Blog

Innovate & Elevate: Equipping Our Team for Technological Breakthroughs

      Merlin - Director, Software

In the ever-evolving landscape of technology, software stands as the driving force, reshaping the world as we know it. Artificial Intelligence (AI) has become an integral part of every enterprise application, underscoring the need for secured and scalable Enterprise Architectures in data platforms and application development. The decisionmaking process for developing enterprise solutions presents a critical juncture. Opting for a cloud-native approach offers advantages such as scalability, elasticity, and resilience, but it requires thorough consideration of the associated annual operational costs

On the other hand, choosing on-premises solutions ensures data security within the organization’s firewall,demanding meticulous management and maintenance. In response to these challenges, teams at EinNel recognize the necessity for a comprehensive understanding of business logics, data management, application development, and technology insights. The company has taken proactive steps to empower its technical team leads, architects, engineering directors, and project managers by fostering the spread of knowledge and innovation.

EinNel has adopted the following strategies in building successful enterprise applications:

•  Empower those involved in building the architecture to take the lead in decision-making, recognizing that a deep understanding of the construction process is crucial for informed choices that shape the architecture positively.
•  Emphasize the importance of clearly defining and prioritizing Quality Attribute Requirements (QARs) as they serve as guiding principles that drive successful architectural designs.
•  Encourage engineers to get familiar with the domain, specific context, and QARs of the project to make informed trade-offs on architectural decisions.
•  Promote the development of unique architectures tailored to each project’s specific context and Quality Attribute Requirements, discouraging the direct replication of designs from open sources.
•  Highlight the importance of early and continuous testing and refinement in the architectural process rather than perfecting the design.
•  Embrace the iterative nature of architecture evaluation through practical implementation and testing.

Drawing from the collective experience and brainstorming sessions in the MDOX platform development, EinNel is poised to enter 2024 with the capability to build reliable and scalable enterprise solutions. These solutions aim to align IT with business goals, optimize enterprise performance, and facilitate enterprise change management processes. EinNel’s commitment to knowledge dissemination, innovation, and a tailored approach to architecture positions it as a leader in navigating the changing landscape of enterprise architectures.

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Unlocking Leadership Excellence: The L-Edge Experience at EinNel Technologies

John Terry - Chief Operating Officer

On the 13th and 14th of October, EinNel Technologies, in collaboration with Upskill Training House, organized the transformative “L-Edge” Leadership Program for their Managers, Leads, and Directors. This initiative, recognizing the vital role of effective leadership in today’s corporate world, equipped participants with essential skills through continuous learning and practical application.

The program extended beyond traditional classroom learning, integrating physical activities that encouraged teamwork and camaraderie among participants. Facilitated by Mr. Mark Koushik, the resource person for the program, these activities proved instrumental in keeping participants actively engaged. Movie-based learning sessions provided valuable insights into leadership styles and decision-making processes, fostering a deeper understanding of effective leadership principles. EinNel Technologies’ commitment to nurturing its leaders is evident in this initiative, enhancing the skills of its workforce and propelling the organization towards greater success and innovation.

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Transformative Advances in Medical Imaging through Computer Vision

Dr.Dhatchanmoorthy - Director, EinNext Biosciences

Computer vision involves the use of algorithms and computational models to enable computers to interpret and analyze visual information. Computer vision interprets visual information by utilizing algorithms and computational models to mimic human visual perception. In healthcare, computer vision algorithms assist doctors by analyzing medical images (like X-rays, MRIs, CT scans and histology slides) enabling earlier and more accurate diagnoses. Efficient computer vision AI/MLalgorithms for digital radiology (radiomics) and pathology streamline the extraction of quantitative features from medical images, automating the identification of relevant patterns and characteristics to enhance diagnostic precision and analytical capabilities.

Computer vision in radiomics uses advanced image processing to extract quantitative features from medical images, enhancing diagnostic and predictive capabilities. The integration of computer vision in radiomics, analyzing large sets of imaging data to uncover hidden information, holds promise in enhancing disease diagnosis, personalized treatment planning, and patient outcomes. The ongoing evolution of computer vision in radiomics holds promise for enhancing diagnostic accuracy, treatment planning, and personalized healthcare through efficient and objective analysis of largescale medical imaging data.

Computer vision in digital pathology involves the application of advanced image analysis techniques to interpret and analyze pathology slides in a digital format. It enables automated detection, classification, and quantification of cellular and tissue features, aiding in more efficient and objective diagnostic processes. The integration of computer vision in digital pathology has the potential to improve accuracy, speed up workflows, and enhance the overall understanding of pathological specimens for better patient outcomes.

The impact of the latest computer vision AI/ML algorithms in the medical field is transformative, enhancing diagnostic accuracy, treatment personalization, and overall patient care. The continued growth of these technologies signals a promising future, driving advancements in medical imaging analysis, disease prediction, and the development of innovative healthcare solutions.

Engineers at EinNel technologies developing cutting-edge computer vision AI/ML algorithms exhibit strengths in advanced mathematical modeling, programming expertise, and a deep understanding of image processing, contributing to the innovation and effectiveness of their algorithms. Their interdisciplinary skills enable them to tackle complex challenges, ensuring the development of robust solutions with real-world applications for chemical/pharma and medical sciences. Currently, we are employing computer vision algorithms to develop an automated workflow for designing patient-specific implants in total knee replacement surgery, utilizing 2D X-ray images of the lower limb.

EinNel technologies is involved in an academic collaboration with students of the Neural TechGenix Club at BSA Crescent Institute, working under the supervision of Prof. Arputha Rathana.The focus is on computer vision for medical image processing, aiming to harness students’ innovative insights and provide training in developing cutting-edge algorithms for enhanced medical image analysis.

We employ latest computer AI/ML algorithms leverage advanced deep learning techniques, such as transformer architectures, to achieve state-of-the-art performance across diverse tasks like natural language processing, computer vision, and reinforcement learning. These algorithms demonstrate increased scalability, efficiency, and adaptability, pushing the boundaries of AI applications in various bioscience domains.

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Model based Engineering & Design for FCEV – Design, Analytics & Optimization in MDOX

Abdul Samath - Embedded Team

In the global initiative to establish eco- friendly environments and attain decarbonization, companies are increasingly prioritizing innovative approaches to reduce carbon emissions. The automotive sector is at the forefront of this shift as fundamental perspectives on environmentally sustainable vehicles are undergoing a transformation. Notably, the commercial vehicle market is spearheading this change, actively seeking alternative fuels to achieve the objective of carbon neutrality.

Prominent automobile manufacturers such as Mercedes-Benz, Toyota, and Volvo have emerged as pioneers in adopting fuel cell technology. Several corporations are making substantial investments to develop and incorporate fuel cell-based electric vehicles into their product ranges.Fuel cells represent a significant step toward environmentally friendly transportation, utilizing hydrogen to generate energy and emitting only water vapor as waste. Industries are employing innovative technologies to expedite this transformation while improving product development operations. The current generation of technologies is significantly hastening the product manufacturing life cycle, relying on data science and model-based system engineering.

With the use of these instruments, the automotive industry can enhance vehicle designs for increased efficiency and compliance with strict environmental regulations. By incorporating datadriven approaches, decision-making becomes more informed and efficient, leading to the design of every vehicle part with sustainability and efficiency in mind.

The automobile industry is undergoing a revolutionary period marked by the convergence of modern engineering techniques, fuel cell technology, and decarbonization activities. This allencompassing strategy emphasizes the importance of technology in fostering a sustainable future while simultaneously addressing the urgent demand for ecologically friendly transportation.

An automotive engineer, a power electronics engineer, and an electrochemistry engineer collaborated at EinNel to create a model-based system engineering model using computational and mathematical techniques. They successfully built a digital twin of a fuel cell-powered electric vehicle. These models’ physics and performance were thoroughly verified against the actual test results of Fuel Cell Electric Vehicles (FCEVs), and the findings demonstrated an incredibly strong connection with real-world outcomes.

EinNel has established a unified data platform to enhance vehicle systems and performance using these mathematical models. This platform also provides system design engineers with the ability to integrate various AI and data analytics advancements in a unified environment. With this capability, the team can conduct several design explorations and ultimately identify the best concepts. At EinNel, chief scientist engineers, equipped with backgrounds in Data Science, Chemistry, and Quantum Physics, actively pioneer research related to hydrogen production, storage, transportation, and efficient fuel cell technology.

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EinNel’s Digital Solutions Set to Transform the Construction Industry

Ajita Magdalene - Business Analyst

EinNel Team recently made a significant appearance at both the Expand North Star and GITEX events in Dubai, alongside Grow London. Their primary objective was to exhibit EinNel’s AI solutions and data platforms tailored specifically for the construction industry.

Dubai, renowned as one of the top international cities globally, stands out for its construction and tourism sectors, notably housing the world’s tallest building, the Burj Khalifa, which attracts countless visitors to its skyline.

The majority of the monumental ongoing construction projects are spearheaded by the real estate giant, Emaar Properties. Dubai heavily depends on importing construction goods and materials from across the globe to fuel its ambitious projects.

Given the immense scale of these investment ventures and their stringent timelines, meticulous project management from conception to completion becomes indispensable. This encompasses everything from site identification, comprehensive planning, intricate construction phases, quality assurance assessments, and a seamless handover process.

Every construction project involves a complex network comprising subcontractors, contractors, suppliers, government agencies, and import-export entities. The utilization of various software, data systems, and processes often leads to data synchronization challenges, resulting in fragmented information. The absence of a centralized system poses significant hurdles in managing data, projects, inventory, and cost control.

As a consequence, billion-dollar construction projects frequently incur substantial losses, typically ranging from 5-10%, due to communication gaps, complexities, and mismanagement. The introduction of a digital platform that consolidates all construction-related data, knowledge, and analytics into a unified interface could drastically enhance operational efficiency.

Here is where EinNel steps in, aiming to facilitate the construction industry’s transition to cutting-edge digital platforms by seamlessly integrating disparate manual and Excel-based entries into a unified knowledge platform.

Leveraging cloud platforms such as GCP, AWS, and Azure within the big data environment, EinNel consolidates construction-related data, analytics, and AI into a single, accessible platform. This centralized platform facilitates robust applications, including mobile access, thereby accelerating program management within the construction industry while simultaneously reducing operational costs by 20-25%.

EinNel’s dedication to revolutionizing the construction industry through innovative digital solutions holds the promise of not only streamlining processes but also significantly optimizing outcomes and resource utilization within this vital sector.

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