
Pleno
Autonomous system for robots.
Date | Investors | Amount | Round |
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- | investor investor investor | €0.0 | round |
investor | €0.0 | round | |
investor investor | €0.0 | round | |
* | N/A | Acquisition | |
Total Funding | 000k |





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PLENO is a startup that revolutionizes the carbon credit certification process by automating data collection, reporting, and verification. The company operates in the carbon markets, serving clients such as carbon project developers, carbon auditors, and carbon registries. These clients are involved in creating, auditing, and managing carbon credits, which are used to offset carbon emissions.
PLENO's platform significantly reduces the time and cost associated with the carbon credit certification process. Traditionally, this process could take up to 24 months and cost as much as $20,000. With PLENO's automated solutions, the same process can be completed in as little as 2 hours, with costs reduced by up to 80%. This is achieved through the use of machine learning and third-party data providers to enhance the accuracy of carbon quantification, real-time monitoring, and one-click reporting.
The business model of PLENO is based on providing a digital solution that automates the entire carbon credit creation process. This includes measuring and monitoring carbon emissions, generating reports, and verifying data. The platform stores carbon project data securely and transparently on a blockchain, ensuring that the information is tamper-proof and easily accessible for verification purposes.
PLENO makes money by offering its platform as a service to its clients. By automating the certification process, PLENO helps its clients save time and money, while also improving the accuracy of their carbon emission calculations. This value proposition makes PLENO an attractive option for businesses looking to streamline their carbon credit operations.
In summary, PLENO is a game-changer in the carbon markets, providing an automated, cost-effective, and accurate solution for carbon credit certification.
Keywords: carbon credits, automation, data collection, reporting, verification, machine learning, blockchain, cost reduction, time-saving, accuracy.