We are a top software development   firm with experience assisting businesses in their digital transformation. With more than 20 years of expertise and a highly skilled group of agile developers, our company has been providing and implementing innovative technological solutions that meet the various needs and financial constraints of its clients.

With the same sincerity and enthusiasm, we have worked for small businesses and huge corporations such as Lenovo, RoofAid, Dealer Specialties, Byjus, Bigbasket, Bosch, Reliance, Aditya Birla, BPCL, Tata, and many more.

Our team would like to take this opportunity to share with you our latest accolade from Clutch! We’ve been named as one of the game-changing Healthcare App Development Companies on their platform and we are beyond honored to be included in this list. Also, we are grateful to Clutch for making this award a reality!

If this is the first time you are hearing about Clutch, they are a B2B ratings and reviews platform based in Washington, DC. They evaluate technology service and solutions companies based on the quality of work, thought leadership, and client reviews. A rapidly expanding startup, Clutch has become the go-to resource in the agency space.

To celebrate this award, we decided to showcase some of the best reviews and testimonials on our Clutch profile! Here they are:

“What impressed us most about FUSION INFORMATICS LIMITED was their dedication to creating visually appealing interfaces without compromising functionality. Their design team showcased a remarkable ability to understand and translate our brand identity into a stunning app design that resonated with our target audience. Their focus on user experience and attention to detail made them a standout choice for our project.” CEO of Prototyp, Tobias Bard

“Throughout the engagement, FUSION INFORMATICS LIMITED demonstrated excellent project management. They followed the set timeframe and established clear milestones. We were kept up to date on the project’s status by the team’s regular progress reports. They quickly dealt with any issues that developed during the development process and quickly adjusted to shifting requirements.

The ability of FUSION INFORMATICS LIMITED to comprehend our business goals and transform them into a highly functional mobile application was what most impressed us. Additionally, they distinguished themselves from other service providers with their dedication to producing a superior product and their proactive approach to problem-solving.” CEO of Ecosmob Technologies, Maulik Shah

Why Fusion

Connect with our team! At Fusion Informatics we ensure to be incredibly responsive to your requests and address your questions.

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This article explores how ChatGPT is progressively weaving its impact, shedding light on the real-world applications of this AI marvel. 

Understanding ChatGPT

ChatGPT, a product of OpenAI, is not just a program—it’s a conversation partner built on artificial intelligence. This AI model operates on the principles of machine learning and language understanding. It’s designed to process a user’s input and generate a response, but not just any response. What sets it apart is its capability to deliver complex and nuanced replies that make sense in a given context.

This proficiency arises from its training methodology. It has been trained on an expansive dataset comprising various types of internet text. But what does training mean here? It’s a process where the model learns to predict the next word in a sentence based on the words that come before it. Through this, ChatGPT has learned not just words and grammar, but also the context, style, tone, and common patterns found in human language.

The outcome is an AI model that can engage in a conversation that feels human-like. Whether it’s answering a query, writing an essay, or even creating poetry, ChatGPT can do it all while keeping the conversation coherent and contextually apt. It’s like having a knowledgeable and adaptable communication partner that caters to a wide array of conversational needs.

Applications of ChatGPT

• Healthcare

ChatGPT’s role in healthcare extends beyond simply dispensing health-related information. It can serve as a preliminary interface for patient interaction. A user could communicate their symptoms to a ChatGPT-powered platform, and the system, using its understanding of medical terminologies and conditions, could offer potential diagnoses and suggest next steps.

However, it should not replace professional medical consultation. Instead, its purpose is to provide an initial assessment, saving time for both doctors and patients. In areas where healthcare is hard to access, this application could be invaluable, offering immediate advice when visiting a doctor isn’t feasible.

• Education

The role of ChatGPT in education can be transformative. For students, ChatGPT can serve as an accessible tutor available around the clock. Whether it’s explaining complex mathematical equations in a simplified manner, offering different perspectives on a piece of literature, or aiding in language learning.

ChatGPT’s capabilities can greatly augment individual learning experiences. It can offer personalized teaching strategies, adapting to each student’s pace and learning style, potentially revolutionizing the conventional one-size-fits-all approach to education.

• Business

In business environments, ChatGPT can have a wide range of applications. One of the most immediate uses is in customer service. With ChatGPT, businesses can have chatbots capable of handling customer inquiries in a more interactive and human-like manner. Instead of simple predefined responses, these bots can engage customers in a conversation, enhancing the overall customer experience. 

Apart from customer service, ChatGPT can also be instrumental in data analysis. By summarizing lengthy business reports or financial data into concise insights, ChatGPT can help busy professionals quickly grasp essential details, improving business efficiency

• Creative Industries

Creative industries can leverage ChatGPT’s language generation capabilities to foster creativity. Authors could use it as a brainstorming tool, generating story outlines, character descriptions, or even plot ideas. It could serve as a creative companion, helping authors overcome writer’s block and stimulating their creative process. 

In advertising and marketing, teams could use ChatGPT to brainstorm innovative campaign ideas or slogans, enhancing their creative output.

• Journalism and Media

In journalism and media, ChatGPT can be a powerful assistant. Reporters could use it to transform raw information, like notes from a town hall meeting, into a well-structured news article. Editors could use it as an additional tool for checking grammar, consistency, or factual errors in stories. 

Beyond this, it could be used to draft interview questions, or even simulate an interview with a figure of interest, providing a unique training tool for budding journalists. These diverse applications could increase efficiency and productivity in the fast-paced media world.

Potential and Limitations of ChatGPT

ChatGPT’s potential seems virtually boundless, demonstrating its utility across a myriad of fields. Its strength lies in the ability to comprehend and generate human-like text, making it a valuable tool for tasks that require contextual understanding, ranging from customer service to content creation.

However, while the prospects of ChatGPT are enticing, it’s equally crucial to acknowledge its limitations. Firstly, although ChatGPT learns from a vast amount of internet text, it doesn’t truly “understand” or “know” information in the way humans do. Instead, it predicts responses based on patterns it has gleaned from its training data. This can sometimes lead to the generation of inaccurate or nonsensical responses.

Additionally, ChatGPT could potentially reflect and perpetuate the biases present in its training data. Since it learns from the text available on the internet, it may inadvertently adopt the biases, stereotypes, or prejudices that may exist within that data. Efforts are made to prevent such issues, but completely eliminating these is an ongoing challenge in the field of AI.

Striking a balance between harnessing its potential and navigating its limitations will be key to leveraging ChatGPT’s capabilities responsibly and effectively. 

Conclusion

ChatGPT’s wide-ranging applications make it a game-changer in various industries, from healthcare to journalism. Its ability to assist, educate, create, and communicate can provide valuable support, enhancing efficiency and accessibility. 

However, with the power of such a tool, comes the responsibility of using it wisely and ethically. With careful navigation, ChatGPT can be an excellent tool, bringing together the best of artificial intelligence and human ingenuity.

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Simultaneously, the Internet of Things (IoT) represents a network of devices that are connected to the internet, exchanging data and enabling automation. From smart home appliances to sophisticated industrial machinery, IoT has been bridging the gap between the digital and physical world, fostering efficiency and convenience. When this robust system of IoT collides with the capabilities of 5G, the result is a synergy set to supercharge the digital world, embedding connectivity deeper into our daily lives and business operations.

5G technology: An overview. 

5G, the fifth generation of mobile network, offers more than just faster download and upload speeds. It brings substantial improvements in three critical areas: enhanced mobile broadband, massive machine type communications, and ultra-reliable and low latency communications. This new standard provides a high-speed, low-latency network that enables real-time interactions, supporting a massive increase in the number of connected devices.

Internet of Things: An overview 

IoT encompasses a wide variety of devices, from your smart thermostat at home to autonomous vehicles, all connected through the internet. These devices generate data which, when analyzed, allows for the optimization of systems and processes, improving efficiency and effectiveness. As of 2023, there are over 16.7 billion IoT devices worldwide, and that number is predicted to grow exponentially.

Impact of 5G on IoT

The advent of 5G holds significant implications for the IoT landscape. This transformative technology has the potential to redefine the performance, application, and efficiency of IoT devices. Let’s delve deeper into the three primary ways 5G will impact IoT:

• Enhanced Data Speed

5G technology is set to drastically amplify the data transmission speed, outperforming its predecessors. Such a rapid data exchange rate means IoT devices can communicate and share information at unprecedented speeds. This acceleration doesn’t just improve the functionality of the devices but also enables real-time analytics, fostering quicker insights and smarter decision-making. Therefore, the uptick in speed does not simply imply faster performance but also facilitates a more intelligent and responsive IoT system.

• Reduced Latency

One of the crucial offerings of 5G is its promise of significantly low latency. Latency refers to the delay before data transfer begins following an instruction for its transfer. In practical terms, lower latency means that devices and systems can respond to each other virtually in real-time. This is an essential feature for many IoT applications, where an immediate response is crucial, such as autonomous vehicles, precision drones, or emergency alert systems. By ensuring near-instantaneous response times, 5G makes these applications more reliable and safer.

• Increased Device Density

Perhaps the most critical aspect of 5G in the context of IoT is its capability to support a massive number of connected devices simultaneously. As the IoT ecosystem expands, the number of devices that need to be interconnected is growing exponentially. 5G technology is designed to handle this device density, offering connectivity to up to a million devices per square kilometer. This not only accommodates the growing volume of IoT devices but also ensures smooth, uninterrupted communication between them, thereby significantly boosting the reliability and efficiency of complex IoT systems. 

Therefore, the impact of 5G on IoT is threefold – increasing data speed, reducing latency, and supporting a higher density of devices, each aspect contributing to making IoT more efficient, responsive, and expansive.

Applications of 5G in IoT. 

• Consumer Electronics:

Consumer Electronics: In this sector, the 5G rollout is expected to significantly advance the functionality of smart devices. The accelerated data speeds and reduced latency characteristic of 5G networks are poised to redefine the user experience across a broad spectrum of devices. Gaming consoles, for instance, can provide lag-free, multi-player gaming experiences with real-time response, taking gaming to an unprecedented level. 

Streaming devices will offer high-definition content without buffering delays, catering to the growing demand for smooth, high-quality streaming. In smart homes, devices equipped with sensors and AI can interact more efficiently, offering homeowners seamless control over everything from temperature regulation to home security, all in real-time.

• Logistics and Supply Chain: 

The logistics and supply chain industry stands to benefit immensely from 5G-powered IoT solutions. The ability to track assets in real-time will revolutionize warehouse management practices, reducing inefficiencies and minimizing errors. In transportation, 5G-enabled IoT devices can provide constant updates on vehicle location, status, and estimated time of arrival, ensuring accurate tracking of goods in transit.

 This real-time monitoring and decision-making capacity can lead to optimized routes, efficient fuel usage, and ultimately significant cost savings.

• Retail: 

The retail industry can leverage the advantages of 5G to amplify IoT applications, leading to a profound transformation in the way businesses operate and customers shop. Inventory management can become a real-time process with sensors and smart devices providing constant updates on stock levels, reducing instances of overstocking or understocking. In payment solutions, contactless and mobile payments can become faster and more secure, encouraging hassle-free transactions. 

Additionally, customer experiences can be enriched through the use of Augmented Reality (AR) and Virtual Reality (VR) technologies. Shoppers can virtually try on clothes or preview furniture in their homes before making a purchase, creating a unique, enhanced shopping experience.

Potential Challenges faced by 5G

The amalgamation of 5G and IoT, although exciting, comes with its share of challenges that must be addressed to fully realize its potential. The barriers lie in areas like infrastructure, security, energy efficiency, and regulatory policies.

• Infrastructure Development: 

The implementation of 5G technology requires significant infrastructure upgrades. For a full 5G rollout, a dense network of small cells or antennas is required to ensure uninterrupted coverage, demanding substantial investment and time.

• Energy Efficiency:

 With the proliferation of IoT devices powered by 5G, power consumption becomes a pressing issue. The challenge is to create energy-efficient devices and networks that can sustain the energy demands of a high-speed, low-latency 5G network.

• Regulatory Policies:

Updating and implementing regulatory policies in pace with rapid technological advancement is a challenge. Standardization of protocols and establishing global regulations for data privacy and security are key hurdles to navigate.

• Integration and Compatibility: 

IoT devices are diverse and ensuring they are compatible with the new 5G networks can be a complex task. Device manufacturers and network providers need to work together to ensure seamless connectivity and communication among devices.

Therefore, while 5G technology offers tremendous potential to drive IoT capabilities, these challenges need to be effectively tackled to pave the way for a truly connected future.

Future of 5G in IoT. 

The potential integration of 5G and IoT technologies promises an incredibly interconnected future. As 5G’s adoption becomes more widespread, we can anticipate an explosion of IoT applications, not just confined to traditional sectors. In the retail industry, for instance, 5G-enabled IoT can revolutionize real-time inventory management and customer experiences. In the realm of education, it may redefine the boundaries of the classroom, promoting remote, immersive learning experiences.

 Similarly, the logistics and supply chain management sector might witness groundbreaking improvements in real-time tracking and decision-making processes. While challenges remain, the transformative power of these converging technologies will facilitate an environment of enhanced functionality, interactivity, and efficiency across various walks of life.

Conclusion. 

The integration of 5G and IoT presents a promising path towards an efficiently interconnected future. The superior capabilities of 5G, such as enhanced speed, reduced latency, and greater device connectivity, are poised to amplify the benefits of IoT. 

Although potential challenges exist, the immense opportunities these technologies offer outweigh the hurdles. This symbiotic fusion propels us closer to a reality where seamless digital-physical integration redefines convenience and productivity.

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In this article, we will discuss the importance of customer retention for Saas companies and how to build a customer retention strategy. We will also explore how technology can be leveraged to improve customer retention, and provide case studies of successful customer retention strategies. So let’s get started.

Understanding the Importance of Customer Retention for Saas Companies

Customer retention is crucial for Saas companies for several reasons. Firstly, the cost of acquiring a new customer is much higher than retaining an existing one. According to Harvard Business Review, acquiring a new customer can be five to twenty-five times more expensive than retaining an existing one. Therefore, customer retention can save Saas companies a significant amount of money in the long run.

Additionally, customer churn can have a negative impact on a Saas company’s revenue. If customers fail to become repeat members, the company will struggle to grow its revenue. On the other hand, if a company can retain its customers, it will experience steady revenue growth. In fact, a study by Bain & Company found that increasing customer retention rates by just 5% can increase profits by 25% to 95%.

Furthermore, customer retention has several other benefits for Saas companies. Retained customers are more likely to be satisfied with the product and refer others, which can lead to organic growth. Retained customers are more likely to spend more money over time, as they become more familiar with the product. 

Building a Customer Retention Strategy

To build a successful customer retention strategy, Saas companies must understand their customers’ needs and preferences. This can be done through customer surveys, feedback, and data analytics. Once a company understands its customers, it can implement several key components of a customer retention strategy:

1. Understanding customer needs and preferences: Saas companies should strive to understand their customers’ needs and preferences to provide a personalized experience. This can be achieved through customer surveys and feedback, as well as data analytics.

2. Measuring customer satisfaction and engagement: Saas companies should measure customer satisfaction and engagement to ensure that customers are happy with the product and actively using it. This can be done through Net Promoter Score (NPS) surveys, customer feedback, and data analytics.

3. Offering personalized experiences: Saas companies should offer personalized experiences to retain customers. This can be achieved through personalized emails, in-app messaging, and customized content. Personalization can make customers feel valued and improve their overall experience with the product.

4. Providing excellent customer support: Providing excellent customer support is critical for customer retention. Saas companies should ensure that they have a knowledgeable support team that can provide timely and helpful assistance to customers. This can include offering self-service options and implementing a ticketing system to track customer inquiries and resolutions.

5. Continuous improvement: Saas companies should constantly strive to improve their product and services. They should actively seek customer feedback and use it to make improvements to the product. Continuous improvement can help ensure that customers remain satisfied with the product and are less likely to churn.

Leveraging Technology to Improve Customer Retention

Technology can be a powerful tool for improving customer retention for Saas companies. Some ways that technology can be leveraged include:

1. Implementing customer relationship management (CRM) tools: CRM tools can help Saas companies keep track of customer interactions and ensure that they are providing personalized experiences. These tools can also help companies identify opportunities for upselling and cross-selling to existing customers.

2. Leveraging data analytics to understand customer behavior: Data analytics can provide valuable insights into customer behavior and preferences. Saas companies can use this data to identify patterns and trends, and make data-driven decisions to improve the customer experience.

3. Offering self-service options: Offering self-service options such as knowledge bases, FAQs, and tutorials can help customers quickly find answers to their questions and solve issues on their own. This can improve customer satisfaction and reduce the workload on the support team.

4. Utilizing marketing automation: Marketing automation can be used to deliver personalized content and messages to customers at various stages of the customer journey. This can help keep customers engaged and improve their overall experience with the product.

Examples of Successful Customer Retention Strategies.

Several Saas companies have implemented successful customer retention strategies. Here are a few examples:

1. HubSpot: HubSpot is a marketing, sales, and service software company that has a strong focus on customer retention. They offer a range of self-service options, including a knowledge base and community forum. They also provide personalized content and offers to customers based on their behavior and interests.

2. Dropbox: Dropbox is a cloud storage and file sharing company that has a strong focus on customer satisfaction. They offer a simple and intuitive user interface, as well as 24/7 customer support. They also actively seek customer feedback and use it to make improvements to the product.

3. Salesforce: Salesforce is a customer relationship management software company that has a strong focus on personalized experiences. They offer personalized onboarding, training, and support to customers. They also provide customers with a range of self-service options, including a knowledge base and community forum.

Conclusion: 

In conclusion, customer retention is critical for the success of Saas companies. By understanding the importance of customer retention, building a customer retention strategy, and leveraging technology, Saas companies can improve customer satisfaction, reduce churn, and grow revenue. By following the examples of successful Saas companies and continuously striving for improvement, Saas companies can build a loyal customer base and achieve long-term success.

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Python’s user-friendly syntax and readability make it an approachable choice for beginners, while its powerful capabilities cater to the needs of seasoned professionals. It runs seamlessly across different platforms, making it a versatile tool in diverse cybersecurity contexts. Python’s expanding role in cybersecurity serves as a testament to its practicality and effectiveness in combating ever-evolving cyber threats.

Understanding Python’s Features

Python is a high-level programming language that stands out for its simplicity and readability. Its straightforward syntax and use of common English keywords make it accessible even to beginners. Moreover, Python reduces the complexity of coding, encouraging clean and efficient code with less room for error. Its simplicity doesn’t compromise its power, making it a preferred choice among professionals in various fields, including cybersecurity.

Beyond simplicity, Python is incredibly versatile. It’s an interpreted language, which means it can run directly from the source code, eliminating the need for separate compilation and execution steps. This feature, combined with Python’s cross-platform compatibility, allows cybersecurity professionals to write code that operates seamlessly across different environments.

Python’s Use in Cybersecurity: A General Overview

Python’s use in cybersecurity extends from automating routine tasks to creating advanced security tools. Its ability to simplify complex tasks and integrate with other systems makes it an indispensable tool for cybersecurity professionals. For instance, Python is often employed to automate network security tasks, such as monitoring network traffic or identifying unusual activity that could indicate a cyber threat.

Additionally, Python’s role in data analysis and penetration testing is significant. It provides tools to extract insights from vast amounts of security data, helping professionals identify trends, patterns, and potential vulnerabilities. Its flexibility allows for the creation of custom scripts to test system vulnerabilities, making Python a comprehensive tool for cybersecurity operations.

Python Libraries for Cybersecurity

Python’s power in cybersecurity is further enhanced by its wide range of libraries. These libraries, or pre-written chunks of code, allow cybersecurity professionals to perform complex tasks without starting from scratch. Scapy, for example, is a Python library used for packet manipulation, making it invaluable for network security. It can decode packets of many different protocols, create new ones, send them on the wire, and more.

Similarly, the Requests library simplifies the process of making HTTP requests, a common requirement in many cybersecurity tasks. Another valuable tool is the Cryptography library, providing cryptographic recipes for securing sensitive data. Beautiful Soup, on the other hand, assists with web scraping, a technique used to extract information from websites, which can be instrumental in cybersecurity investigations.

Python in Penetration Testing

Penetration testing is a critical cybersecurity practice that involves testing a computer system, network, or web application to identify vulnerabilities that an attacker could exploit. Python proves to be a go-to language for this practice. Its easy-to-use syntax and extensive library support make it a convenient tool for writing custom penetration testing scripts.

Python-based tools such as Metasploit and Wireshark offer pre-made solutions for penetration testing, allowing security professionals to identify vulnerabilities more efficiently. Python’s ability to integrate with these tools and create powerful, custom scripts makes it an essential component of effective penetration testing strategies.

Python in Network Security

Python plays a pivotal role in network security, particularly in automating tasks and developing network security tools. For instance, Python can be used to automate the process of monitoring network traffic, a critical part of identifying potential threats. The ability to create custom scripts that scan for unusual patterns in network traffic makes Python a powerful tool in maintaining network security.

Python’s versatility extends to the development of intrusion detection systems (IDS). These systems monitor network traffic for suspicious activity and issues alerts when such activity is detected. Python’s readability, simplicity, and extensive library support make it an excellent choice for developing effective IDS tools. It’s no surprise, then, that Python is a favored language in network security operations.

Python in Malware Analysis and Reverse Engineering

Python is frequently used in malware analysis and reverse engineering, two critical processes in cybersecurity. Malware analysis involves the dissection of malicious software to understand its functionality, origin, and potential impact. Python simplifies this process by providing tools to automate the extraction and analysis of suspicious files.

Reverse engineering, the process of dissecting software to understand its inner workings, is another area where Python shines. It can be used to deconstruct malware, understand its behavior, and subsequently develop countermeasures. Tools like PyREBox leverage Python’s capabilities, providing a robust platform for reverse engineering and dynamic analysis of malware. 

Future of Python in Cybersecurity

Given Python’s current prevalence in cybersecurity, its importance is only set to grow. The continued development of Python libraries will likely provide even more robust and efficient solutions for tackling cybersecurity challenges. Furthermore, the rise of machine learning and artificial intelligence in cybersecurity will likely further reinforce Python’s position, given its strong support for these technologies.

In the face of evolving cybersecurity threats, the need for professionals skilled in Python will increase. It’s imperative for those in the field to stay abreast of Python’s capabilities and applications. The future of cybersecurity is intertwined with Python, and mastering it will remain a significant advantage for cybersecurity professionals.

Conclusion

Python’s role in modern cybersecurity is multifaceted and crucial. Its simplicity, versatility, and extensive library support make it a powerful tool for combating escalating cybersecurity threats. Encouraging the learning and use of Python will be instrumental in strengthening our defenses and safeguarding our digital landscapes. As we continue to grapple with the challenges of cybersecurity, Python will undoubtedly be at the forefront of our defense strategies.

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Outsourcing involves hiring a third-party company to perform specific tasks or functions that would otherwise be done in-house. This can include services such as IT support, customer service, or accounting. The primary benefit of outsourcing is that it allows a company to focus on its core competencies while delegating non-core tasks to experts in the field. Outsourcing can be done both domestically and internationally.

On the other hand, offshoring involves relocating business processes or services to another country. The primary benefit of offshoring is cost savings due to lower labour costs in the destination country. However, it can also come with challenges like language barriers, cultural differences, and time zone differences.

Key Benefits of Outsourcing

Outsourcing is a process that delegates specific business functions or operations to a third-party service provider. Here are some benefits of outsourcing:

1. Cost saving: Outsourcing often provides cost savings by allowing companies to access cheaper labour rates in other countries. Additionally, outsourcing can help companies reduce overhead costs by eliminating the need to invest in infrastructure and equipment.
2. Focus on core business: Outsourcing allows companies to focus on their core business functions rather than being bogged down by non-core tasks. This can help companies improve their efficiency and productivity.
3. Access to specialized expertise: Outsourcing can provide companies with access to specialized expertise that may be available in various ways. For example, outsourcing IT, functions can provide companies with access to the latest technology and the expertise of IT professionals.
4. Scalability: Outsourcing allows companies to easily scale up or down their operations as needed without hiring or laying off employees.
5. Risk mitigation: Outsourcing can help companies mitigate risks associated with certain business functions, such as regulatory compliance or security.

Outsourcing can benefit companies significantly, allowing them to save money, focus on core business functions, and access specialized expertise. However, it is important for companies to carefully evaluate potential outsourcing partners to ensure that they are reliable and can deliver high-quality services.

Key Benefits of Offshoring

Offshoring, which refers to the practice of outsourcing business processes or services to companies in other countries, can provide several benefits to businesses. Here are some potential advantages of offshoring:

1. Cost savings: Offshoring can often be less expensive than hiring domestic workers due to lower labor costs in other countries. This can allow businesses to save money on salaries, benefits, and other expenses.
2. Access to specialized expertise: Offshoring can enable businesses to tap into specialized expertise and knowledge that may not be available domestically. For example, a company might offshore certain software development tasks to a team in India, with a large pool of highly skilled software developers.
3. Improved efficiency and productivity: Offshoring can enable businesses to operate around the clock, as teams in different time zones can work on tasks in succession. This can lead to faster turnaround times and increased productivity.
4. Increased flexibility: Offshoring can provide businesses with greater flexibility, as they can scale their operations up or down as needed by adjusting the size of their offshore teams.
5. Reduced risk: Offshoring can help to reduce risks associated with a single point of failure. For example, if a business’s domestic team experiences a disruption (such as a natural disaster), its offshore team can continue to operate and keep the business running.

It’s important to note that offshoring has challenges and potential drawbacks, including language barriers, cultural differences, and the need to manage teams across long distances. However, if done strategically and with proper planning, offshoring can benefit businesses significantly.

Which one is the best for digital transformation?

Outsourcing for Digital transformation 

Outsourcing can play a significant role in digital transformation initiatives. Digital transformation involves using technology to change how businesses operate and deliver customer value. Outsourcing can provide access to expertise, resources, and technologies that a company may need in-house. Here are some ways outsourcing can contribute to digital transformation:

1. Access to specialized skills: Digital transformation requires a range of specialized skills, including data analytics, cybersecurity, cloud computing, and software development. Outsourcing can provide access to experts in these areas who can help a company implement and manage new technologies.
2. Cost savings: Outsourcing can be cost-effective, as it can reduce the need for large investments in hardware, software, and personnel. Companies can take advantage of economies of scale by leveraging the resources of an outsourcing partner.
3. Flexibility: Outsourcing can provide flexibility in scaling up or down as needed. As digital transformation initiatives progress, the scope and scale of the project may change. Outsourcing can help companies adjust to these changes without significantly investing in infrastructure or personnel.
4. Speed to market: Outsourcing can accelerate the implementation of digital transformation initiatives. Outsourcing partners can provide a ready-made infrastructure and resources, speeding up the time needed to get new technology up and running.

However, it’s important to note that outsourcing comes with its own set of challenges. Companies must ensure they work with trusted partners with the expertise, resources, and technologies needed to support digital transformation initiatives. Additionally, companies must establish clear communication channels and governance structures to ensure that outsourcing partnerships deliver the expected results.

Offshoring for Digital transformation 

Offshoring can be a powerful tool for digital transformation, as it can help organizations access specialized expertise and lower costs while implementing new technologies and processes. Offshoring involves outsourcing certain business functions or processes to a third-party service provider located in another country, often with the goal of achieving cost savings and other benefits.

In digital transformation, offshoring can also be useful for organizations implementing new technologies or processes requiring specialized expertise. For example, an organization may choose to offshore its software development function to a country with a large pool of skilled developers or its data analysis function to a country with a strong data science industry. By doing so, the organization can access specialized expertise at a lower cost than it could domestically.

Offshoring can also help organizations to scale up quickly as they pursue digital transformation. Outsourcing certain functions allows organisations to quickly add resources to support their digital initiatives without going through the time-consuming process of hiring and training new staff. This can be particularly valuable in fast-paced industries such as technology and e-commerce.

However, offshoring has its challenges. Organizations must be careful to choose the right service providers and to manage their offshoring relationships effectively to ensure that quality standards are maintained and that data privacy and security requirements are met. Additionally, there may be cultural and language barriers to overcome when working with offshore service providers.

Overall, offshoring can be a powerful tool for organizations seeking digital transformation. However, it is important to approach offshoring strategically and to manage offshoring relationships to ensure success carefully.

Summary

In conclusion, outsourcing may be the better choice for companies looking to implement new technologies or systems for digital transformation. Outsourcing allows businesses to access specialized expertise and resources that may only be available in some places. Additionally, outsourcing can be more flexible, allowing companies to scale up or down as needed.

However, offshoring may be viable for companies looking to cut costs on routine, repetitive tasks that do not require specialized expertise. For example, back-office operations such as data entry or payroll processing may be outsourced to a lower-cost country.

Ultimately, the best approach for your digital transformation will depend on your specific business needs and goals. It is important to carefully evaluate both outsourcing and offshoring options and consider factors such as cost, expertise, and potential challenges before making a decision.

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Businesses experienced strategic shifts in their journeys during this transformation process. Some have risen due to trends, others have entered technology mergers and acquisitions, and others have become chains.

Even though businesses have long recognized the importance of digital transformation, other priorities can sometimes take precedence. In contrast, prioritizing digital efforts has emerged as a critical business enabler for success in an increasingly competitive world.

The increased use of automation technologies will be a significant trend in digital transformation by 2023. Similarly, effective use of cloud technologies, low-code/no-code tools, hyper-automation, artificial intelligence (AI), and other technologies would greatly aid company scaling.

Some of the most recent advancements in digital transformation technology include hybrid work, intelligent search, Customer data platforms (CDPs), AIOps and machine learning, and platforms that connect Agile, DevOps, and ITSM.

The ‘Media and Entertainment’ industry is one such industry that has seen a rapid transition as a result of the digital transformation managed services trend. In recent years, the media and entertainment industry has witnessed the true form of the digital transformation strategy, as interactive video ads and content-driven strategies have expanded social media and other internet platforms.

Every industry is following in the footsteps of the media and entertainment industries. At the same time, consumers are demanding more content in more unique forms!

Before delving into the digital transformation trends for 2023, we must first understand the concept of digital transformation.

What is Digital Transformation?

Digital transformation solutions use technology to create new customer experiences, cultural norms, and business practices. It entails modifying corporate strategies for the digital era by utilising cutting-edge technology.

In contrast to previous attitudes and methods, the digital transformation strategy aims to shift the focus away from sales, marketing, and digital transformation customer experience services and towards the actual customers. As a result, over the last decade, customers have received significant priority when developing corporate goals, and businesses now base their plans on what customers require.

The paper must be replaced with online and mobile apps as part of a digital transformation strategy. As a result, it is more organised and clean, as well as more environmentally friendly and sustainable. The digital transition necessitates data security. Team members can organise everything in a secure cloud that they can easily access instead of sending spreadsheets or physical notes.

So, here are the Top 10 Most Significant Digital Transformation Trends for 2023.

Trust and Privacy

Trust and privacy are critical factors determining organisational progress in the digital transformation services journey. According to one global survey of over 4000 brands and consumers, 61% of brands admitted to losing consumer trust by failing to protect their data and information. There is a growing gap between consumers and brands, which brands must bridge to progress. 

Aside from social media and government, traditional media was reportedly among the top three most distrusted industries. Given this, the future will focus on maintaining consumer data’s visibility and providing the best user experience possible with the collected data. Data regulations have already begun advocating for such measures, and more are coming.

Personalization 

Personalization of services will be a critical factor in determining an organization’s success in digital transformation services companies in 2023 and beyond. There will be no free content or content for all! The more innovative the approach, the better the results. As a result, organizations need to personalize their approach to get the most out of their customers instead of simply pushing content for traction.

This approach, known as ‘smarter personalization,’ is not limited to content. It is reflected everywhere the brand interacts with the customer! And this will be critical for digital transformation customer relationship management.

Data-Driven Enterprise

Data is unquestionably at the heart of today’s Digital Transformation services companies. The ability to unlock and analyse data potential has become critical for driving business, streamlining operations, and launching new products and services.

Effective data utilisation is mainly responsible for the efficient movement of resources and the smooth flow of operations across organisations.

Connected User Experience

The average number of applications used in an organisation is rapidly increasing. Customers expect consistency when using multiple channels, such as messaging or mobile service portals.

Given this requirement, providing a connected experience is critical for businesses as part of their digital transformation consulting services efforts. Omni-channel customers with better-connected experiences were found to stay online longer than single-channel customers.

A connected experience entails giving customers improved and convenient access at any time and from any location. While an enterprise has an average of 900 applications, only 29% of them can provide a connected experience, according to survey results.

AI for Reducing overall operational expenses (OPEX)

According to one of the leading surveys, the media and entertainment industries are spending more and making less money. The industry’s operational expenses (OPEX) are outstripping profit margins. Spending is out of control to pursue early profits or gain a competitive advantage. Exactly at this point, the industry should reconsider its strategy.

It’s time to rethink how they handle content and spending power. And AI and Machine Learning (ML) are leading the charge! AI and machine learning techniques assist you in making better use of content and spending.

5G Technology

5G is the acronym for the fifth generation of mobile network technology. 5G’s essential characteristics include multi-peak data speeds, low latency, a better user experience, improved connectivity and availability, and increased network bandwidth.

Edge computing and 5G have the potential to produce some fascinating advances. For example, IBM will provide cloud services to Verizon and Telefonica to power 5G networks. In turn, using technologies such as artificial intelligence (AI), drone-initiated inspections, and video inspections, automation of routine jobs will prevent network problems.

IoT

As IoT makes it possible for machinery and things to interact with one another without requiring human intervention, the full value of data may be gathered through better and quicker decision-making, predictive analytics, and automation.

As billions of items, services, and systems become connected, the proliferation of more accessible and affordable sensors that convert physical data into digital content is anticipated to fuel the Internet of Things industry’s constant expansion. There will be 11.3 billion networked devices in 2021. The number is anticipated to increase to almost 30 billion by 2030.

As a result, several tech titans are quickly adopting IoT and reaping the benefits because startups and small businesses are progressively riding on the IoT bandwagon because they recognize how crucial it is for driving digital transformation and maximizing operational effectiveness. 

Enterprise Resource Planning (ERP)

The first thing that comes to mind when discussing digital transformation services is technology. However, this is only sometimes the case.

Service providers for digital transformation are more concerned with establishing a new culture within an organisation. It consists of people, processes, and technology. As a result, rather than concentrating solely on developing effective media arms or channels to promote services, organisations should also focus on developing intelligent Enterprise Resource Planning (ERP).

ERP can assist you in lowering costs, increasing resource efficiency, and increasing productivity. While you may have already invested in technology and tools, it is time to focus on your back-office operations to see measurable results and high profitability.

Effective IT

Today, the IT department is a critical enabler of any business. The department assists in utilizing the full technological potential to deliver more by making effective and correct decisions on the use of emerging technologies. As a result, in order to succeed in the digital journey, organizations must expand beyond their current IT capabilities.

Multi-Cloud Utilization

The majority of businesses today operate in multi-cloud environments. However, one of the most difficult challenges is managing multi-clouds, particularly when moving workloads between clouds. API-led development and containerization provide solutions to this issue.

APIs aid in the discovery of the unique functionalities of applications running in multi-cloud environments. Containerization is also a tried-and-true solution for dealing with multi-cloud concerns. Get multi-cloud to improve your digital transformation managed services journey.

Partner Ecosystem

As a company grows, strategic partnerships become increasingly important. Successful businesses have already begun to build a collective ecosystem of external partners, stakeholders, and customers. This partner ecosystem assists digital businesses in seamlessly integrating products and services into the customer experience.

In Conclusion

The adoption of digital technology by a company disrupts while increasing revenue. This is known as digital business transformation. Every year, new digital business transformation trends emerge with the potential to accelerate business growth. The benefits of digital transformation include software monetization, data-driven insights, improved customer satisfaction, increased agility, and other advantages.

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However, decision-making remains one of the ultimate tests for leadership in new entrepreneurs. Even experienced leaders with a track record of sound decision-making have, at some point, made a drastically poor decision that shook their reputation.

As the talk about Artificial intelligence promises a radical transformation of the organization, leaders are inquisitive to know if it will make it easier for them. While many of them are excited, some don’t want decision-making made easier. Their ability to make sound decisions without complex technology is the foundation of their reputation as good leaders.

The good news is that AI is unlikely to make it easier for decision-makers as they’ll be required to input judgment in the machine predictions. As the real impact remains to be seen, there are ways in which AI is set to affect business decision-making inevitably.

AI aims to create intelligent machines that can carry out tasks like speech recognition, visual perception, decision-making, and language translation that ordinarily require human intelligence. AI systems use a variety of techniques to learn from data and improve their performance over time, including algorithms, statistical models, and machine learning techniques.

There are several ways in which AI can help leaders make better decisions. Here are a few examples:

Predictive analytics: AI algorithms can analyse large data sets and find patterns and trends that human analysts might miss. This can help decision-makers reach better conclusions based on data-driven insights. Examining historical data and predicting future developments, such as market trends, consumer behaviour, and financial performance, are all skills that can be learned. This can help executives make decisions based on data and the most recent information. AI algorithms can process and analyse vast amounts of data from numerous sources, including structured data like sales figures and unstructured data like social media posts.

Data Analysis: AI algorithms can help leaders quickly and accurately analyze large volumes of data from various sources, allowing them to identify patterns, trends, and insights that would be difficult or impossible to detect through manual analysis. This can help leaders make informed decisions based on objective data rather than gut feelings or intuition.

Natural language processing: AI can analyze large amounts of unstructured data, such as text from social media, customer feedback, or news articles, and extract valuable insights that can inform decision-making. Depending on the analysis being done, natural language processing can be structured using a variety of machine learning techniques. It might be something straightforward, like usage frequency or sentimental value, or it might be something more intricate. 

Automation: AI can automate repetitive tasks and processes, freeing up valuable time and resources for leaders to focus on strategic decision-making. AI can also automate repetitive and time-consuming tasks, freeing human employees to focus on more strategic tasks. Artificial intelligence can automate both cognitive and physical tasks. People can carry out their errands more successfully and make better decisions as a result. It makes it possible for automated decisions to be made without human involvement. 

Simulations: Finally, leaders can use AI to solve issues by building simulations. Organizations can use AI to test various decision scenarios and determine the possible outcomes. Considering the results of their decisions can assist leaders in making wiser decisions. A city might, for instance, use AI to simulate various traffic patterns to determine how a new road design would affect congestion.

Personalize experiences: AI can analyze customer data and personalize experiences, such as product recommendations and marketing messages, to increase customer satisfaction and loyalty. The AI algorithms can analyze customer data to identify individual preferences and tailor marketing and sales efforts accordingly.

Risk management: AI can identify potential risks and vulnerabilities in an organization’s systems and processes, allowing leaders to take proactive measures to mitigate these risks. It can identify risks and opportunities in real-time, such as detecting fraudulent transactions or identifying new market trends.

Predictive modelling: Predictive modelling uses mathematics to predict future events or outcomes by looking for patterns in a set of input data. It is a vital component of predictive analytics, which uses recent and historical data to forecast activity, behaviour, and trends.

AI can create predictive models that forecast future trends and outcomes, helping leaders anticipate problems and opportunities before they occur.

Decision support: AI can provide decision support tools that help leaders evaluate different scenarios and make informed decisions based on a range of factors. AI systems can provide decision support to leaders by suggesting possible courses of action based on data analysis and machine learning algorithms. This can help leaders identify the most effective strategies for achieving their goals.

Decision support systems, which use artificial intelligence to make rational decisions, may aid in better predicting customer behaviour. By utilising this system, AI systems can support real-time decisions and updated market trend gathering, forecasting, and analysis.

Business decisions with AI

AI improves automation while minimizing labour-intensive human work and tiresome tasks. Consider intelligent weather forecasting. Today, it is known that AI-powered tasks can fill the gap between climate and data scientists.

Companies are more prepared to combat disasters with the aid of AI, thanks to its decision-making algorithms. On the plus side, the world has seen firsthand how significantly AI has affected people’s lives and the economy. AI is currently a hybrid form of capital, assisting human and economic development.

Marketing decisions

When it comes to marketing decisions, businesses frequently face several complexities. Customer-driven market complexities in decision-making are increasing every day. The customer’s wants and requirements must first be understood. Finally, the products must be in accordance with the applicable specifications.

Understanding dynamic consumer behaviour is critical for making long-term and short-term marketing decisions. Appropriate AI modelling and simulation methods may assist people in gaining a better understanding of the buyers’ perspectives.

Customer relationship management (CRM)

AI has improved and expanded the capabilities of customer relationship management. Several functions have been automated, including data recording, contact management, data analysis, and lead ranking. Furthermore, the AI buyer’s persona model can predict a customer’s lifetime value. These features enable marketing teams to work more effectively and fluently.

Recommendation system

This artificial intelligence system was first used on music-related websites. The recommendation system has since spread to a variety of industries. It works by first learning about the user’s content preferences. As a result, the content that corresponds to the preferences is advanced. The bounce rate is reduced as a result. Furthermore, the AI system’s learnings may be used to target relevant content better.

Automation efficiency

In business processes, AI-generated automation efficiency has surpassed assembly lines. Automated efficiency is used in business functions such as marketing and distribution. AI has accelerated processes and provided decision-makers with trustworthy information. Humans can gain reliable insights into customers through marketing. This improves interaction with customers. Effective decision-making is now possible thanks to automated market segmentation and campaign management.

In summary, AI can revolutionize how leaders make decisions by providing them with real-time data-driven insights, automating repetitive tasks, and identifying potential risks and opportunities. However, leaders must understand AI’s limitations and use it with human judgment and expertise to make the best organizational decisions. Lots of exciting changes are on the horizon. While AI might not make the process easier, it will significantly contribute towards streamlining decisions for better processes and an agile future organization.

For businesses of all sizes, AI technology is becoming more accessible and less expensive. Using AI’s power, leaders can improve decisions, boost productivity, and encourage innovation. But it’s critical to remember that AI is not a cure-all. Organizations must combine AI and human resources to get the best results.

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Edge computing refers to the practice of deploying computers and data storage closer to the data source. This eliminates the need for data to be processed in a faraway data center and provides advantages such as faster insights, enhanced bandwidth availability, and quicker response times.

While edge computing addressed some of the problems, things became complicated when the expansion of sensors and smart devices created traffic bottlenecks that could have improved performance. The solution to this challenge eventually emerged as edge machine learning.

Edge machine learning is an approach that allows smart devices to process data locally on the device, either using local servers or machine learning algorithms. The term ‘edge’ refers to the processing these deep learning or machine learning algorithms perform at the device or local level. Even though some data is delivered to the Cloud via these edge devices, this decreases reliance on cloud networks. Yet, the ability to analyze some or all of the data locally enables the filtering of the data sent to the Cloud. It also makes real-time data processing and response possible. 

Edge machine learning employs both deep learning and machine learning methods to enable local data processing, depending on the application. Unlike typical data processing computers, edge machine learning devices may process incoming data at the source. It then selects which data need more robust algorithms for processing in the Cloud and which data can be processed locally.

Let’s take the virtual assistant Siri as an example. When you ask Siri to tell you a joke or story, the data is processed locally on the device and does not need to be processed on the Cloud. This is because the jokes or games are kept locally on the device.

The device executes the command without interfering with the operation of the Cloud network. But, when you ask Siri for the weather, the device searches an external source in the Cloud for the information. We can also use edge machine learning to analyze massive data volumes in real-time, which is currently not possible with traditional cloud-powered devices but is critical for applications such as medical devices and driverless vehicles.

Edge machine learning alleviates security concerns associated with storing personal user data on the Cloud. The Cloud’s load is also considerably lessened. This also minimizes the likelihood of DDOS assaults because edge devices decentralize data storage. Edge machine learning also improves data privacy and security since the algorithms can be trained to ignore critical data areas.

Because data is handled locally in algorithms stored on a hardware device, edge machine learning increases system reaction times. Edge machine learning deals with resource constraints, processing capacity, memory issues, response times, and Cloud security concerns.

Why is Edge Machine Learning Important?

Machine learning is continually growing in order to provide more accurate predictions and uncover critical trends more quickly. Edge machine learning is becoming more important currently because:

• By evaluating customer data more quickly makes it easier to detect data anomalies such as malfunctioning devices or data anomalies.

• It addresses the growing requirement in AI and machine learning projects to optimize workloads from training and inference. By relieving edge devices’ central processing units of complicated and heavy mathematical work, edge machine learning makes it faster, cheaper, scalable, and more power-efficient.

• As the Internet of Things uses cases become more tangible in everyday life, the demand for intelligent decision-making at every step in the infrastructure stack will grow.

• The growth of self-improving products necessitates using cutting-edge machine learning to create individual enhancements.

•    Security issues are growing, and feature extraction utilizing neural network partitioning will become critical for safely transmitting data over the network, balancing workloads and latency, and efficiently managing bandwidth needs.

• The ability to recognize complicated events by processing massive data sets in real time is improving.

• It is becoming increasingly necessary to optimize and reduce network costs while also providing offline availability by storing intelligence locally.

• Staying ahead of the regulatory curve requires enabling improved compliance and enhancing security posture by acquiring and processing confidential and essential data locally.

In conclusion

Although edge machine learning is a rapidly changing field, it has the potential to become critical for next-generation solutions. It is an interesting technology that increases predictive skills and performance by analyzing data and sending messages in real time, enhancing responsiveness. It is only a matter of time until edge machine learning becomes a mainstream technology and part of our daily life.

Furthermore, In the future hospitals and assisted living facilities may develop Edge ML-based systems to monitor things like patient heart rate, glucose levels, and falls (using cameras and motion sensors). These technologies have the potential to save lives, and if the data is analysed locally at the edge, employees would be notified in real-time when a speedy response is required to save lives.

Edge ML is an intriguing new technology that is still being discussed and researched. It will only be a matter of time before Edge ML-powered gadgets (like the Internet of Things) become commonplace. And what a thrilling time it will be.

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Technology has been a key player in the gamut of the payment world for the last few decades. The evolutionary mechanism has duly reshaped the payment industry from time to time.

Following the first Industrial Revolution that brought about a major transformation in economies worldwide, the payment scenario equally underwent the transition cycle. It’s for the last fifty years or so that the need for a more convenient, secure, regulated mode of monetary transactions catapulted a significant shift in the manner we pay for goods & services now.

From cash payment to check payment, then to plastic cards like debit/credit card payments, the payment industry has seen it all. A solo swipe method did the trick! It’s indeed interesting to find out how technology has impacted payments and finally arrived at the present stage of digital payments. Let’s discuss it!

EMV Technology

It is the power of Smart Card technology that has challenged a rather precarious counterfeit fraud leading to an alarming situation in the payment domain globally. EMV – Europay, MasterCard, Visa – the names of original creators of the very technology stand for the abbreviation, has come as a big solace to us.

Also known as the Chip Card or IC Card, its data are stored on the IC chips (Integrated Circuits). The transaction is done by physically inserting a card onto a reader or by just tapping over a distance(contactless) using a Near-FieldCommunication Technology. It is the authentication method that categorizes cards into a Chip &Pin card or a Chip &Signature Card.

• Mobile Point of Sale (MPOS)

Mobile POS is the technology that facilitates a flexible payment process in areas like retail, hotel, parking lots, etc. For instance, in a departmental store, customers don’t need to stand in a queue at billing counters to pay bills.

Mobile POS enables sales staff to receive payment from customers just from any location they are present inside the store.

Similarly, hotel staff can check you in or check you out at the lobby itself (or any convenient point). No need to do the formality in the usual front desk corner of the hotel. MPOS is widely being used across industries not only in hotels or retail but SMBs and even the bigger enterprises.

Mobile Wallets

The arrival of digital technology has smoothened the process of payment methods viz., Mobile Wallet is the e-version of a Real Wallet in physical form. Under the technology, consumers use mobile phones to pay for goods & services instead of hard cash, swiping/inserting credit cards, or debit cards. Take, for instance, Google Play, and Apple Pay, where the entire payment card information is stored on a mobile phone.

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Peer-To-Peer Payments

P2P Money transfer is the electronic transfer of money done by one person to another through an intermediary in the form of a Peer-to-Peer payment application. Paypal, ApplePAyCash, Venmo, and Zelle are a few examples of P2P applications. It is the process of transferring funds between two people through their respective personal bank accounts or credit cards using an online medium or app.

In short, it is an effortless money transfer process with a  mere few taps! So, next time when you go outing with family or friends, don’t carry cash but a smart digital payment app on your mobile.

AI-based Voice Payments

Has it not been a common scenario by now- “Alexa, pay my water bill,” a scene you can connect to so often! After mobile shopping, you can now resort to your Android apps that can do you favor towards paying bills through an integrated system of Voice Assistant.

This is termed an AI technology-backed Smart Speaker! You speak, and the AI obeys your command! Many renowned names rule the picture – Amazon, Apple, and Google. Not only at the present but Smart Speaker has a bright future with a Business Insider report suggesting its usage to grow up to 77.9 million users by 2022!

Biometric Authentication

You can consider Biometric Authentication as a significant addition to various digital modes that the payment industry has witnessed so far. It is a verification system incorporating measurable physical attributes like your handprints, fingerprints, your irises, and even voice.

These attributes are unique from person to person. Biometric technology does scanning and then verifies the given attributes to authenticate a user to a particular service. It gives ample scope for combating security threats in the entire system!

Internet-of-Payments

  A disruptive technology like the Internet- of- Things (IoT) has introduced Internet-of-Payment (IOP) that enables financial transactions over IoT devices like wearable gadgets, appliances, and automobiles. MASTERCARD and VISA are the pioneers in this segment that are helping financial institutions with the seamless method of card payments over connected devices.

How would you rate the technologies that let you pay with just a wave of the hand (FitBit), or some In-Car APPfor seamless payments(HONDA or GM cars), shopping for groceries using your Samsung Refrigerators? Thus, the Payment Industry has reached a point where digital payments are the core of businesses across industries.

Would you like to develop some modern technologies to accelerate your business payment systems, reach out to us for a free demo today!

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