Highlights:                                                      

  • The startup has developed an all-in-one visual AI platform designed to streamline the creation of computer vision models and their integration into applications.
  • The platform lets users annotate images, evaluate datasets, generate training data, and test configurations to optimize model performance.

Recently, the visual AI development startup Roboflow Inc. has secured USD 40 million in funding to further enhance the tools developers require for creating more advanced AI systems capable of perceiving and interpreting the world.

The recent Series B funding round was led by GV and included contributions from Craft Ventures, Y Combinator, and notable individuals such as Guillermo Rauch from Vercel AI Inc., Jeff Dean from Google LLC, and Amjad Masad from Replit Inc.

The startup has developed an all-in-one visual AI development platform designed to streamline the creation of computer vision models and their integration into applications. Initially launched as a tool for managing large image datasets, it has since evolved into a comprehensive solution that supports teams in transforming raw image and video data into production-ready vision AI applications. The platform offers features for dataset analysis, automated data labeling, model training, fine-tuning, deployment, and more.

Essentially, Roboflow provides developers with a guided workflow to integrate computer vision into their products. Users can begin by uploading the images or videos they want their application to interpret, select an appropriate model, and train it to perform effectively.

The platform allows users to annotate images, evaluate dataset quality, generate additional training data, and experiment with various configurations to optimize model performance. After training is complete, Roboflow streamlines the deployment of the application to the cloud, edge devices, or even a web browser. It also monitors the app’s performance over time, alerting users to any potential degradation.

In a blog post, Roboflow Co-founder and CEO Joseph Nelson highlighted various applications users have already developed using the platform. These include medical imaging tools for diagnostics, early wildfire detection systems for firefighters, and coral reef monitoring solutions. Nelson also noted that individuals can create personalized apps, such as one that monitors an RTSP feed and sends an email notification when a package is delivered to their doorstep.

“Visual AI is a platform-level shift similar in impact to the cloud and internet itself. As software eats the world, a rate limiter is the speed at which computers can understand the visual world,” Nelson said.

Roboflow harnesses AI to enable devices to understand the visual world, a mission it has pursued with remarkable success. Its open-source tools are utilized by over 25,000 companies and more than one million developers. The platform also boasts an extensive library of over 500,000 image and video datasets, comprising more than 500 million images and 150,000 pretrained computer vision models. Collectively, users have consumed over one million GPU hours on Roboflow to drive advancements in open-source computer vision.

Nelson expressed his belief that visual understanding will become a foundational capability for nearly every company, emphasizing that many enterprises already possess petabytes of underutilized visual data. “[There are] millions of cameras deployed globally, and billion-dollar startups are being built in markets that didn’t exist five years ago, thanks to computer vision,” he said.

One example is the startup Relo Metrics Inc., which leverages computer vision AI to deliver real-time ad attribution and ROI analysis during live broadcasts—something that was previously unattainable. “What previously was prohibitively uneconomic — cataloging the exact seconds a logo is aired alongside showing a scoreboard during a sports broadcast — is now possible,” he said.

Another example is Pella Corp., one of the world’s leading window and door manufacturers, which leverages Roboflow to develop computer vision models for inspecting product quality as items come off the production line.

“Maintaining an innovative edge is critical to our strategy at Pella Corporation, and advancements in AI represent an unprecedented opportunity to optimize manufacturing processes and quality controls. Roboflow has been instrumental in accelerating our learning and deployment of innovative AI solutions to achieve our goal of leading the industry in product quality and delivery for our customers,” said Pella Chief Information Officer Travis Turnball.

Roboflow stated that the funding from this round will be used to accelerate research and development, focusing on enhancing its open-source tools and growing its community. Additionally, the company plans to expand its product, engineering, and go-to-market teams.