Frekil is an end-to-end platform for procuring and annotating medical imaging datasets—including X-rays, CT scans, MRIs, and more—designed to accelerate and improve the quality of data preparation with AI assistance. Frekil serves AI startups, hospitals, and life sciences companies by streamlining dataset acquisition, annotation, and quality control, helping organizations reduce costs, ensure data quality, and de-risk their path to regulatory approvals such as FDA clearance.
How does Frekil's platform work?
Frekil provides a web-based suite for both 2D and 3D medical image annotation, supporting tasks like segmentation, point and polygon labeling, lesion measurement, and advanced visualization. The platform accommodates a range of imaging modalities, including X-ray, CT, MRI, ultrasound, and histopathology. Users benefit from:
- Exclusive radiology partnerships for access to premium datasets
- A benchmarked annotator marketplace enabling high-quality labeling at scale
- Secure data handling via pre-signed URLs
- Flexible project creation and user role management
- Powerful AI-assisted annotation tools, such as zero-shot segmentation, 3D brush and eraser, grow/cut, thresholding, and slice interpolation
- Quality control workflows featuring consensus checks
- Export and versioning capabilities for annotated datasets
These features enable teams to annotate medical images up to 10x faster than traditional manual approaches, while maintaining high standards for data integrity and compliance.
Who uses Frekil?
Frekil primarily targets organizations that require high-quality, annotated medical imaging data to build and validate AI models or to support clinical research. Typical users include:
- AI startups focused on healthcare and medical imaging
- Hospitals and radiology departments
- Life sciences and pharmaceutical companies developing diagnostic or therapeutic solutions
By offering a scalable, secure, and efficient workflow, Frekil helps these organizations accelerate product development and regulatory submissions.
What sets Frekil apart?
Frekil differentiates itself by combining exclusive access to premium medical imaging datasets with a robust suite of AI-driven annotation tools and quality controls. Its marketplace approach for annotators, advanced automation features (like zero-shot segmentation), and support for a wide variety of imaging types make it a comprehensive solution for teams dealing with complex healthcare data challenges. The platform is designed to reduce the bottlenecks in healthcare AI data sourcing and preparation, an area highlighted as critical in discussions with industry leaders and investors.
Who leads Frekil?
Frekil was founded by Nikhil Tiwari (Co-founder & CEO) and Shivesh Gupta (Co-founder & CTO), both alumni of the Indian Institute of Technology Bombay. Their technical backgrounds and experience in data-centric AI product development shape Frekil's focus on speed, quality, and regulatory readiness for medical imaging AI projects.
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