Monday, July 22, 2024
HomeFunding Singapore-Based Bags Undisclosed Amount in Seed Round Funding

[FUNDING NEWS] Singapore-Based Bags Undisclosed Amount in Seed Round Funding has announced the closure of an oversubscribed seed investment round. The firm employs artificial intelligence (AI) to construct sophisticated climate models for deciding the issuing of carbon credits.

This round was led by Silverstrand Capital. Ascend Network, DMV Investments, Orvel Ventures, and Timbul Ventures were also involved.The funding’s conditions are yet unknown.

Read also- Israel-Based Meitav Secures $100 Million in Funding was founded by Lawrence Xiao, the CEO, and Johann Wah, the President. It records forest carbon, examines additionality, baseline, leakage, and permanence data, and delves deeply into geolocation data. With the use of this data, investors and developers of carbon projects can create nature-based initiatives that help them achieve net zero.

“Most machine learning solutions in the market use locally based compute, which limits the model’s ability to scale, or they run very inefficiently on the cloud due to nonoptimal cloud architectures,” co-founder Wah told e27.Our proprietary geospatial machine learning infrastructure automatically configures optimal resources to ensure your model is scalable and built efficiently. This significantly increases the time it takes to complete and improves cost structures,” he explained.

Beyond carbon, Nika eco intends to utilise the funds to introduce its geospatial infrastructure technology as a stand-alone software as a service (SaaS) offering. This move could reduce expenses and technological obstacles to the development of various kinds of climate models.

Read also- India-Based Felicity Games Secures $700K in Pre-Seed Round Funding asserts that top financial institutions, such as Carbon Growth Partners and significant European banks, employ its audit-grade models. The model’s output can also be set up such that forestry assets can be made profitable through carbon credits during the auditing process.

“Traditional carbon models usually take anywhere from six to eight months to train and build by industry standard. Our infrastructure has been able to support customers to reduce the time to within a month,” Wah added.“Our vision is to redesign the geospatial and climate modelling space by making powerful geospatial machine learning infrastructure easy to use and accessible to all, starting in the carbon markets,” Wah noted.

Julianto Johanes, the Impact Investment Manager at Silverstrand Capital, has joined’s board, and Patti Chu, the Head of Impact Investments, has joined as a Strategic Advisor as part of this funding round.

About is a climate-tech startup. Our principal method of de-risking investment decisions is through the creation of very accurate carbon issuance estimates using our patented AI models, for which we specialise in providing technical services.

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