In the rapidly evolving landscape of India's manufacturing sector, a critical environmental concern looms large: the significant contribution of industries such as steel, cement, and chemicals to greenhouse gas (GHG) emissions.
As one of the world's leading GHG emitters, India faces a pressing challenge, with the power sector alone accounting for 37% of its emissions, followed by agriculture, manufacturing, and transportation. This scenario underscores an urgent need for innovative solutions that can reshape manufacturing practices, making them more sustainable and environmentally friendly.
The challenge is not just about reducing emissions but doing so in a way that aligns with the global business priority of sustainability. This priority is driven by growing environmental awareness, increasing consumer demand for sustainable practices, and the tightening grip of regulatory pressures.
Traditional manufacturing processes, heavily reliant on fossil fuels and inefficient technologies, contribute significantly to the carbon footprint, exacerbating the climate crisis.
The manufacturing sector's struggle to balance economic growth with environmental responsibility highlights the necessity for a paradigm shift towards more sustainable practices.
The integration of advanced technologies like artificial intelligence (AI) in manufacturing processes presents a promising avenue to address these challenges, offering a path to reduce emissions and enhance sustainability in a sector crucial for economic growth.
Who are the founders?
Dr. Soudip Roy Chowdhury is the Founder and Chief Executive Officer of Eugenie.ai. His journey, marked by a personal battle with autoimmune hepatitis due to industrial emissions, led him to pivot from a successful career to higher studies in machine learning.
What Eugenie.ai offers?
Founded in 2018, Eugenie.ai is a California- and Mumbai-based startup that offers a Software as a Service (SaaS)-based platform to help major asset-heavy manufacturers minimize Scope I emissions, which are direct GHG emissions from owned or controlled sources.
The platform leverages AI-driven digital twins to provide real-time tracking of machine performance and emissions data.
This technology enables precise measurement and attribution of emissions to individual machines and processes, allowing for the detection of operational anomalies. The platform empowers CXOs and operations engineers to swiftly implement corrective actions and optimize production processes for reduced GHG emissions.
Eugenie.ai's clientele includes firms in the ferrous, non-ferrous, petrochemical, food and beverage, and cement sectors.
Funding & Investors
Eugenie.ai has raised a total investment of $4.4 million from Fractal AI through a SAFE (Simple Agreement for Future Equity) instrument. The company is planning to raise its next round of funding to expand in the US, Latin America, and MEA markets.
Eugenie.ai operates on a monthly subscription model, tailored to each customer’s process line. The startup provides a comprehensive approach to emissions tracking, including emissions measurement, benchmarking, and actionable recommendations.
This single-point solution differentiates Eugenie.ai from competitors that offer fragmented aspects of emissions tracking and management. The startup is strategically expanding its growth through collaborative sales with key partners like Azure, Google Cloud, HP Enterprise, and consulting firms like EY.
Impact and Growth Plans
Eugenie.ai aims to help manufacturers reduce harmful emissions significantly, equating to removing 40 million cars off the roads annually. The startup is focusing on expanding its team and enhancing its sales strategies to meet the growing demand for industrial decarbonization solutions.
With a vision to combat climate change and protect future generations, Eugenie.ai is set to play a crucial role in the environmental intelligence platform market, which is expected to surpass $3.28 billion by 2035.
The current landscape of the global emission monitoring system market
The global emission monitoring system market, valued at approximately $4.78 billion in 2022, is witnessing a significant growth trajectory. The market is projected to expand at a robust compound annual growth rate (CAGR) of 8.33% through 2028.
The growth is largely fueled by a heightened global awareness of environmental issues, including air and water pollution, climate change, and their impact on public health. This awareness is driving industries across the globe to adopt more proactive measures in monitoring and mitigating their environmental footprint.
Additionally, the market's expansion is being propelled by the increasing stringency of environmental regulations enforced by governments and regulatory bodies worldwide.
These regulations are focused on limiting the release of pollutants into the air, water, and soil, thereby necessitating the adoption of advanced emission monitoring systems by industries to ensure compliance.
Another significant factor contributing to the market's growth is the rapid advancement in technology, particularly the integration of the Internet of Things (IoT) in emission monitoring solutions.
The technological evolution is replacing traditional monitoring systems with smart, connected devices that offer real-time data collection, analysis, and reporting. IoT-enabled sensors and devices are enhancing the automation and accuracy of emission monitoring, allowing industries to optimize their processes while adhering to environmental regulations.
The integration of IoT in emission monitoring systems is enabling remote monitoring and control, which reduces the need for on-site inspections and manual data collection. This not only enhances the efficiency of monitoring processes but also helps in minimizing operational costs for businesses.
Moreover, the continuous development of sensor technologies, data analytics, and communication protocols is leading to more sophisticated and reliable emission monitoring solutions.
The advancements are benefiting not just large industrial facilities but are also making emission monitoring more accessible to smaller enterprises, contributing to the widespread adoption of such systems across various industries.
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