Case Studies Sylvera brings transparency to the carbon-offset market with AI

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	Sylvera brings transparency to the carbon-offset market with AI

Sylvera brings transparency to the carbon-offset market with AI

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics Application Infrastructure & Middleware - Data Visualization
Applicable Functions	Business Operation Quality Assurance
Services	Data Science Services System Integration
Challenge	Taking on the gargantuan task of assessing carbon sinks, Sylvera needed to accurately verify the performance of the projects they rate. This required precise tracking of land use and its evolution over time, particularly focusing on mangroves, which are crucial for absorbing more carbon than regular tropical forests. Sylvera knew that bringing in students and interns was one option to get the job done, but the company also knew how much additional interviewing, hiring, onboarding, training, and management that approach would take. Read More
About Customer	Before launching Sylvera in 2020, COO and Cofounder Samuel Gill worked at a U.S. law firm and saw how complicated carbon-offsetting projects could be, and how difficult it can be to get up-to-date data on the climate impacts they promised. To address this issue, Gill partnered with CEO and Cofounder Dr. Allister Furey, a machine learning expert, to establish Sylvera. The startup ranks carbon projects, bringing a new layer of transparency to this market by assigning ratings to projects. Companies wanting to purchase offsets to lower their carbon footprints can access rankings and monitoring services via Sylvera’s web app to choose the right project for them and track projects’ performance over time. Read More
Solution	As Bonnefond and her team started searching for solutions, they discovered that many annotation platforms were built for autonomous vehicles. They needed a platform that could overlay Google Maps and shift between different satellite images, including high-resolution imagery from Google Earth. CloudFactory annotators, specifically trained to handle these types of geospatial tasks, were chosen for the job. CloudFactory was also able to integrate Azavea’s GroundWork tool to meet Sylvera’s labeling requirements. The CloudFactory team uses images provided by Sylvera to form annotation data that explains exactly where mangroves sit. The goal is to ultimately train a deep learning model to help them track losses and gains in mangroves over time. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Application Infrastructure & Middleware - Data Visualization

Applicable Functions

Business Operation

Quality Assurance

Services

Data Science Services

System Integration

Challenge

Taking on the gargantuan task of assessing carbon sinks, Sylvera needed to accurately verify the performance of the projects they rate. This required precise tracking of land use and its evolution over time, particularly focusing on mangroves, which are crucial for absorbing more carbon than regular tropical forests. Sylvera knew that bringing in students and interns was one option to get the job done, but the company also knew how much additional interviewing, hiring, onboarding, training, and management that approach would take.

About Customer

Before launching Sylvera in 2020, COO and Cofounder Samuel Gill worked at a U.S. law firm and saw how complicated carbon-offsetting projects could be, and how difficult it can be to get up-to-date data on the climate impacts they promised. To address this issue, Gill partnered with CEO and Cofounder Dr. Allister Furey, a machine learning expert, to establish Sylvera. The startup ranks carbon projects, bringing a new layer of transparency to this market by assigning ratings to projects. Companies wanting to purchase offsets to lower their carbon footprints can access rankings and monitoring services via Sylvera’s web app to choose the right project for them and track projects’ performance over time.

Solution

As Bonnefond and her team started searching for solutions, they discovered that many annotation platforms were built for autonomous vehicles. They needed a platform that could overlay Google Maps and shift between different satellite images, including high-resolution imagery from Google Earth. CloudFactory annotators, specifically trained to handle these types of geospatial tasks, were chosen for the job. CloudFactory was also able to integrate Azavea’s GroundWork tool to meet Sylvera’s labeling requirements. The CloudFactory team uses images provided by Sylvera to form annotation data that explains exactly where mangroves sit. The goal is to ultimately train a deep learning model to help them track losses and gains in mangroves over time.

Impact #1	In just two months, CloudFactory and Sylvera have worked together to annotate an area that’s nearly 25 times larger than London.
Impact #2	The entire process has gone smoothly, with clear communication and check-ins along the way.
Impact #3	Bonnefond has been building models out of the mangroves classification, and they are performing exceptionally well, sometimes even better than the ground truth itself.

Impact #1

In just two months, CloudFactory and Sylvera have worked together to annotate an area that’s nearly 25 times larger than London.

Impact #2

The entire process has gone smoothly, with clear communication and check-ins along the way.

Impact #3

Bonnefond has been building models out of the mangroves classification, and they are performing exceptionally well, sometimes even better than the ground truth itself.

Benefit #1	15,000 square miles of annotation completed.
Benefit #2	500 hours saved.

Benefit #1

15,000 square miles of annotation completed.

Benefit #2

500 hours saved.

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Overview

Sylvera brings transparency to the carbon-offset market with AI

Operational Impact

Quantitative Benefit