Rewire AI provides artificial intelligence solutions for biomedical image analysis through its Polygon AI platform. This software automates the detection and quantification of cells, fluorescent probes, and other targets in micrographs. The company also offers Sightologist.ai for AI-layer integration and model development within the biotech and digital health sectors.
Funding
$2.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Analyzing biomedical images from microscopy sources to detect and quantify biomarkers is a time-consuming and often manual process. This can lead to inconsistencies in data quality and slow down the pace of research and development in biomedical fields.
Solution
Rewire AI offers two primary solutions: Polygon AI for researchers and scientists, and Sightologist.ai for biotech and digital health companies. Polygon AI is a desktop interface that automates the detection and quantification of cells, fluorescent probes, and other targets in biomedical images using machine learning. Sightologist.ai provides AI-layer integration, licensing, and model development services, enabling businesses to integrate advanced AI capabilities into their products and workflows. Both solutions improve data quality through standardized and automated quantification, accelerate analysis, and facilitate the discovery of complex interactions within tissue samples. The platform supports multiple fluorescent channels and identifies stain co-localization, enabling researchers to determine how multiple proteins or targets interact and change under different experimental conditions.
Target Audience
The primary target audience includes researchers and scientists in biomedical fields, as well as companies in the biotech and digital health space seeking to enhance their image analysis capabilities.
Features
- Automated region of interest (ROI) detection for cell counting and quantification
- Machine learning models that improve with use for reliable and replicable results
- Compatibility with confocal, brightfield, and compound microscope image formats
- Multi-channel analysis for identifying stain co-localization
- Customizable target detection with user oversight for refinement
- Easy data export to .csv format for integration with Excel and statistical packages
- Cloud-based AI engine (Sightologist.ai) for discovering complex tissue interactions