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Eugenie was incepted with an intent to solve two of the biggest problems the process industry faces today. First was the democratization of data-driven insights to drive complex operational decisions with a bottom-line impact. Second, to build an eco-system that leverages both human and machine intelligence to improve reliability, efficiency, and sustainability of assets as well as processes.
Eugenie's unique decision intelligence and execution platform enables enterprises to make efficient and optimal operational decisions about their assets and processes. The company addresses issues related to anomalies in operations such as unscheduled downtime detection, production quality issue detections, process-deviation detection, etc., using its descriptive, prescriptive, and predictive analytics products.
Eugenie believes in solving the unsolvable by bringing the best of AI, engineering, behavioural science, and design together in the company's products and solutions. In terms of offerings, the company has two products (Ray-Finn and Papillon) that help the IT/OT teams find better answers to the industrial operational challenges.
Eugenie is on a mission to make operations more reliable by transforming people, processes, and assets in every enterprise to become more efficient using AI, engineering, and design. The company aspires to create a world where technology plays an important role in transforming the operation industry to become more ecologically and economically sustainable. Eugenie wishes to play a pivotal role in bringing that change with the company's products and solutions.
We consider reliability as the first step towards establishing sustainable operations. Ensuring reliable operations requires handling large data streams and drawing actionable conclusions from them, which includes considerable scaling efforts to ensure a seamless data-to-decision journey. Eugenie presents complex data-driven insights in user-centric and diagnostic steps, which assist operational and maintenance staff in making quick, timely decisions. Insights also contain suggested operational procedures, consisting of past failures and subsequent actions performed. Eugenie brings traceability and transparency of insights to life, which are fundamental building blocks of its explainable AI framework.
Eugenie received the best AI innovation award from Microsoft in March 2020 for creating a business impact of more than US$2 billion for various customers in a short span. The company was featured in CIO Insider's 'Top 10 Analytics Company in India'. Eugenie has also been featured in various top-notch digital publications such as India.ai, Inside big data, Silicon angle, Gartner, and Forrester.
The accurate and relevant insights provided by Eugenie aided one of its major fortune 100 consumer packaged goods companies to transform the product marketing and distribution strategy. The CPG Corporation was facing problems in leveraging the available high-volume enterprise data, which caused considerable time loss and cost for manual analysis, and confusion. Eugenie's user-friendly root-cause analysis helped the corporation to reduce the data-to-action time drastically by more than 95% and discovered hidden, uncovered patterns in data that revealed declining product performances. Later, the global director of the CPG company acknowledged Eugenie's contribution in extracting knowledge from the data to form a new way of organizational thinking.
Eugenie's diagnostic platform proactively diagnosed operational failures in the tank farms of a major Indian Oil and Gas company that led to massive hydrocarbon losses. Eugenie's subsequent data-driven actions resulted in an economic impact of US$2 billion across 5000 tank farms. Eugenie also reduced their operational costs considerably by reducing detection-to-reaction time from several hours to few minutes.
Dr. Soudip Roy Chowdhury, the Founder and CEO of Eugenie.ai, is a passionate technology enthusiast with a doctorate from the University of Trento, Europe. Soudip is an accomplished entrepreneur and an esteemed member of the Forbes Technology Council. Being an ardent advocate of industrial sustainability, he likes to keep himself updated with various initiatives related to the burning issue of climate change. Soudip is armed with an assiduous vigour to solve complex problems using AI, Engineering, and Design. He zealously encounters various challenges in his entrepreneurial journey such as creating scalable and trustworthy products and responsible AI eco-systems.
Eugenie's unique approach towards explainable AI, backed by scalable data engineering and intuitive UI/UX makes the company stand out against other solutions in the market. Eugenie uses unsupervised, supervised, and semi-supervised genres of AI algorithms for curating insights from both stream and batch data. The company's patented AI algorithms are designed to identify both unknown-unknowns and known-unknowns anomalies from high-volume and high-velocity data with very little or no human supervision. Eugenie helps decision-makers detect anomalies that are hard to identify using traditional BI or statistical approaches. Eugenie's machine learning-driven algorithms learn about the utility and relevance of the solution's insights from users' feedback that helps the solution to continuously improves its efficacy. Further, Eugenie provides an end-to-end execution platform that helps detect anomalies along with enabling users to act on them using prescriptive analytics and past process information.
Eugenie is aiding major oil and gas companies in India and across the world to determine anomalies in their operations. The company prepares its clients for any unanticipated downtime or incident in the operations that might lead to major disasters. Simultaneously, Eugenie supports other manufacturing companies to reduce operation and maintenance costs by improving process efficiency, product quality, and throughput.
The pandemic has made many organizations rethink their digital transformation strategy and we have witnessed how the clients have fast-tracked a few of the operational transformation projects. As per Eugenie, most people within the client organizations have realized that enterprises which can operate and manage workforces remotely, would make a profit in the coming decade. Industry 4.0, IIoT, augmented reality-based operation interventions, etc., are becoming the need of the hour. Eugenie reckons that even with all the great progress in AI and IoT, the real industry adoption of such technologies is still very low – partly because AI is yet to prove great values for businesses and AI technology focuses less on explainability. Eugenie views this as an opportunity to progress the technology in a humanly interpretable and usable way and the company's choice of technology and framework are inspired by this realization.
Eugenie intends to further the research in the areas of the human-AI cooperative system, explainable AI, bringing traceability, and trust in AI algorithms. Reliability and performance are driving forces that lead users to trust an AI system. Eugenie considers technology as an ally to augment human capability, especially around complex decision-making. The company aspires to shape industrial sustainability transformation through the power of Responsible AI. Eugenie expects that the industry and academia would do some seminal works in the aforementioned areas in the future.
Eugenie's innovative approach is manifested in the form of user-centric and explainable AI, which has resulted in the congruence between humans and machine learning algorithms. The company's solution is equipped with clarity that can transform complex technical and business problems into rational insights.
Eugenie's distinctive AI-backed algorithm suite consists of SEE (Spot, Explore, and Exploit) TM framework, which can detect and diagnose operational anomalies at scale. The solution can scan through vast amounts of data comprising of IoT sensor data, audio and video streams in real-time to stitch patterns for generating actionable insights with descriptive, predictive, and prescriptive analytics for discovering operational steps.
Eugenie's strategic partners include Microsoft, SAP, AWS, Qualcomm, Intel, etc. Eugenie's partner eco-system is a strong pillar of the entrepreneurial inclination of the company. Eugenie believes in innovations with continuous learning through creative disruptions.
Eugenie understands that most of today's industrial enterprises possess the required operational data, but an essential element of utilizing digital systems involve extracting data from organizational silos and collating them in an accessible format. Further, integrating the advanced analytics systems with the legacy OT sources poses challenges in data mining, data governance, and extensive standardization.
According to Eugenie, data quality is important, but often ignored as an obstacle for digital initiatives. For developing an AI-powered diagnostic framework, industrial companies need to identify processes to manage incorrect and missing data.
Eugenie perceives climate change as the biggest challenge of today that needs urgent actions and a shared vision of industries, government, and society. Recent advancements in technology are at the forefront of the measures being taken to tackle this humongous challenge. The company is of the opinion that reducing industrial carbon footprint will demand concrete investment in AI-enabled operational technology and achieving net-zero emission is still a distant dream. However, Eugenie believes that improving asset and process efficiency can lower carbon emissions by 15-20% and optimizing industrial operations is a requirement and an obligation from the standpoint of humanity. As stated by Eugenie, the key to digital adoption includes including people, processes, and assets in building technical and operational resilience. The company is confident that it will strive to make AI the invisible force for building a better world with sustainable systems and processes.
