Csequester

Csequester

Csequester

Carbon Markets, Tech driven, Early-stage

Carbon Markets, Tech driven, Early-stage

Carbon Markets, Tech driven, Early-stage

screenshot of csequester
screenshot of csequester
screenshot of csequester

Overview

Overview

Csequester is an early stage startup that democratizes access to the carbon market for small and medium landowners.

Csequester is an early stage startup that democratizes access to the carbon market for small and medium landowners.

Csequester is an early stage startup that democratizes access to the carbon market for small and medium landowners.

(currently under an NDA, I'm allowed to share only parts of some explorations we've been doing over the past months)

(currently under an NDA, I'm allowed to share only parts of some explorations we've been doing over the past months)

(currently under an NDA, I'm allowed to share only parts of some explorations we've been doing over the past months)

Tools Used

Figma

Design Tool

Framer

Web Tool

Notion

Documentation

Miro

Design workshops/sprints

Tools Used

Figma

Design Tool

Framer

Web Tool

Notion

Documentation

Miro

Design workshops/sprints

Tools Used

Figma

Design Tool

Framer

Web Tool

Notion

Documentation

Miro

Design workshops/sprints

Tools Used

Figma

Design Tool

Framer

Web Tool

Notion

Documentation

Miro

Design workshops/sprints

Created

Created

2024

Two iPhones displaying an a book-tracking app
Two iPhones displaying an a book-tracking app
Two iPhones displaying an a book-tracking app
Two iPhones displaying an a book-tracking app

Process

Process

Technology

Utilizing satellite imagery, drone and ground-based LiDAR, along with rigorous soil and water sampling, the project aims to create a comprehensive ecological database. This data will support the development of sophisticated machine learning models to predict and analyze ecological transformations necessary for the restoration and preservation of these zones.


Aimed Outcome

By automating the verification process of environmental assets such as biodiversity restoration and carbon sequestration, the project lowers barriers to entry, allowing these landowners to validate their contributions to carbon storage and participate in carbon trading. This model not only fosters environmental sustainability but also offers economic incentives for community involvement in ecological conservation efforts, making a significant impact on global climate regulation and local livelihoods.















Technology

Utilizing satellite imagery, drone and ground-based LiDAR, along with rigorous soil and water sampling, the project aims to create a comprehensive ecological database. This data will support the development of sophisticated machine learning models to predict and analyze ecological transformations necessary for the restoration and preservation of these zones.


Aimed Outcome

By automating the verification process of environmental assets such as biodiversity restoration and carbon sequestration, the project lowers barriers to entry, allowing these landowners to validate their contributions to carbon storage and participate in carbon trading. This model not only fosters environmental sustainability but also offers economic incentives for community involvement in ecological conservation efforts, making a significant impact on global climate regulation and local livelihoods.















Technology

Utilizing satellite imagery, drone and ground-based LiDAR, along with rigorous soil and water sampling, the project aims to create a comprehensive ecological database. This data will support the development of sophisticated machine learning models to predict and analyze ecological transformations necessary for the restoration and preservation of these zones.


Aimed Outcome

By automating the verification process of environmental assets such as biodiversity restoration and carbon sequestration, the project lowers barriers to entry, allowing these landowners to validate their contributions to carbon storage and participate in carbon trading. This model not only fosters environmental sustainability but also offers economic incentives for community involvement in ecological conservation efforts, making a significant impact on global climate regulation and local livelihoods.















Technology

Utilizing satellite imagery, drone and ground-based LiDAR, along with rigorous soil and water sampling, the project aims to create a comprehensive ecological database. This data will support the development of sophisticated machine learning models to predict and analyze ecological transformations necessary for the restoration and preservation of these zones.


Aimed Outcome

By automating the verification process of environmental assets such as biodiversity restoration and carbon sequestration, the project lowers barriers to entry, allowing these landowners to validate their contributions to carbon storage and participate in carbon trading. This model not only fosters environmental sustainability but also offers economic incentives for community involvement in ecological conservation efforts, making a significant impact on global climate regulation and local livelihoods.















Next Project

Next Project

Next Project

Loop

Loop

Loop

->

->

->

Nitin Surendran © 2024

Nitin Surendran © 2024

Nitin Surendran © 2024