For most of computer vision's history, training has been extremely challenging. Going from an idea to a deployed application meant spending weeks labeling hundreds or thousands of images by hand just to see if a concept would work.
Now the era of manual labeling is ending.
Today, we are introducing Roboflow Rapid, the fastest way to build custom vision models. Rapid is the first prompt-based model creation engine designed to take you from an idea to a deployed model without labeling data.
From prompt to deployed model in minutes
Visual artificial intelligence can help us understand the physical world—from accelerating scientific research and guiding autonomous machinery to reducing defects in manufacturing. However, the friction of getting started has always been high.
Roboflow Rapid: Going from text prompt to deployable vision model in minutes
With Rapid, you can start building a vision application with a text prompt and a handful of images or a short video. Instead of labeling images by hand, Rapid automatically finds objects based on your text input. This allows you to skip hours of manual annotation and move straight to testing and implementing your application to solve real-world problems.
Video tutorial: Build and deploy a production-ready vision application in just a few minutes using Roboflow Rapid.
"Rapid is designed for people who have a visual problem to solve and want to get straight to the solution so you can use AI to fix real-world issues, without the model building process becoming a project in itself,” said Brad Dwyer, Co-Founder and CTO for Roboflow. “During the development process, early users say Rapid has saved them months of work. They were prepared to invest time in collecting and labeling data, but Rapid allowed them to skip that step and go straight to production."
Finding all the yellow and grey caps in a video with Roboflow Rapid
Let’s look at a practical example. Suppose you want to build an application that counts vials on a production line.
In the past, creating a model to detect vials would have required a significant amount of manual labeling. Now, the process takes a just a moment:
- Go to rapid.roboflow.com.
- Upload your images or a short video.
- Enter a text prompt (e.g., “yellow cap”, “grey cap”).
- Receive a model that can find those objects immediately.
Using the Workflows AI assistant to create an app to count the yellow caps crossing a line
From there, you can integrate the model into your application without setting up your own hardware or cloud environment. Rapid is integrated into Roboflow Workflows, allowing you to create automations, such as counting the number of vials as they cross a specified line, right out of the box.
The final output: Counting the number of vials with yellow caps with the model we made in Roboflow Rapid
Orchestrating the entire vision stack
The key to Rapid’s speed is how it simplifies the complex landscape of computer vision by weaving together foundation models, few-shot learners, and custom detectors (such as RF-DETR) into a seamless pipeline to create the best model for your data.
Instead of relying on manual inputs, Rapid leverages the knowledge of the latest foundation models. This approach allows the system to detect and segment objects based entirely on natural language.
Using Roboflow Rapid to find specific objects in an industrial setting, like small specks of dust in this food processing line.
When it’s time to use your model, Roboflow manages the infrastructure to get into production. You don’t need to worry about provisioning GPUs, managing containers, administering software updates, or ensuring compatibility between libraries. Roboflow handles the entire stack, ensuring every component, from the initial prompt to the production-ready API, works together seamlessly.
"Roboflow unifies the training expertise, cloud hosting, and deployment pipeline to make vision AI easily accessible to more people. It takes months to configure an environment like this yourself; with Rapid, you have a custom, scalable endpoint in just a couple minutes." Dwyer said.
Foundation intelligence, with edge efficiency
For many production use cases, speed of deployment isn't the only factor; operational efficiency and computational cost are critical. Depending on your environment, you may need a model with a small footprint that runs efficiently on edge hardware.
Rapid handles this automatically. As soon as you save your project, it starts training a custom RF-DETR model in the background. The result is a highly efficient model, tuned to your data and ready to run anywhere.
"Our goal is to help you get the right model for your specific environment – the most efficient solution that actually solves your problem,” said Grant Nelson, Product Manager at Roboflow. “Rapid completely changes the process. You won’t spend 95% of your time labeling and training. Now, you spend 5% of your time on data, and the other 95% actually building your application and running it in production."
Want to create a vision app for the edge? Create a custom model and start testing
Roboflow Rapid: A New Paradigm in Visual Artificial Intelligence
Roboflow Rapid represents a shift in how we build vision applications. We are moving from a world where model development takes months to a world where the majority of people will never label an image.
Build a vision app today at rapid.roboflow.com.
Cite this Post
Use the following entry to cite this post in your research:
Patrick Deschere. (Dec 9, 2025). Introducing Roboflow Rapid: Text prompt to vision model in minutes. Roboflow Blog: https://blog.roboflow.com/roboflow-rapid/