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About Pollen Sense

Building the measurement layer for intelligent air.

Pollen Sense combines optics, AI, embedded systems, and environmental science to make airborne particles visible in real time. Our team is turning that measurement capability into infrastructure for health, research, operations, and public awareness.

Microscopic airborne particles

Our Focus

A company built around field-ready particle intelligence.

AI particle identification
APS400 sensor platform
24/7 environmental monitoring

Our Team

Deep tech experience, grounded in practical deployment.

Our team spans AI, environmental science, operations, commercialization, customer success, and clinical expertise. The group is built to move between lab-grade science and field-ready products.

Kris Klein

Chief Executive Officer

Kris Klein

Deep tech commercialization, B2B sales, startup scaling, and strategic partnerships.

Nathan Allan

Chief Technology Officer, Founder

Nathan Allan

Machine learning systems, architectural design, technical strategy, and team leadership.

David B. Noel

Chief Operating Officer

David B. Noel

Angel investor and co-founder, mechanical and manufacturing engineering, and Lean Six Sigma execution.

Alton Campbell

Aerobiologist

Alton Campbell

Aerobiology, data quality, and pollen identification, supporting real-time aerosolized particulate counts.

Sheena Calansingin

Customer Success Specialist

Sheena Calansingin

Customer onboarding, client relationships, and operational support for Pollen Sense's global network.

Sagun Kayastha

Research Scientist

Sagun Kayastha

Machine learning for atmospheric science, pollen forecasting, and physical AI systems built on sensor observations.

Praveen Buddiga

Medical Doctor, Founder

Praveen Buddiga

Allergy and immunology specialist, asthma expert, and patient-centered care advocate.

Measure the real world

We build hardware and data systems around direct particle observation, not broad regional estimates.

Turn science into infrastructure

Our work connects optics, machine learning, aerobiology, and cloud systems into practical tools teams can use.

Make air data actionable

The goal is not just more data. It is faster decisions for patients, cities, researchers, and facilities.