Squint peers $13M led by Sequoia for AR aimed at B2B to interact with physical objects

Apple and Google’s move into smart augmented reality a few years ago, created ways for people to use their smartphone cameras to detect everyday objects to interact with them, put technology on the map for everyday consumers and provide a way for businesses to build new experiences to appeal to them. It also laid the groundwork for building new frontiers in visual search.

Squinting is one of the startups taking advantage of this concept with what founder and CEO Devin Bhushan describes as “a platform that connects people with the right information at the right time.”

Focusing on today’s business users, it has created a simple and fast way for organizations to create AR-based workflows: users point their smartphone or tablet cameras at the physical objects in the work environment – whether these objects are “smart” and connected or not – can trigger detailed, step-by-step instructions for the use of such machines, log sheets to record maintenance or other work, etc., and they can use generative AI-based interactions to learn more about what they need to know.

Squint has so far acquired a number of enterprise customers who use it to manage workflows in factories and other industrial settings, including Volvo, Siemens, Colgate-Palmolive, Michelin and Berkshire Hathaway Energy. Today, to drive business growth and further technological development, Squint announced a Series A of $13 million led by Sequoia with participation from Menlo Ventures.

B2B is its primary target, but contrary to its name, Squint has a broader focus. Its ultimate goal, says Bhushan, is to “eliminate the search bar, and eliminate all the time we spend looking for information and data.”

Bhushan first came up with the concept for the company when he was working in a very different kind of business: he was an engineering manager at Splunk, where he helped conceive and build Splunk AR, a way for users to use tools. in data analytics company. to map that data directly to physical machines to better understand how they work in real time.

The idea is to expand Splunk’s addressable customer base to more non-technical users.

“People really loved it, but they didn’t have a lot of use cases just for Splunk data visualization,” he recalls. However, he saw that customers were trying to use the AR tool for other types of workflows, which were outside of what Splunk handled on the data side and which rattled Bhushan’s business antennae. “We’re on to something with this concept,” he said he thought to himself. “I think we can bring AR to the masses. There’s an opening.”

Bhushan left Splunk in 2021 to pursue this idea in founding Squint. He said that while working at Splunk made him think about the bigger problem, Squint’s goals, and the route to achieving them, are very different.

“With Splunk we never solved the problem of allowing data and information from anywhere to come in and we also never solved the problem of authoring (because you only allow your device to be scanned and see metrics),” he said. “At Squint we are innovating both on the object analysis side and also on the content creation.” For example, computer vision and object analysis are used to create videos with AR methods, he added.

“We also wrote it completely from scratch, mostly using our time at Splunk as a learning experience.”

There are a number of ways that are already on the market to provide assistance to those who work in industrial or other manual roles. If a business already equips workers with handsets or tablets, they can have apps pre-loaded on them, or they can place QR codes on the machines themselves. The more common method is very analogue: manuals with instructions and registration logs when people need to prove their work.

The advantage of Squint’s solution, says Bhushan, is that it is more dynamic and specific: a business can easily create workflows and tie them to specific actions to be performed by users, and to specific parts of engine system. System AI consists not only of computer vision for recognizing objects, but also around the workflows that a person can go through and the generative AI that powers the ability to ask questions. and get answers from the platform.

Bhushan’s first stop as a founder was to do a stint in the company’s incubation at Menlo Ventures, as part of its product Menlo Labs: his connection was Tim Tully, a partner in the company who became the CTO of Splunk so worked hard with Bhushan there.

Squint in turn got to know the Sequoia team when it was in a cohort of Arc, Sequoia VC’s early-stage program for finding and mentoring outlier startups. (Menlo and Sequoia are both previous investors as a result.)

But Bhushan goes back further with Jess Lee, the Sequoia partner who helps run Arc: the two joined Yahoo nearly a decade ago. He described the first time he saw Devin demonstrate how the Squint worked as a “moment of intuitive magic,” similar to what he said he felt the first time he saw an AirTag, he said.

Lee believes the time is ripe for creating the next generation of tools to help skilled workers do their jobs better. “When you’re put in a new job, you can find the person on the floor who can tell you what to do, or you can go to a storage room to find a binder, or you can wing it. Or, you can pick up your phone and that will help you figure it out,” he said.

Whether it’s for stock taking, machine maintenance, or something else, the key is that Squint heralds how technology will eventually permeate the offline world beyond knowledge workers. In these situations, “nobody thinks about whether they’re using AI or AR,” he added.

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