulting experience at Booz Allen Hamilton and Slalom, which has enabled him to gain expertise in process improvement for a variety of industries.
Ajay has a BS in Electrical & Computer Engineering from Rutgers University, and an MEng in Systems Engineering from Stevens. He’s passionate about using technology to measurably improve societal outcomes and is actively involved in youth-oriented volunteering for his local community.
Chief AI Officer & Co-Founder
Kurt co-founded Slashdot.org and has served as a professor at Michigan State University in information management, economics, and policy. Kurt is an accomplished analytics programmer.
CEO & Co-Founder
Jon has served on the management teams of several companies in pioneering industries, including Tesla Motors, SourceForge, and in its early years, Yahoo! Jon holds an BA from Princeton, a JD from the University of Michigan, and an MBA from Wharton.
Lead Applications Engineer & Co-Founder
Anthony has over 12 years of experience developing and deploying robotics, computer vision, and data analysis tools in the manufacturing sector. He is a multidisciplinary software engineer who is equally at home in application engineering, dev-ops, front and back end development, and vision programming.
Jerry has over 20 years of experience in technology corporate finance and public/private equity investments. Prior to his career in finance he was a manufacturing engineer with Silicon Graphics. Jerry holds BS and MS degrees in electrical engineering from Stanford and an MBA from Wharton. He is a CFA charterholder.
VP of Data
Beth Crane, PhD is Vice President of Data for Sight Machine, the category leader in manufacturing analytics. In this role she focuses on helping manufacturers understand how advanced analytical techniques can solve complex problems in production and operations.
Prior to Sight Machine, Beth has worked in both academia and industry and has led the development of analytical and reporting tools used for continuous process improvement.
She received her PhD and Masters of Science degrees from the University of Michigan and was awarded a National Science Foundation postdoctoral fellowship to explore the development of statistical methods for predicting dysfunction in multi-dimensional time series data.
VP of Implementation
Sudhir Arni is Sight Machine’s VP of Manufacturing Transformation. Prior to joining Sight Machine, Sudhir was an engagement manager at McKinsey & Co., where he designed and led manufacturing transformation programs for pharmaceutical and chemical manufacturers. He received joint MBA and Master of Science degrees from the Kellogg School of Management and McCormick School of Engineering at Northwestern University.
CTO & Co-Founder
Nathan Oostendorp is the CTO of Sight Machine, he co-founder the company in 2011. Nathan started his career as a controls engineer at Donnelly Corporation (now Magna Mirror) where he worked on PLC programming, computer vision, data acquisition, and robotics for a major automotive supplier.
In 1996 he co-founded Slashdot.org, a major tech news blog which was the center of the Linux and Open Source Software movement. During this period he spun off several other successful open online communities including Everything2.com (an early precursor to Wikipedia) and PerlMonks.org, the central hub for the Perl programming Language. He also created the first Open Source advertising and analytics platform. He then joined SourceForge.net as the site architect and ushered it through a period of growth where it became a top 100 website globally, and hosted several hundred thousand software projects.
He holds a BS in Computer Science from Hope College in Holland Michigan, and an MSI in Information Science from the University of Michigan.
The Internet of Things generates a lot of data that needs to be processed, and innovative startups recognize that artificial intelligence can lighten the load. Jeff Vance of Network World selected Sight Machine as a 10 hot AI-powered IoT startup. Read on to learn more about what Sight Machine does to address this.
Problem Sight Machine solves: Manufacturers struggle to make optimum decisions quickly. When dealing with problems that emerge on the plant floor, any indecision or delay in decision making could be costly.
In manufacturing, data variety (due to thousands of sources) is far greater than in other IoT use cases, and according to research from Morgan Stanley, the sheer quantity of data is also larger than anywhere else. Traditional analytics tools can’t cope with either the variety or volume.
How they solve it: Sight Machine software uses canonical data models and AI to ingest, integrate, and map massive amounts of heterogeneous data into operational models. The canonical data models represent any machine, line, facility, supplier, part or batch that the manufacturer specifies. Once modeled, data is then systematically and continuously analyzed.
By standardizing the manufacturing models and following a data-first approach to decision making, Sight Machine enables manufacturers to automate data ingestion in a rapid, highly repeatable manner. The standardized model allows manufacturers to create downstream applications that immediately leverage the modeled data.
Analytical techniques include advanced inferential statistics, machine learning and AI, all of which are applied to generate manufacturing-specific insights. Within its platform, Sight Machine analyzes and visualizes data, so results can be viewed via a browser on any connected device.
Why they’re a hot startup to watch: Sight Machine has the deepest pockets in this roundup, backed by $50 million in VC funding. CEO and co-founder Jon Sobel was previously with Tesla and Yahoo, while co-founder and CTO Nathan Oostendorp and co-founder and Chief Data Scientist Kurt DeMaagd previously co-founded Slashdot.org. Finally, the customers Sight Machine has accumulated are impressive, including GE, Fiat Chrysler, and Fujitsu.
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