Keylabs.ai Enhances Annotation Workflow with RoboFlow Integration and Custom YOLO Models

[New York City NY] - [09.04.2025] - Keylabs.ai, a leading annotation platform, continues to push the boundaries of AI-powered labeling. Сompany announces integrations with RoboFlow and custom YOLO models for assisted annotations, enhancing automation and efficiency in computer vision projects.

These advancements make Keylabs.ai an even more powerful and performance-oriented platform. They enable users to accelerate the data annotation process significantly and allow for faster AI development, testing, and deployment.

Key Features of New Updates:

Initial Integration with RoboFlow
Users can launch a local RoboFlow node and use a basic wrapper interface over the SDK for inference, allowing you to run models directly on this node.

What does this mean?
- Fast Model Inference: This allows models to be tested directly within Keylabs.ai, speeding up the development cycle and improving the quality of annotations.
- Flexibility in Using Models: Users can use pre-trained models or adapt to specific tasks, such as preprocessing images before annotation.
- Workflow Optimization: A single environment scope can be used for ML-assisted tasks. This reduces the risk of data vulnerability, enhances security, and cuts down on time spent switching between tools.

Integration of Custom Yolo Models for Assisted Annotation
Added the ability to use Yolo models trained by customers and uploaded to RoboFlow for automatic object detection directly in the annotation editor. Users can now connect their custom models and receive preliminary annotations. Predicted objects can be quickly edited or confirmed manually.

What does this mean?
- Assistive Object Recognition: Significantly speeds up annotation, especially with large datasets.
- Flexibility in Custom Models: Especially useful for highly specialized tasks requiring precise annotations.
- Time Savings: Users can now edit or confirm automatically generated annotations, reducing labor costs and increasing productivity.
- Support for Complex Scenarios: Integrating custom models allows easy adaptation of annotations for various industries - from autonomous driving to medical imaging.

Michael Seldin, CTO of Keylabs.ai, shared his vision for these updates: "We are significantly enhancing the flexibility and efficiency of our annotation platform. These advancements empower our users to streamline their workflows, accelerate the annotation process, and ultimately deploy AI models faster and more accurately. At Keylabs.ai, we are committed to providing cutting-edge solutions that address the evolving needs of the computer vision and AI industries."

Teams interested in taking advantage of Keylabs' new annotation tools can request a demo (https://keylabs.ai/) to explore the new ML-powered annotation features.

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For media inquiries, please contact:
Olena Butenko
PR manager
Keylabs.ai/Keymakr
olena.butenko@keymakr.com

About Keylabs.ai:
Keylabs.ai image and video annotation platform have been built by data labelling experts to deliver high-performance data annotation and management features as well as unique operations management. Its tools have a track record of handling large datasets without compromising on efficiency or accuracy. Trusted by global technology leaders, Keylabs combines cutting-edge technology with user-focused design to deliver solutions to projects of any type and size.

This release was published on openPR.