In AI, Digital Manufacturing, Manufacturing Analytics

Sight Machine

Sight Machine recently announced a venture capital investment from Sony Innovation Fund (SIF), Sony Corporation’s venture capital arm.

We recently sat down with Gen Tsuchikawa, Head of Sony Innovation Fund, to talk about why SIF made the investment, Sight Machine’s impact on manufacturing performance, and Japan’s long-standing leadership in practices like lean and just-in-time manufacturing and continuous improvement.

What is the investment focus of the Sony Innovation Fund, and how did that focus lead you to Sight Machine?

A: Since its inception, SIF has notably been focused on creative and disruptive applications of AI. In that context, SIF’s investment thesis naturally encompasses the enterprise and B2B use-cases for AI as a powerful and practical catalyst to improve operational efficiency and generate new value across many industries. The other angle that SIF has increasingly focused on is Industrial IoT (IIoT). SIF has already invested in IIoT in the past year, both in U.S. (StrongArm) and Japan (iXs).

Sony Innovation Fund has evaluated many companies working in AI and machine learning. Among those companies, what has Sight Machine uniquely achieved?

A: There are many point solutions that solve a specific use-case for a certain type of manufacturing operation or specific machinery (for instance, using computer vision for optimizing semiconductor assembly, or leveraging vibration or sound sensors for predictive maintenance, etc.). But achieving a truly holistic understanding of the end-to-end manufacturing operation is a much more complex challenge: many talk about the opportunity for creating digital twins of factories, and Sight Machine has proven that this can actually be implemented at scale and deliver tangible benefits. Sight Machine abstracts itself from the underlying connectivity and has engineered its platform in a highly modular and flexible way so as to be able to ingest any kind of existing database, logs or formats, and its solution requires no hardware change, allowing deployment in a swifter and cost-effective fashion.

In other words, Sight Machine helps reconcile IT and OT on the factory floor. Its track record of bringing actionable value to customers spanning a wide range of industries—from process manufacturing to automotive manufacturing and precise assembly—is another key parameter that SIF evaluated before deciding to invest in Sight Machine. This is complemented by the fact that Sight Machine’s leadership has a deep understanding yet pragmatic appreciation of the industrial challenges customers face in evaluating and adopting new technologies. Another positive driver is the thriving ecosystem of strategic consulting firms, channel partners and system integrators that Sight Machine has rallied around its platform, as it further enhances the business momentum around the company’s platform and lowers friction for its customers.

What do you see as the market opportunity for this type of technology?

A: Because Sight Machine’s solution is not confined to a certain industrial category, its platform can cover a wide variety of manufacturing and logistics scenarios. While the online and mobile spaces have embraced advanced analytics and predictive AI, this is still a burgeoning theme in the industrial context. As such, Sight Machine enables going beyond using data in a reactive way to leveraging advanced predictive models across manufacturing lines, and even between physical sites. One of the frequent use-cases where Sight Machine’s platform shines relates to energy savings; several of its existing customers are the platform to optimize their energy usage, making Sight Machine a contributor to a cleaner, more sustainable footprint. This is another positive trait SIF correlates with this type of technology.

Japanese companies have long been known for excellence in manufacturing, including continuous improvement in quality and productivity. How can technologies like AI and digital twins complement that?

A: Lean and just-in-time manufacturing (Kanban) as well as continuous improvement (Kaizen) indeed find their roots in Japan, where these methodologies have been implemented and refined over the decades. AI-based solutions can enable leapfrogging from this business process and workflow automation towards the next “Machine Age,” where factories can more astutely and dynamically innovate their business models (i.e. capacity-based pricing, manufacturing-as-a-service, microfactories, etc.). While plant data is plentiful (especially in Japan), it still tends to be difficult to use at scale and, in many cases, requires manual integration and analysis. There’s an opportunity for bringing more consistent, comprehensive coverage across the plants’ operations, real-time analytics and forecasting capabilities, from which even a manufacturing innovation leader like Japan can extract value.

Is Sony incorporating technologies like Sight Machine into its own manufacturing processes?

A: SIF always looks at ways to support its portfolio companies, both within and beyond Sony’s footprint. As such, we look forward to working with CEO Jon Sobel and the Sight Machine team to explore ways to enhance its footprint in and beyond Japan.

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