Standardized Observation. Expert Verification.
POLLi does not guess. We provide a governed framework for documenting, classifying, and auditing vegetation exactly as it appears in high-resolution imagery.
We have replaced 'black box' predictions with an evidence chain. Rather than asking an algorithm to predict future risk, we use technology to accelerate the review of current conditions. Our system highlights visual signals—which we call 'Findings'—that are then verified by Subject Matter Experts (SMEs) to create a defensible record of the land.
Our Approach to Data Integrity
Predictive models in natural landscapes are often unreliable due to seasonal variability and environmental shifts. POLLi prioritizes optical integrity. Every classification in our system is linked to a source image, ensuring that your records are based on verifiable evidence, not mathematical projections.
Why We Don't Predict
Vegetation management fails when data is fragmented. POLLi creates a continuous Digital Thread—linking raw imagery to expert decisions and delivering them as standardized evidence.
Building the Digital Thread
Standardized Collection
We establish requirements-driven imagery standards. By capturing data at 0.25 cm GSD,
we ensure every finding is backed by
optical truth that is comparable across
seasons and sensors.
Governed Review (Triage)
Our system triages high-priority signals, allowing Subject Matter Experts (SMEs) to validate findings. This "Human-in-the-Loop" approach ensures that every record is expert-led
and audit-ready.
Evidence Pack Delivery
The final output is a standardized, GIS-ready Evidence Pack. Every data point contains a direct link back to the source image, providing a traceable record for your Enterprise GIS
or Asset Management systems.
POLLi provides organizations with the tools needed to supercharge data collection and analysis. We remove barriers, letting you focus on making the most informed decisions, increasing your team’s effectiveness.
POLLi helps individuals and organizations across North America identify and inventory Common Milkweed for Monarch Butterfly conservation and provides detailed reports for monitoring protocols.
Common Milkweed Identification
Characterizing each pixel in an image of a right-of-way, a solar production site, CRP or broad acre wildlife habitat into nine separate categories can be done quickly and accurately using POLLi’s Habitat Index tool.
Habitat Index
New Algorithms and Applications
We've only scratched the surface of what POLLi can do to assist with object detection and characterization. There is much more to do. Explore further how you can leverage the economic convenience of object detection for various applications.
Our mission is to make field data collection fast, easy, and robust. We want to put drones and artificial intelligence in your organization’s toolbox.
The same images can be exposed to multiple algorithms using the same GSD, reducing your cost to collect and monitor your areas of interest.
POLLi maximizes drone imagery benefits with standardized GSD and data types, simplifying data collection and analysis. It ensures uniform data parameters for RGB, multispectral, hyperspectral, satellite, thermal, etc., fostering consistency and integration across data types, land types, and uses.
POLLi facilitates collaboration by easily using standardized imagery data and insights, reducing redundancy. This interoperability empowers users to apply advanced analytics and machine learning to diverse datasets. This synergy between standardized data and advanced analytics enhances decision-making, fosters better choices, and deepens our understanding of complex challenges, thanks to POLLi's innovative capabilities.
Same Data, Different Uses
We are working with other custom analytics developers to host their technology when it makes sense. If you think this is an opportunity worth exploring, please contact us. Or, if you have performed research and need to get it over the finish line, there may be a way we can work together to make your solutions come to life for others to employ.
Bring your own analytics
