Sight Machine Raises $29M To Become The 'SAP Of Industrial Data'

'What we're finding is demand for a scalable product because manufacturers understand there is value to be created from their existing data,' a Sight Machine executive says of the industrial IoT startup, which aims to become the 'SAP of industrial data' with its new funding round.


Sight Machine, a San Francisco-based industrial Internet of Things startup, has a lofty goal: to become the "SAP of industrial data" — and it's taking a major step forward with its unique approach to big data analytics for manufacturers thanks to a new funding round.

The company — which claims to be the only provider of a digital twin for the entire manufacturing process — announced on Tuesday a $29.4 million Series C round led by LS Group, a South Korean conglomerate with holdings in electrical equipment and automation systems, among other businesses.

[Related: SAP Launches Leonardo IoT To Meld Physical Data With Business Apps]

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The round, which brings total funding to roughly $85 million, comes as the company increased its customer contract value by almost 400 percent from 2017 to 2018, with deployments at "some of the world's largest companies" across the automotive, food and beverage and pulp and paper industries. That includes Nissan Motor Co., Heineken N.V. and Westrock Co., who are among Sight Machine's customers in North America, Europe, Asia and Australia.

Sight Machine aims to become the "SAP of industrial data" by helping discrete and process manufacturers with the problem of "data variety," according to John Stone, the company's vice president of business development and partnerships.

The company tackles this data variety problem by taking the hundreds of structured and unstructured data sources coming from the manufacturing plant floor and then contextualizing and modeling those data sources into digital twins for real-time analysis and visualization. The digital twins represent anything from parts and machines to lines and assemblies, as well as entire plants, allowing manufacturers to create a model of their entire process.

"This models the entire production process," Stone said.

What separates Sight Machine from other industrial IoT vendors is that it takes a "data-first" approach, according to Stone, which allows manufacturers to quickly create customized analytics and applications for things like predictive maintenance and root cause analysis. Sight Machine's platform also comes with off-the-shelf applications for visualization tools and analytics workflows. In the end, the aim is to help Sight Machine's customers improve productivity, quality and profitability.

Stone likened the problem Sight Machine is solving for manufacturing to how Google's search engine helps people find what they're looking for: the company is "creating models that suck up all that data and index it such that any kind of use case related to data and process can be addressed in real time."

Sight Machine works with three types of partners: strategic consulting firms, systems integrators and cloud service providers. Stone said the company has upwards of 10 partners now, which includes Accenture, Deloitte, Fujitsu and Boston Consulting Group. In addition, the company has cloud partnerships with the three major providers: Amazon Web Services, Microsoft Azure and Google Cloud.

For systems integrators and consulting firms, Sight Machine can help automate the process of data preparation and data structuring. "What we're able to do is streamline that process so they can spend a majority of their time on analysis," Stone said. The value, he added, "is enabling them to scale that aspect of the business."

While partners can make money by receiving a cut of Sight Machine software sale, the real opportunity is in services, according to Stone, which includes things like creating specialized analytics workflows. Sight Machine's platform can also arm partners with the right data to advise on things like organizational changes.

With Sight Machine's plan to expand sales and marketing efforts with the new funding round, the company has found that the "market has woken up significantly" in the last six to 12 months as manufacturers now understand the value of big data and want to make changes fast.

"What we're finding is demand for a scalable product because manufacturers understand there is value to be created from their existing data," Stone said. "Any value that's created there goes to the bottom line."