Elio transforms microscopy by integrating adaptive optics with artificial intelligence to create a real-time interface for biological study. The platform enables researchers to generate dynamic and intelligent insights directly from biological samples. This approach allows for label-free analysis, redefining how biological observation and interpretation are performed in the lab.
Funding
Funding not disclosed
Founders
Product
Problem
Conventional microscopy relies on fixed imaging snapshots and fluorescent labels, which limit the ability to observe dynamic biological processes in real time and add cost, preparation time, and potential perturbation to samples. Researchers often face bottlenecks when scaling high‑content assays across diverse model systems such as 2D cultures, 3D organoids, and thick tissues.
Solution
Elio delivers a unified platform that couples adaptive optics with AI‑driven interpretation to create a closed‑loop imaging system. The optical hardware actively shapes illumination based on real‑time feedback, while machine‑learning models extract quantitative phenotypes directly from label‑free samples. This approach enables continuous monitoring of cellular morphology, behavior, and interactions without the need for exogenous dyes. The platform integrates with both bench‑top microscopes and automated workflows, delivering rapid, high‑content data that can be fed directly into downstream analysis pipelines. By providing virtual labeling and holistic phenotyping, Elio accelerates discovery across drug screening, cell profiling, and tissue‑level studies.
Target Audience
Primary customers are academic and industry life‑science laboratories, pharmaceutical R&D teams, and biotech companies conducting high‑throughput screening, cell profiling, and tissue‑level phenotypic assays.
Features
- Diffractive adaptive optics that modulate light in response to sample feedback, enabling dynamic illumination patterns
- AI‑guided data interpretation pipeline that generates feature‑level insights from label‑free images
- Real‑time closed‑loop control linking optical modulation to machine‑learning outputs for continuous experiment adaptation
- Virtual labeling capability that produces fluorescence‑like contrast without physical dyes
- Holistic phenotyping suite capturing morphology, dynamics, and cell‑cell interactions across 2D cultures, 3D organoids, and thick tissue sections
- High‑content imaging workflow optimized for both manual bench‑top use and fully automated lab robotics
- Modular software APIs for integration with existing data management and analysis platforms