Applied Innovation

Generative AI – a game-changing technology set to revolutionize the way organizations approach knowledge management

Applied Innovation

Generative AI – a game-changing technology set to revolutionize the way organizations approach knowledge management

In today’s digital era, information is a valuable asset for businesses, propelling innovation, decision-making, and seeking competitive advantage. Effective knowledge management is critical for gathering, organising, and sharing useful information with employees, consumers, and stakeholders. However, traditional knowledge management systems frequently fail to keep up with the growing volume and complexity of data, resulting in information overload and inefficiency. Enter generative AI, a game-changing technology that promises to transform how organisations approach knowledge management.

Generative AI vs Traditional Knowledge Management Systems

GenAI refers to artificial intelligence models that can generate new material, such as text, graphics, code, or audio, using patterns and correlations learnt from large datasets. Unlike typical knowledge management systems, which are primarily concerned with organising and retrieving existing information, generative AI is intended to produce wholly new material from start.

Deep learning methods, notably transformer models such as GPT (Generative Pre-trained Transformer) and DALL-E (a combination of “Wall-E” and “Dali”), are central to generative AI. These models are trained on massive volumes of data, allowing them to recognise and describe complex patterns and connections within it. When given a cue or input, the model may produce human-like outputs that coherently mix and recombine previously learned knowledge in new ways.

Generative AI differs from typical knowledge management systems in its aim and technique. Knowledge management systems essentially organise, store, and disseminate existing knowledge to aid decision-making and issue resolution. In contrast, generative AI models are trained on massive datasets to generate wholly new material, such as text, photos, and videos, based on previously learnt patterns and correlations.

The basic distinction in capabilities distinguishes generative AI. While knowledge management software improves information sharing and decision-making in customer service and staff training, generative AI enables new applications such as virtual assistants, chatbots, and realistic simulations.

Unique Capabilities of Generative AI in Knowledge Management

Generative AI has distinct features that distinguish it apart from traditional knowledge management systems, opening up new opportunities for organisations to develop, organise, and share information more efficiently and effectively.

  1. Knowledge Generation and Enrichment: Traditional knowledge management systems are largely concerned with organising and retrieving existing knowledge. In contrast, generative AI may generate wholly new knowledge assets from existing data and prompts, such as reports, articles, training materials, or product descriptions. This capacity dramatically decreases the time and effort necessary to create high-quality material, allowing organisations to quickly broaden their knowledge bases.
  2. Personalised and Contextualised Knowledge Delivery: Generative AI models can analyse user queries and provide personalised, contextualised replies. This capacity improves the user experience by delivering specialised knowledge and insights that are directly relevant to the user’s requirements, rather than generic or irrelevant data.
  3. Multilingual Knowledge Accessibility: Global organisations often require knowledge to be accessible in multiple languages. Multilingual datasets may be used to train generative AI models, which can then smoothly translate and produce content in many languages. This capacity removes linguistic barriers, making knowledge more accessible and understandable to a wide range of consumers.
  4. User Adoption and Change Management: Integrating generative AI into knowledge management processes may need cultural shifts and changes in employee knowledge consumption habits. Providing training, clear communication, and proving the advantages of generative AI may all assist to increase user adoption and acceptance.
  5. Iterative training and feedback loops enable continual improvement for generative AI models. Organisations should set up systems to gather user input, track model performance, and improve models based on real-world usage patterns and developing data.

The Future of Knowledge Management with Generative AI

As generative AI technology evolves and matures, the influence on knowledge management will become more significant. We might expect increasingly powerful models that can interpret and generate multimodal material, mixing text, pictures, audio, and video flawlessly. Furthermore, combining generative AI with other developing technologies, such as augmented reality and virtual reality, might result in immersive and interactive learning experiences.

Furthermore, developing responsible and ethical AI practices will be critical for assuring the integrity and dependability of generative AI-powered knowledge management systems. Addressing concerns of bias, privacy, and transparency will be critical to the general use and acceptance of these technologies.

Contact us at to schedule a consultation and explore the transformative potential of this innovative technology

Applied Innovation

Avatars as a Service: Opportunities and Challenges

Applied Innovation

Avatars as a Service: Opportunities and Challenges

The phrase “avatars as a service” describes the development and usage of virtual representations of individuals or fictional characters in various internet settings. Chatbots, artificial intelligence, machine learning, and human control can all be used to power avatars. Customer service, entertainment, education, health, and other uses for avatars are possible.

Different techniques

Different methods may be used to create 3D avatars. The first technique, known as 3D scanning, is taking a person’s face or body in three dimensions using a smartphone or other specialized device. After processing, the final scan is uploaded to the cloud so that it may be further changed and animated. This service is provided by businesses employing a portable 3D body scanner. A different technique is known as “selfie-based,” in which an avatar is made based on a selfie or photograph of a person’s face. To analyze the image and produce a 3D representation that can be altered and animated, artificial intelligence and machine learning are utilized. The third approach is known as “template-based,” and it enables users to either build an avatar from scratch or edit an existing one with different features and settings. A company that provides this service enables customers to make avatars that can digitally try on apparel and accessories. This method allows for the creation of unique, inventive, and versatile avatars. Avatars as a service make it easy and accessible for users to create their own avatars and use them across different platforms and applications. Depending on the provider and method, the process of creating an avatar can vary in complexity and duration, but the general steps remain the same.

Different Use Cases

Avatars have gained new relevance in recent years as more companies and organizations employ them for a variety of use cases. Avatars are changing different sectors of the economy and may be utilized for a variety of tasks, including customer service, entertainment, education, health, and so on. Customers may have a more interesting and personalized experience thanks to avatars. They are able to conversely aid clients with their questions and offer fixes to their issues. An avatar of a customer service agent, for instance, may assist a consumer with placing an order or guiding them through a troubleshooting procedure. Customers can be welcomed and given introductory information about a company or product using avatars.

In order to give consumers more immersive and captivating experiences, avatars can be employed in video games, movies, and virtual reality applications. Users may personalize their avatars to suit their interests, giving them the freedom to explore virtual worlds and engage in interesting and engaging interactions with other users. For instance, a user can design an avatar that resembles themselves and go on an adventure with companions in a virtual metropolis. The usage of avatars on social media platforms may make the user experience more entertaining and participatory.

The educational sector is also utilizing avatars to improve the learning process. Students may study in a more individualized and immersive way by using avatars to create more dynamic and interesting online courses. Students may practice problem-solving abilities and decision-making in a secure and controlled setting by using avatars to imitate real-life circumstances. For instance, students can practice reacting to a medical emergency by using an avatar to imitate one.

The healthcare sector is another area where avatars are used. Doctors and nurses can employ avatars to help with patient care, especially when actual interaction is impractical or impossible. Avatars may be utilized to provide patients with a rudimentary understanding of their symptoms and available treatments, direct patients through exercises and rehabilitation, and even offer emotional support. An avatar, for instance, may direct a patient through physical therapy exercises and give them performance ratings.

Utilizing avatars may make advertising for goods and services more interesting and tailored. Avatars may be altered to represent the interests and traits of certain clients, enabling companies to develop tailored marketing strategies. An avatar of a famous person, for instance, may be used to advertise a brand-new perfume, and an avatar of a model, a new line of apparel.


In addition to the benefits, there are also challenges when using avatars as a service. The quality of avatars can vary depending on the provider and method used. Users may have different expectations and preferences regarding the quality of their avatars. Privacy is also a concern, as avatars as a service involve collecting and processing personal data from users. Security risks include data breaches, hacking, identity theft, or fraud by malicious actors who may try to access or manipulate user data or avatars. Finally, ethical questions arise regarding the implications of creating and using digital representations of people or characters, such as issues of consent, ownership, authenticity, accountability, and responsibility. Despite these challenges, avatars as a service are gaining popularity as a means of personalizing and enhancing user engagement in various online environments

In conclusion, since they may improve interaction, personalization, and engagement, avatars are growing in popularity across a range of businesses. They are employed in marketing, advertising, education, healthcare, and customer service. Future use cases for avatars are likely to be increasingly creative as long as technology keeps developing. The way we engage with technology, one another, and our surroundings might change thanks to avatars.

To discover more about the various evolving use cases in different industries, kindly reach out to us at

Applied Innovation Retail

From Chatbots to Humanoids: A Look at the Diverse World of Virtual Beings

Applied Innovation Retail

From Chatbots to Humanoids: A Look at the Diverse World of Virtual Beings

A Virtual Being is a conversational avatar intended for lifelike human interaction driven by AI. An avatar is a digital representation of a person in a virtual environment used for communication or self-expression. Virtual beings, on the other hand, rely on cutting-edge technology like AI, NLP, and ML and are more complicated creatures created to interact with people in a lifelike manner. Even though both involve developing a digital image of a person, virtual beings are far more advanced and have a wider range of practical uses.

Virtual beings can be used for a range of tasks, including companionship, customer service, and entertainment. The capability of virtual entities to converse with humans in normal language is one of their distinguishing characteristics. They can appear in a variety of ways, such as animated characters on a screen or as humanoid robots. Additionally, they can be tailored to fit particular requirements and preferences by changing things like age, gender, and personality. Virtual beings can be endowed with a variety of different technologies, like facial recognition, emotion detection, and gesture recognition, in addition to their conversational skills. This enables individuals to react to non-verbal cues and engage in more subtle interactions with people.

Examples of Virtual Beings

Chatbots and realistic humanoid robots are only two examples of increasingly common virtual entities. Mitsuku, a chatbot created by Steve Worswick, has received recognition for its capacity to carry on frank discussions with people. Another chatbot that adapts its replies based on human input is Replika. Magic Leap’s AI-driven chatbot Mica employs spatial computing to provide an immersive experience. Hanson Robotics created Sophia, a humanoid robot that can replicate facial expressions and have casual conversations with people. Last but not least, Soul Machines’ AI-powered virtual Zoe has been deployed in customer service applications and can communicate authentically with people.

Technologies Used in Virtual Beings

Virtual beings are made possible through a combination of several technologies, including artificial intelligence (AI), natural language processing (NLP), computer graphics, and machine learning (ML). AI forms the foundation of virtual beings, enabling them to understand and respond to human input in a natural and engaging way. NLP is used to teach virtual beings to understand and interpret human language, from casual speech to formal language. Computer graphics play an essential role in creating the visual representation of virtual beings, including their appearance and movements. ML algorithms train virtual beings to recognize patterns and make predictions based on large datasets of information, such as language or image data. Augmented reality (AR) and virtual reality (VR) technologies can be used to create immersive experiences with virtual beings, overlaying virtual objects onto the real world or creating entirely virtual environments for users to explore. As these technologies continue to evolve and improve, virtual beings will become even more advanced and capable, opening up new possibilities and applications in various industries

Natural language processing (NLP), machine learning (ML), and computer graphics are some of the technologies used to program virtual entities. The construction of a 3D model or avatar that will serve as the virtual being’s representation is usually the first step in the programming process for virtual beings. This may entail creating the avatar’s physical attributes, such as its look, attire, and range of motion. Next, natural language processing is used to give the virtual being the ability to comprehend and react to human input. For the virtual entity to comprehend and provide natural language replies, extensive linguistic training is required.

The market for Virtual Beings:

In a number of sectors, including healthcare, education, and entertainment, virtual beings are becoming more and more common. They provide a number of advantages, including scalability, personalization, and availability around the clock.

The market for virtual beings is expected to grow significantly in the coming years. According to a report by MarketsandMarkets, the global virtual and augmented reality market, which includes virtual beings, is projected to reach USD 125.32 billion by 2026, with a compound annual growth rate (CAGR) of 43.8% from 2021 to 2026.

The use of virtual beings is becoming increasingly popular in a range of industries, including healthcare, education, entertainment, and customer service. In the healthcare industry, virtual beings are being used to provide patient support and therapy, while in education, they are being used for virtual tutoring and training.

In the entertainment industry, virtual beings are being used for gaming and virtual experiences, while in customer service, they are being used to provide personalized assistance and support. The COVID-19 pandemic has also accelerated the adoption of virtual beings, as more companies and organizations look for ways to interact with customers and users remotely.

As virtual beings become more advanced and capable, they are likely to be used in even more industries and applications. For example, virtual beings could be used in manufacturing and industrial settings to improve productivity and safety, or in the automotive industry to provide virtual driving assistants.

Overall, the market for virtual beings is expected to continue growing as more companies and organizations look for ways to leverage AI and virtual technologies to improve customer experiences and streamline operations.

Virtual Beings in the Clothing Industry :

Virtual beings can be used in the clothing industry in a number of ways, including virtual try-on experiences, personalized styling, and virtual assistants. One of the most common applications of virtual beings in the clothing industry is virtual try-on experiences. These experiences allow customers to virtually try on clothing items and see how they would look on them before making a purchase. This can be done using augmented reality (AR) or virtual reality (VR) technology, which creates a realistic virtual representation of the clothing item on the customer’s body.

Another use of virtual beings in the clothing industry is personalized styling. Virtual beings can use data about the customer’s body type, style preferences, and past purchases to provide personalized recommendations for clothing items. This can be done through a chatbot or voice assistant that interacts with the customer and offers suggestions based on their input. Virtual assistants can also be used to help customers navigate the online shopping experience. These assistants can answer customer questions, provide product recommendations, and help with checkout and payment processes. They can be powered by AI and NLP technology to provide a natural language conversation experience.

Overall, virtual beings offer a range of opportunities for the clothing industry to enhance the customer experience, increase sales, and improve customer satisfaction. However, the ethical and social ramifications of virtual creatures, such as how they could affect human relationships and how they might be abused, are also a source of worry. It’s important to ensure that these technologies are used in a way that is ethical, transparent, and respects customer privacy.

Please write to us at to learn more about Virtual Beings and startups working on its diverse use cases.