Reimagining business processes through decentralized identity

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14:37 Minutes The average reading duration of this insightful report.

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Primers: Primers are quick short form business reports that educate leaders on key emerging technologies.

Reimagining business processes through decentralized identity

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Decentralized Identity systems solve for inefficiencies and security breaches, making them extremely useful for enterprises. We explore in detail important industry use cases where these solutions can be used and means to implement them.

What’s inside

  1. Transforming KYC using DID
  2. Perishable supply chain using DID
  3. Enabling electronic health records using DID

Transforming KYC using DID

Kyc Process Flow

The KYC Process in Banks and Financial institutions is mandated by the government and can be quite painful both for the bank and the customers. We examine how DID can help not only simplify the process but also ensure high trust and make the process fraud proof, by eliminating intermediaries and returning to trusted direct relationships. Download Complete Research

Perishable supply chain using DID

In case of Food supply the application of IoT can provide real-time data and insights. The current IoT supply chain and the food Supply chain face innumerable challenges.  Using DID and verifiable credentials in food/perishable supply chain can provide a tamper-proof and auditable record of a product’s journey, from its origin to its destination. Solution will have lasting impact not only for controlling quality and expense for organization but will also have impact on public nutrition, health, and sustainability. We explore how!

Enable electronic health records using DID

While managing Electronic Health Records, healthcare organizations face two main challenges: Privacy & Security and Interoperability due to multiple systems in play. By providing patients with greater control over their health information, Decentralized Identity solutions can enhance trust and confidence in the healthcare system, leading to better health outcomes. We explore the details with an example. Download Complete Research

Credits
Author@lab45: Sujay Shivram, Abhigyan Malik

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Reimagining software engineering with GenAI

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13:30 Minutes The average duration of a captivating reports.

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Primers: Primers are quick short form business reports that educate leaders on key emerging technologies.

Reimagining software engineering with GenAI

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GenAI is transforming various domains including software engineering. This technology enables high productivity, rapid development, and abundant innovation promising overall productivity gains of 26-30%. Embrace the future and discover the extraordinary potential of GenAI.

What's inside

  1. An overview of GenAI’s impact on the software engineering industry
  2. A detailed prognosis of GenAI’s impact on the software development lifecycle
  3. Tools and useful technologies for GenAI-assisted software engineering
  4. Future trends in GenAI for Software engineering

Key insights: How GenAI can impact software engineering

GenAI is expected to boost productivity in software engineering by 28% and is projected to improve task completion speed by 54% by 2025. It can also increase application development and maintenance revenue by 25%-30%, leading to a 5%-6% improvement in overall profitability. The GenAI market is expected to grow at a CAGR of 42% over the next decade, and the technology can help address the expected shortfall of 4 million developers by 2025. However, detailed study and implementation strategies are needed to consider factors such as initial installation effort, resource training, and technology integration.

GenAI’s impact on the software development lifecycle

GenAI can significantly impact the various phases of software development by generating code, improving code quality, simplifying code structures, and automating tasks such as unit testing and bug detection. It can reduce the duration of task execution across various software development stages by 20%-45%, resulting in substantial cost savings. While software engineers may be the primary beneficiaries of GenAI, other teams, such as architects, consultants, and sales teams, can also derive substantial advantages. However, implementing GenAI requires a comprehensive strategy that includes tool selection, investment, deployment, and developer training. The implementation strategy should target the highest-leverage phases of software development, and enterprises should invest in resources and training necessary for developers to leverage the technology effectively. Download Complete Research

Tools and useful technologies for GenAI-assisted software engineering

Integration of GenAI with DevOps principles can increase productivity by automating tasks, generating content, and providing intelligent insights. Adopting GenAI in the DevOps software development environment can further boost productivity through script generation, automated monitoring and alert generation, and synthetic data for pipeline load testing. GenAI can complement and enhance Low Code No Code (LCNC) capabilities by integrating visual developer interfaces, quickening development cycles, and creating text and multimedia assets. Key platforms for code generation using GenAI include Copilot by GitHub, CodeWhisperer by AWS, ChatGPT by OpenAI, Vertex AI by Google Cloud, and TabNine by Codota Dot Com Ltd.

Future trends in GenAI for software engineering

As AI continues to evolve, GenAI will become an increasingly essential aspect of the software development process. GenAI provides opportunities for innovation and creativity while also presenting new challenges. Customized benchmarking contextualized to the customer environment is crucial in refining and optimizing GenAI tools, fostering greater productivity and efficiency in software development. Enterprises must formulate a comprehensive GenAI strategy and incorporate GenAI tools in the implementation and testing phases of the software development lifecycle to maximize development cost and effort savings and improve quality. Collaboration with GenAI tools will create new roles, such as Prompt Engineers, and allow developers to focus on strategic thinking and creative problem-solving. GenAI is also an excellent learning and training tool, automating the generation of educational content and assisting in information retrieval and organization. Download Complete Research

Credits
Lead Authors@lab45: Hussain S. Nayak, Anju James
Contributing Authors@lab45: Vinay Ramananda, Dattaram B A

Top trending insights

Future of connected world with AIoT

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11:45 Minutes The average duration of a captivating reports.

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Future of connected world with AIoT

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AIoT is a revolutionary blend of AI and IoT that creates a connected world with limitless opportunities. Smart devices can collaborate to make informed decisions without human intervention, transforming various industries. As AI and IoT converge, their applications will become more advanced, presenting new prospects for businesses and consumers.

What's inside

  1. Insights and technology trends
  2. Overview, benefits, and architecture
  3. Use cases, challenges and key players
  4. Enterprise AIoT adoption strategy

Insights and technology trends

  1. AIoT enables devices to become smarter and more autonomous by analyzing massive data streams in real time and making informed decisions based on that data. They are expected to become more personalized and intuitive by implementing self-learning algorithms, providing real-time solutions. 
  2. Fast, reliable connectivity ensures seamless user experience and data exchange, allowing AIoT systems to respond and act promptly.As cybersecurity technology advances, users gain confidence in the security of AIoT systems.
  3. AIoT can contribute to sustainability initiatives through intelligent monitoring and control systems.
  4. Integrating new technologies in AIoT systems has become an essential component in the future of enterprises and individuals. Key Technology Trends include:  Secure Access Service Edge (SASE), Nanotechnology, Multiplicity, Contextual Proactivity, Seamless Multi-Modal Interaction, Brain- Computer Interfaces.

Overview, benefits, and architecture

AIoT combines sensors, AI, data and ambient computing elements to create a responsive, context-aware environment. It uses embedded devices and natural user interfaces to provide services based on detected requirements and user input.

AIoT can revolutionize how users interact with technology, offering greater convenience and seamless connectivity. The benefits include: intuitive and seamless experience without commands, automated decision making, efficiency and convenience.

While creating an AIoT system, a well-balanced architecture is crucial to manage data processing speed and costs. There is a flow of information in the system based on the external inputs, that ultimately results in a response based on analysed data points by AI and ML algorithms. Download Complete Research

AIoT adoption – Connected enterprise strategy

The 5 step enterprise strategy include the following:

  1. Define AIoT Vision, scope, goals and objectives
  2. Assess IoT Capability, identify AIoT devices & systems
  3. Define Connected enterprise System Architecture
  4. AIoT System Development & Pilot implementation
  5. Enterprise - wide implementation

Use cases, challenges and key players

Use Cases for following domains are discussed:

  • Manufacturing: Employee safety, Inventory management, Collaborative robots (Cobots), AI-driven product design
  • Smart Homes: Home Security, Health and Wellness, Child and Elderly Care, Home Automation
  • Healthcare: Predictive Healthcare, Smart Wearables
  • Automobile: Autonomous Vehicles, Smart Traffic Management, Connected Car Services
  • Retail: Smart Shelves, Customer Experience, Ambient Commerce
  • BFSI: Fraud Detection, Personalized Financial Services

Implementing a complex system like AIoT requires careful planning, collaboration, and attention to detail. Data management, privacy concerns, and integration with various systems can pose significant obstacles to successful implementation.

The AIoT space is dominated by key players such as IBM, Microsoft, Siemens, GE, Cisco, Huawei, ABB, Bosch, SAP, and Honeywell. Download Complete Research

Credits
Author@lab45: Anju James
Contributing Authors@lab45: Hussain S Nayak, Nagendra Singh

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