Experience the Future of Chemical Detection with Groundbreaking rtCRD Spectroscopy
At SpectraCann, we believe quantum physics and AI have the power to revolutionize the field of drug and chemical detection.
SpectraCann is pioneering the development of the world’s first drug breathalyzer powered by our patented Runtime Cavity Ringdown (rtCRD) Spectroscopy Breath Analysis.
This advanced technology detects a range of distinct chemicals, including drugs, toxic substances, chemicals and metabolites in human breath in seconds. The technology enables rapid and precise molecular-level detection, offering unmatched accuracy and speed from a single sample. With infinite potential use cases, SpectraCann is setting a new standard in rapid chemical detection, offering transformative solutions for a wide array of applications.
Rapid Runtime Cavity Ringdown Spectroscopy (rtCRD)
SpectraCann’s advanced breathalyzer uses novel Rapid Runtime Cavity Ringdown Spectroscopy (rtCRD) to detect volatile organic compounds (VOCs) in breath samples with exceptional accuracy and unmatched speed. The process begins as a breath sample is introduced into an optical chamber, where it is analyzed by a sequence of laser pulses. Inside the optical chamber, the breath sample interacts with the laser, allowing the light to reflect thousands of times and thus significantly amplifying sensitivity of detecting VOCs.
SpectraCann is leading the way in human breath analysis using rtCRD, achieving levels of sensitivity previously unattainable in the industry.
The SpectraCann device is designed for swift and precise analysis, detecting compounds up to parts-per-trillion concentrations. These highly sensitive measurements are enhanced with machine learning algorithms to identify biomarkers linked to specific drug metabolites in human breath.
AI and Machine Learning
SpectraCann is transforming drug detection with AI and machine learning (ML) at the core of its THC breathalyzer technology. Traditional methods can be slow and error-prone, but SpectraCann’s AI-driven devices offer real-time, precise detection, while ML continuously enhances sensitivity to detect even trace amounts of THC.
The algorithm adapts to real-world data, refining itself based on usage patterns, environmental factors, and user profiles, making it more personalized and accurate over time. This personalized focus ensures fewer false positives, greater reliability, and a quicker, less invasive testing experience for law enforcement, workplace testing, and consumers, setting a new standard in drug detection.