Enterprise

Scandit snaps up $150M at a $1B+ valuation for its computer vision-based data capture technology

Comment

Image Credits: Scandit

Consumers and businesses are forever demanding faster and easier ways to get things done, and today a startup that is building tech to make that a reality using AI and the camera on your mobile device is announcing a big round of growth funding. Scandit — which uses computer vision to scan barcodes, text, ID cards or any physical object to trigger automated responses, provide analytics and more — has raised $150 million, a Series D that values the Swiss startup at over $1 billion.

Scandit has made a name for itself with technology that can work on smartphones — meaning customers do not need to invest in more clunky and narrowly functional customized devices to tap into computer vision magic — but it also has been working on other applications of its technology, including in autonomous data capture, an area where it will also be putting some of this investment.

“We focus on enabling smart data solutions, which means any direct end user device whether it’s a smartphone or tablet, or a drone, anything that can use computer vision,” said CEO and co-founder Samuel Mueller in an interview. It also plans to use the funding to continue hiring more talent and expanding internationally.

Warburg Pincus led the round, with previous backers Atomico, Forestay Capital, G2VP, GV, Kreos, NGP Capital, Schneider Electric, Sony Innovation Fund and Swisscom Ventures all also participating. The company has now raised $300 million.

Since last raising money in 2020 — an $80 million Series C — Scandit has been on a roll. Annual recurring revenues have doubled (it doesn’t disclose actual figures). And it now has some 1,700 customers using its tech in a range of B2B and B2C services in verticals like retail, transportation and travel, manufacturing and logistics, healthcare and any use case where capturing an image of you or something else will spur another action. The list includes huge enterprises like the NHS, FedEx and L’Oréal, but also smaller apps, which are all getting up to speed with the times and how the working world works.

“There has been a sea change among enterprise customers looking at solutions like Scandit’s,” Mueller said, noting that eight out of the 10 bigger retailers in the U.S. are currently customers. “They’ve all moved away from traditional scanning equipment to embrace either smartphone-based data capture solutions, or BYO devices, because of lower costs and much more flexibility.” In retail, for example, one big driver he said has been the need for better real-time inventory data.

One other factor that may well have influenced this funding round and valuation is that Scandit’s core mechanics go beyond that of simple barcode reading. The startup is a spinout of the highly regarded computer vision department of ETH Zurich, and it currently has some 23 patents for its technology — eight granted and the rest working their way through the patent application process.

The opportunity that Scandit has identified and is addressing is one that spans all of our daily lives, whether we think about it consciously or not. As a population, many of us have grown used to things working automatically, a state of affairs made to feel ever more “natural”, more commonplace, thanks to technology that makes it so. That, in turn, is driving a faster pace of innovation to speed things up even more. Smartphones have had a massive role to play in this area, with sensors and fast data processing that authenticate us, help us look for and buy things and, of course, communicate with the world in all kinds of ways (text, audio, video) and through any number of channels, wherever we happen to be.

The cameras on these devices have been a critical component (pun intended) of the evolution. “In the blink of an eye” has become “in the click of a cameraphone.” That has opened the door for companies like Scandit to come in and make all that possible.

It could be argued that the very basics of computer vision as played out on a smartphone are commoditized these days, since even the most basic smartphones can capture QR codes and other objects with cameras in order to trigger other actions, or for image filtering and so on. Some of what Scandit is doing, though, is supercharging all of those processes. “The computer vision and machine learning we are doing is all on the edge” — that is, on the devices themselves — “so we have learned to deal with limited camera axes, low light and too-bright light, motion,” said Mueller. “Motion blur is one of the hardest. You have to be able to correct for that.”

Taking a production-centric approach to enterprisewide AI adoption

That begs the question, too, of how much Scandit has been talking to hardware and platform companies (for example, companies like Apple or Google or Microsoft, all very keen to drive deeper into enterprise use cases for its technology). Mueller declined to comment on that except to note that Scandit is one of Apple’s “approved mobility partners” and that it has go-to-market initiatives with Apple and Samsung.

For now, Scandit’s version of “smart” in smart data capture seems to be what is interesting investors, despite the fact that there are probably dozens if not more companies in the market offering their own take on image-based data capture. (They include MishiPay, Dynamsoft, Cognex, Blippar and others.)

Scandit’s smart data capture technology is transforming the way businesses operate and interact with their customers in an increasingly digital world and is strongly aligned with some of the biggest secular trends of our time, including enablement of the digital workforce and supply chain visibility,” said Flavio Porciani, MD at Warburg Pincus, in a statement. “Already used by leading enterprises across multiple industries, by customers and end users all over the world, we see a huge opportunity for Scandit to cement its position as the global leader in smart data capture. We are excited to have the opportunity to partner with the team at Scandit on the next phase of their ambitious growth strategy.’’

More TechCrunch

Intuitive Machines made history when it became the first private company to land a spacecraft on the moon, so it makes sense to adapt that tech for Mars.

Intuitive Machines wants to help NASA return samples from Mars

As Google revamps itself for the AI era, offering AI overviews within its search results, the company is introducing a new way to filter for just text-based links. With the…

Google adds ‘Web’ search filter for showing old-school text links as AI rolls out

Ilya Sutskever, OpenAI’s longtime chief scientist and one of its co-founders, has left the company. OpenAI CEO Sam Altman announced the news in a post on X Tuesday evening. “This…

Ilya Sutskever, OpenAI co-founder and longtime chief scientist, departs

Blue Origin’s New Shepard rocket will take a crew to suborbital space for the first time in nearly two years later this month, the company announced on Tuesday.  The NS-25…

Blue Origin to resume crewed New Shepard launches on May 19

This will enable developers to use the on-device model to power their own AI features.

Google is building its Gemini Nano AI model into Chrome on the desktop

It ran 110 minutes, but Google managed to reference AI a whopping 121 times during Google I/O 2024 (by its own count). CEO Sundar Pichai referenced the figure to wrap…

Google mentioned ‘AI’ 120+ times during its I/O keynote

Firebase Genkit is an open source framework that enables developers to quickly build AI into new and existing applications.

Google launches Firebase Genkit, a new open source framework for building AI-powered apps

In the coming months, Google says it will open up the Gemini Nano model to more developers.

Patreon and Grammarly are already experimenting with Gemini Nano, says Google

As part of the update, Reddit also launched a dedicated AMA tab within the web post composer.

Reddit introduces new tools for ‘Ask Me Anything,’ its Q&A feature

Here are quick hits of the biggest news from the keynote as they are announced.

Google I/O 2024: Here’s everything Google just announced

LearnLM is already powering features across Google products, including in YouTube, Google’s Gemini apps, Google Search and Google Classroom.

LearnLM is Google’s new family of AI models for education

The official launch comes almost a year after YouTube began experimenting with AI-generated quizzes on its mobile app. 

Google is bringing AI-generated quizzes to academic videos on YouTube

Around 550 employees across autonomous vehicle company Motional have been laid off, according to information taken from WARN notice filings and sources at the company.  Earlier this week, TechCrunch reported…

Motional cut about 550 employees, around 40%, in recent restructuring, sources say

The keynote kicks off at 10 a.m. PT on Tuesday and will offer glimpses into the latest versions of Android, Wear OS and Android TV.

Google I/O 2024: Watch all of the AI, Android reveals

Google Play has a new discovery feature for apps, new ways to acquire users, updates to Play Points, and other enhancements to developer-facing tools.

Google Play preps a new full-screen app discovery feature and adds more developer tools

Soon, Android users will be able to drag and drop AI-generated images directly into their Gmail, Google Messages and other apps.

Gemini on Android becomes more capable and works with Gmail, Messages, YouTube and more

Veo can capture different visual and cinematic styles, including shots of landscapes and timelapses, and make edits and adjustments to already-generated footage.

Google Veo, a serious swing at AI-generated video, debuts at Google I/O 2024

In addition to the body of the emails themselves, the feature will also be able to analyze attachments, like PDFs.

Gemini comes to Gmail to summarize, draft emails, and more

The summaries are created based on Gemini’s analysis of insights from Google Maps’ community of more than 300 million contributors.

Google is bringing Gemini capabilities to Google Maps Platform

Google says that over 100,000 developers already tried the service.

Project IDX, Google’s next-gen IDE, is now in open beta

The system effectively listens for “conversation patterns commonly associated with scams” in-real time. 

Google will use Gemini to detect scams during calls

The standard Gemma models were only available in 2 billion and 7 billion parameter versions, making this quite a step up.

Google announces Gemma 2, a 27B-parameter version of its open model, launching in June

This is a great example of a company using generative AI to open its software to more users.

Google TalkBack will use Gemini to describe images for blind people

Google’s Circle to Search feature will now be able to solve more complex problems across psychics and math word problems. 

Circle to Search is now a better homework helper

People can now search using a video they upload combined with a text query to get an AI overview of the answers they need.

Google experiments with using video to search, thanks to Gemini AI

A search results page based on generative AI as its ranking mechanism will have wide-reaching consequences for online publishers.

Google will soon start using GenAI to organize some search results pages

Google has built a custom Gemini model for search to combine real-time information, Google’s ranking, long context and multimodal features.

Google is adding more AI to its search results

At its Google I/O developer conference, Google on Tuesday announced the next generation of its Tensor Processing Units (TPU) AI chips.

Google’s next-gen TPUs promise a 4.7x performance boost

Google is upgrading Gemini, its AI-powered chatbot, with features aimed at making the experience more ambient and contextually useful.

Google’s Gemini updates: How Project Astra is powering some of I/O’s big reveals

Veo can generate few-seconds-long 1080p video clips given a text prompt.

Google’s image-generating AI gets an upgrade