Meet our Digital Humans: Sarah in Sales & Marketing

Introduction

We’ve all experienced the frustration of dealing with bots that struggle to understand simple responses, requiring us to repeat “yes” multiple times. Fortunately, thanks to improvements in AI, those days are behind us.

The future of customer interaction is Digital Humans and in this article, we’ll introduce you to Sarah, a Digital Human who specializes in sales and marketing. Sarah is designed to not only understand and respond to queries but to also ask targeted questions and provide personalized solutions, creating a lasting impression and pleasant buying journey.

Defining Digital Humans

The technology of Digital Humans merges the authenticity of human interaction with the power of AI to deliver a more personal and engaging experience. Thanks to Generative and Conversational AI, they’re able to interact with users in emotionally intelligent ways.

They excel in natural language processing, emotion recognition, and machine learning, allowing them to perform complex tasks and make informed decisions.

Meet Sarah

As a sales and marketing expert, Sarah can listen to a multitude of tastes, interests, or issues and make calculated product recommendations that will satisfy customers, thereby engaging in dialogue rather than monolog. For larger purchases that require more thought and discussion, Sarah’s infinite patience allows her to guide customers through every step of the purchasing journey, ensuring they are fully comfortable and confident in their choices.

Her emotional recognition features and machine learning capabilities enable her to respond in ways that personally appeal to each customer, building a connection that fosters trust in your brand.

Sarah doesn’t need sleep or rest, so she is available 24/7 to assist customers. Additionally, she can be programmed to speak multiple languages, allowing her to communicate globally and eliminate language barriers. All these features create a marketing experience that helps each customer feel valued and invested in something deeper than the product.

She can be made available to consumers via kiosks, tablets, apps, websites, and more. By integrating Sarah into your website, you can offer a customized user experience that helps customers find the perfect product.

Hire Sarah or create your own Digital Human today!

The amount of time it takes to onboard Sarah is relatively short compared to traditional employees since she teaches herself and is built to serve your company. Overall, she stands apart from other Digital Humans and employees since she is meant to become a specialist in exactly what you want her to be.

You can also create your very own Digital Human that can act as your sales expert. Using our platform, you can upload or connect to your knowledge base, and personalize her or his personality and overall appearance. You can adjust the tone of voice, quirks, and much more to match your brand.

Stay tuned as we introduce our other Digital Humans!

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Experience the power of Enterprise LLM by booking a custom demo today!

What’s new in the Digital Studio: June 2024 release

What's new in the Digital Studio: June 2024 release

Index Parsing Methods Improvements to provide more accurate bot reponses

We have introduced new capabilities to enhance the parsing of documents into multiple chunks within the Index:

Simple Parsing Method – Delimiters: You can now split documents by setting a delimiter (ENTER or double ENTER). The document will be divided into snippets based on the chosen delimiter. Default delimeter means snippets will be parsed with the same approach as before.

Custom Parsing Method: Select specific areas to split into snippets using the SHIFT + ENTER command, allowing for more control over how the snippets are creating. For now, upload just one document at a time if you want to use this method.

Easily export and manage indexes from your knowledge base

We have enhanced our Knowledge Base tab to allow you to easily export and manage indexes. You can now export one or multiple indexes with a simple click. Additionally, we’ve updated the functionality to ensure that the exported indexes can be seamlessly re-imported.

Copy indexes functionality can be also used if you just want to copy the index (either to the same, or other project).

This will help you to move your fine tuned index from Test to Prod for example. All content of your index is exported (incl. snippets) and are uploaded to the new environment in the same way. You can also export and import whole project configuration, which includes also indexes now.

Share specific nodes or project paths

We redefined how the URLs are structured when using our product. The unique Project ID is now integrated directly into the URL structure, as well as information on which tab are you located and which element you have opened.

With this update, you can now share exact node paths or project paths within the conversation flow with your colleagues. When they access the shared URL, the connected project with the specified node will appear, streamlining teamwork and facilitating more frequent project sharing.

Additional changes

Global Fallback Counter in Answer Node: You can now create a global fallback counter for ANSWER nodes, instead of having individual counters for each node. This means, where applied, that fallbacks count in the whole conversation is considered.

Digital Email Processing tile has been removed from the main page, since email bot is now part/combination of both main products.

Technical Logs Removed from Sidebar: As part of our UI improvements, access to Technical Logs has been removed from the sidebar, resulting in a cleaner and more user-friendly interface

Application Performance: We have enhanced the performance and logic of the Digital Studio, ensuring greater efficiency and a smoother user experience.

Bug Fixes and Improvements: Model queries have been optimized for increased speed and efficiency, contributing to overall system reliability and performance.

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Experience the power of Enterprise LLM by booking a custom demo today!

Digital Humans Predictions for 2024

In 2024, the boundaries between human and digital interactions continue to blur, with digital humans poised to take a central role in this transformative era. From enhancing customer service to revolutionizing marketing strategies, these virtual beings are not just figments of sci-fi imagination but are becoming integral to our daily digital experiences. This article delves into the top five predictions for digital humans in the forthcoming year, highlighting their potential impacts and the technological advancements propelling them.

Our Top 5 Predictions

1. Commercial Success and Brand Partnerships

Digital humans are expected to achieve unprecedented commercial success in 2024. Figures like Lil Miquela have already demonstrated the potential of digital influencers, having collaborated with high-profile brands and amassed millions of followers. This trend is anticipated to expand as more companies harness digital humans for marketing, customer engagement, and brand representation, driving substantial sales and fostering deeper customer relationships.

2. Integration with AI and Machine Learning

Digital humans are likely to become a key interface for interacting with sophisticated AI platforms, including large language models like ChatGPT. As AI becomes more advanced, these digital personas will provide a more natural and engaging way for users to interact with AI systems, enhancing user experience and efficiency across various applications.

3. Enhanced Role in AR and VR

Augmented and Virtual Reality technologies are set to become more embedded in our daily lives, with digital humans at the forefront of this evolution. These technologies will increasingly utilize AI-powered digital humans to create compelling, immersive experiences in sectors ranging from entertainment to education, thus broadening the scope and appeal of AR and VR applications.

4. Significant Roles in Metaverse and Web3

The metaverse and Web3 are set to offer fertile ground for the growth of digital humans. As these decentralized platforms develop, digital humans will likely be employed to offer more personalized and interactive experiences, contributing significantly to the metaverse’s evolution into a mainstream technology.

5. Multilingual Communication

Addressing the need for global communication, digital humans capable of speaking multiple languages will become more prevalent. For instance, a digital human in Amarillo, Texas, is set to support over 100 languages, vastly improving accessibility and inclusiveness in public services and beyond. This leap in multilingual capabilities could redefine global customer service standards.

Summary

In summary, 2024 looks to be a landmark year for digital humans, with significant advancements across various domains. These AI-powered entities are expected to not only enhance how we interact with digital content but also revolutionize customer service, marketing, and the burgeoning fields of AR, VR, and the metaverse. As technology progresses, digital humans will increasingly become embedded in our digital interactions, making them an indispensable part of the future landscape. Their evolution will likely continue to offer new opportunities for innovation and engagement in an increasingly digital world.

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Experience the power of Enterprise LLM by booking a custom demo today!

What’s new in the Digital Studio: May 2024 release

What's new in the Digital Studio: May 2024 release

You can now create new nodes within intents!

We have introduced the ability to create new nodes directly in the ‘Answer’ node of intents, enhancing the user experience by providing a more straightforward workflow.

We've enhanced our Knowledge Base!

We’ve upgraded our knowledge base! You can now edit, delete, or add new chunks in one dialog.

Project Deletion and Associated Asset Removal

Deleting a project will also remove all connected assets. A new dialog box will confirm that the following related assets will be deleted:

• Knowledge base indexes

• Campaign data

• Announcement settings

Additional enhancements

Application Performance: Enhancements to the performance and logic of the Digital Studio now deliver greater efficiency.

Bug Fixes and Improvements: Model queries have been optimized for increased speed and efficiency.

Knowledge Base Indexer: Document descriptions are now limited to 1024 characters.

Campaign Reports in XLSX: You can now export campaign data directly to XLSX format from the campaign page.

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Experience the power of Enterprise LLM by booking a custom demo today!

How to empower digital email processing with Generative AI: 5 practicle examples

Omnichannel customer service is becoming increasingly important. McKinsey reports that about three-quarters of customers use multiple channels to interact with a brand. Depending on the situation and their needs, customers prefer different channels. Among these, email stands out as one of the most important. According to Ultimate’s Trend Survey for 2024, email is experiencing the fastest growth among channels reported by CX leaders, indicating that the volume of email requests will only continue to rise.

For customer service teams handling hundreds, thousands, or even tens of thousands of emails every day, the challenges are familiar. Ensuring that emails reach the right person and that customers receive a timely response without efficiency or revenue losses can be daunting.

Fortunately, with Generative AI, managing customer emails has never been easier. Whether it’s routing emails or automating responses, the latest advances offer significant business opportunities. Let’s explore a few specific examples.

Email classification and routing trends

Previously, the widely used NLP approach primarily relied on keyword extraction to classify emails based on keywords in the body or subject. However, it’s often challenging to determine whether an email mentioning payments multiple times should be addressed by someone handling transaction issues, returns, or coupon inquiries. Consequently, such emails often end up being manually routed. Combining this NLP approach with Generative AI can sometimes enhance efficiency and is advisable. However, the Generative AI alone offers a wide range of additional benefits that can significantly transform your customer service operations.

1) The knowledge base approach

Utilizing both large and small language models enables the classification and routing of requests based on context. This means that an email about payments isn’t simply routed based on keywords but rather on the knowledge base available within your company. The AI leverages this information, contextualizes it to resolve the issue, and routes the email based on the necessary next steps, such as complaint processing. With an astonishing 98% accuracy rate, the email is then directed to the inbox of the person responsible for that area, complete with a label indicating the required action. Additionally, the AI can prioritize responses based on the urgency sentiment conveyed in the message.

2) Preprocessing and response automation

By making efficient use of the available knowledge base, Generative AI can help prepare or fully automate human-like responses, saving your teams significant time. In some scenarios, the prepared response may be sufficient for your agent and only require additional human oversight, such as insurance claims. Over time, however, you can identify processes that are ripe for full automation. This means that the Generative AI-powered email processing tool will accurately classify the request and then send a relevant response without any human intervention.

3) API hooks

In addition, when customers authenticate themselves within the incoming email, for example, based on order numbers, booking numbers, phone numbers, or IDs, additional information can be automatically retrieved from the system via connected APIs.

With such authentication, the Generative AI-powered system can also deliver more personalized and relevant responses, including specific details such as delivery delays or claim status.

Born Digital’s Digital Email Processing tool also automatically prompts for additional authentication if it wasn’t completed correctly the first time. This approach results in significant time savings for agents and a noticeable increase in productivity and response time, as the majority of these requests can be fully automated. In our experience, more than 60% of automated requests can be successfully achieved.

4) Customer insight analytics

In addition to the perks mentioned above, Generative AI also offers significant advantages for uncovering customer insights. Beyond digital email processing, it allows you to analyze the sentiment of emails and prioritize responses accordingly. Furthermore, you gain insights into which topics are most frequently addressed, enabling you to understand what your teams need to deal with and which agents are most overwhelmed. The GenAI-powered analytics also reveal new topics that you weren’t aware of before, enabling you to allocate team resources efficiently. By optimizing team performances, redistributing responsibilities, and enhancing your digital email processing and routing, you can power up your customer service operations.

5) Data extraction from email attachments

Emails often come with attachments like invoices, insurance claims, or ID pictures. Born Digital Email Processing efficiently extracts data from these attachments in various formats. This functionality enables automation tools to seamlessly incorporate attachment information into tasks such as updating internal accounting systems. Moreover, it supports preprocessing email responses for human agents. Additionally, the system can also analyze attachment content for suspicious patterns or inconsistencies, aiding in fraud detection efforts within customer service operations. This multifaceted capability not only streamlines workflows but also enhances security measures, ensuring a more efficient and secure customer service experience.

Business results

In summary, integrating Generative AI into customer service operations presents numerous advantages. Businesses can anticipate cost savings through automation, quicker response times to customer inquiries, and seamless provision of multilingual support. Born Digital’s Digital Email Processing tool encompasses all these features, simplifying email classification, routing, preprocessing, and attachment data extraction. By harnessing Generative AI, companies can optimize team performance, gain deeper customer insights, and bolster fraud detection efforts. We’re thrilled to assist you in navigating the implementation process and addressing any questions you may have, ensuring a smooth transition towards a more efficient and effective customer service experience.

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Find out how you can leverage Born Digital's Generative and Conversational AI solutions to drive business results.

Retrieval Augmented Generation: What you need to know

Retrieval Augmented Generation:
What you need to know

What is Retrieval Augmented Generation?

Retrieval Augmented Generation (RAG) is an advanced AI framework crafted to refine the output of extensive language models by employing a blend of external and internal information during answer creation.

At its essence, RAG functions in two main phases: initially, it retrieves a selection of pertinent documents or sections from a large database using a retrieval system grounded in dense vector representations. These mechanisms, which encompass text-based semantic search models like Elastic search and numeric-based vector embeddings, facilitate efficient storage and retrieval of information from a vector database. For domain-specific language models, integrating domain-specific knowledge is pivotal in bolstering RAG’s retrieval precision, particularly in tailoring it to various tasks and addressing highly specific questions amidst a dynamic context, differentiating between open-domain and closed-domain settings to enhance security and dependability.

Following the retrieval of relevant information, RAG integrates this data, encompassing proprietary content such as emails, corporate documents, and customer feedback, to generate responses. This amalgamation empowers RAG to yield highly accurate and contextually pertinent answers customized to specific organizational requirements, ensuring real-time updates are incorporated.

For instance, if an employee seeks information on current remote work guidelines, RAG can access the most recent company policies and protocols to furnish a clear, succinct, and up-to-date response.

By circumventing the cut-off-date constraint of conventional models, RAG not only heightens the precision and reliability of generative AI but also unlocks opportunities for leveraging real-time and proprietary data. This positions RAG as an essential system for businesses striving to uphold high standards of information accuracy and relevance in their AI-driven interactions.

Limitations of Traditional NLG Models and the Advantages of RAG

Traditional NLG models rely heavily on predefined patterns or templates, using algorithms and linguistic rules to convert data into readable content. While these models are advanced, they struggle to dynamically retrieve specific information from large datasets, especially in knowledge-intensive NLP tasks needing up-to-date, specialized knowledge. They often give generic responses, hindering their effectiveness in answering conversational queries accurately. In contrast, RAG integrates advanced retrieval mechanisms, leading to more accurate, context-aware outputs.

RAG’s grounded answering, backed by existing knowledge, reduces the high rate of hallucination and misinformation seen in other NLG models. Traditional LLMs rely on often outdated training data, resulting in answers lacking timeliness and relevance. RAG tackles these issues by enriching answer generation with recent, factual data, serving as a robust search tool for both internal and external information. It seamlessly integrates with generative AI, enhancing conversational experiences, especially in handling complex queries requiring current and accurate information. This makes RAG invaluable in advanced natural language processing, particularly for knowledge-intensive tasks.

Overcoming LLM Challenges via Retrieval-Augmented Generation

LLMs possess remarkable and continually advancing capabilities, showcasing tangible benefits such as increased productivity, reduced operational costs, and expanded revenue opportunities.

The effectiveness of LLMs can be largely credited to the transformer model, a recent innovation in AI highlighted in a seminal research paper authored by Google and University of Toronto researchers in 2017.

The introduction of fine-tuning LLMs and the transformer model marked a significant advancement in natural language processing. Unlike traditional sequential processing, this model allowed for parallel language data handling, significantly boosting efficiency, further enhanced by advanced hardware like GPUs.

However, the transformer model faced challenges regarding the timeliness of its output due to specific cut-off dates for training data, leading to a lack of the most current information.

Moreover, the transformer model’s reliance on complex probability calculations sometimes results in inaccurate responses known as hallucination, where content generated is misleading despite appearing convincing.

Substantial research endeavors have aimed to address these challenges, with RAG emerging as a popular enterprise solution. It not only enhances LLM performance but also offers a cost-effective approach.

Key Benefits of Retrieval-Augmented Generation

With the capacity to retrieve and integrate relevant information, RAG models produce more accurate and informative responses compared to traditional NLG models. This ensures that the information retrieval component of generated content is dependable and trustworthy, enhancing the overall user experience.

By offering source links alongside generated answers, users can trace the origin of information utilized by RAG. This transparency enables users to validate the accuracy of provided information and contextualize answers based on the sources provided. Such transparency fosters trust and reliability, enhancing user confidence in the AI system’s ability to deliver credible and accurate information.

RAG models excel in delivering responses finely tuned to the conversation’s context or user queries. Leveraging vast datasets, RAG can generate responses tailored precisely to user-specific needs and interests.

RAG models offer personalized responses based on user preferences, past interactions, and historical data. This heightened level of personalization delivers a more engaging and customized user experience, resulting in increased satisfaction and loyalty. Personalization methods may include access control or inputting user details to tailor responses accordingly.

By automating information retrieval processes, RAG models streamline tasks, reducing the time and effort required to locate relevant information. This efficiency enhancement enables users to access needed information more promptly and effectively, leading to decreased computational and financial expenditures. Additionally, users benefit from receiving answers tailored to their queries with relevant information, rather than mere documents containing content.

Use Cases of RAG

Interactive Communication:

RAG significantly enhances AI virtual assistant applications such as chatbots, virtual assistants, and customer support systems by utilizing a structured knowledge library to provide precise and contextually relevant responses. This advancement has revolutionized conversational interfaces, which historically lacked conversationality and accuracy. RAG-enabled systems in AI customer support offer detailed and context-specific answers, resulting in increased customer satisfaction and reduced workload for human support teams.

Specialized Content Generation:

In media and creative writing, RAG supports more interactive and dynamic content generation, suitable for articles, reports, summaries, and creative writing endeavors. Leveraging vast datasets and knowledge retrieval capabilities, RAG ensures content is not only information-rich but also tailored to specific needs and preferences, mitigating the risk of misinformation.

Professional Services (Healthcare, Legal, and Finance):

– Healthcare: RAG enhances large language models in healthcare, facilitating medical professionals’ access to the latest research, drug information, and clinical guidelines, thereby improving decision-making and patient care.

– Legal and Compliance: RAG assists legal professionals in efficiently retrieving case files, precedents, and regulatory documents, ensuring that legal advice remains up-to-date and compliant.

– Finance and Banking: RAG boosts the performance of generative AI in banking for customer service and advisory functions by offering real-time, data-driven insights such as market trend analysis and personalized investment advice.

Summary

Retrieval Augmented Generation (RAG) marks a transformative leap in natural language generation, blending robust retrieval mechanisms with augmented prompt generation techniques. This integration empowers RAG to fetch timely and pertinent information, including proprietary data, resulting in contextually precise responses tailored to user needs. With such capabilities, RAG holds vast potential across diverse applications, from enriching customer support systems to revolutionizing content creation processes.

Yet, the adoption of RAG presents unique challenges. Organizations must commit substantial resources to deploy this technology, investing in cutting-edge tools and skilled personnel. Moreover, continuous monitoring and refinement are imperative to fully leverage RAG’s capabilities, allowing businesses to harness generative AI as a pivotal driver of innovation and operational excellence.

As research and development progress, RAG is poised to redefine the landscape of AI-generated content. It heralds an era of intelligent, context-aware language models capable of dynamically adapting to evolving user and industry demands. By addressing key challenges inherent in traditional large language models, RAG pioneers a future where generative AI not only delivers more reliable outputs but also significantly contributes to the strategic objectives of businesses across sectors.

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Conversational AI in IT Support | Benefits and Use Cases

Conversational AI for IT Support | Benefits and Use Cases

IT personnel spend a lot of time dealing with repetitive tasks like password resetting, asset management, and answering frequent questions. With this wide array of responsibilities, it can be difficult for IT staff and managers to deal with everything they need to in a timely manner. Increased responsibilities can lead to issues like delayed response times and inaccurate reporting, which can cause more problems down the line and impact areas like employee satisfaction and administrative efficiency.

Using Conversational AI technologies to offload some of their responsibilities reduces the workload for overworked managers, and decreases costs for companies, who no longer need to overstaff their IT department to reach goals. Conversational AI and AI bots provide solutions to common HR-related issues, like asset management, accesses, and password resets, which increases productivity and ensures internal satisfaction within a business. Implementing conversational AI in Internal Desk departments establishes a bridge between management and employees, reinforcing the connection between the two and allowing for a more effective form of communication.

Challenges Faced by IT Departments

For internal IT teams, their role transcends basic tech support to become indispensable strategic allies within the organization. From facilitating seamless operations in every department to driving innovation, IT stands at the forefront of achieving business objectives. However, with this expanded role comes a host of challenges.

One pressing issue confronting internal IT teams, particularly in the wake of the COVID-19 pandemic, is ensuring optimal employee engagement with technology. Many staff members struggle to grasp the significance of their tech-related roles within the broader organizational context, leading to decreased motivation and efficiency. Moreover, there’s a growing divergence of preferences among employees regarding their work arrangements. While some favor remote setups, others advocate for a more traditional office environment. Bridging this gap requires fostering open communication channels between IT leaders and their teams. Leveraging conversational AI technologies can facilitate this process, fostering deeper understanding and collaboration between IT managers and staff, thereby enhancing productivity and fostering a positive work environment.

As IT’s significance continues to expand across all facets of business operations, the workload for internal IT teams continues to grow. From managing software and hardware infrastructure to addressing user queries and troubleshooting, IT professionals often find themselves overwhelmed with a myriad of tasks. Conversational AI emerges as a viable solution, capable of automating routine processes and handling user inquiries, thereby freeing up valuable time for IT teams to focus on more strategic initiatives and innovation within the organization.

Benefits of Conversational AI

Leveraging conversational AI within internal IT teams can streamline operations, allowing businesses to tackle intricate tasks while reallocating resources to focus on non-automated processes. IT professionals, often at the forefront of understanding user perspectives, can harness AI technologies to conduct surveys and gather feedback on crucial topics such as software usability, preferences for remote or onsite work setups, and individual alignment with the company’s tech goals. This proactive approach not only enhances user engagement but also provides IT managers with valuable insights into their team members’ needs and aspirations.

With access to chat and voice bots, companies can efficiently manage IT tasks such as software deployment, troubleshooting, and system maintenance in a cost-effective manner. Entrusting AI with routine IT functions empowers human agents to dedicate more time to addressing complex issues and driving innovation within the organization. Additionally, conversational AI is adept at assessing situations and determining whether human intervention is necessary, ensuring efficient problem-solving and timely resolution of critical IT matters.

Use Cases of Conversational AI in IT

Using conversational AI to maximize efficiency in IT will benefit businesses in many ways. Below are 5 use cases to illustrate how conversational AI can be used in IT:

User Support and Troubleshooting

Chat and voice bots can serve as the initial point of contact for employees seeking IT assistance. They can efficiently address common user queries, provide step-by-step troubleshooting guides for common technical issues, and offer relevant solutions based on predefined knowledge bases. This frees up IT support staff to focus on more complex and specialized tasks, ultimately improving overall response times and user satisfaction.

Password Resets and Recurring Tasks

Conversational AI can streamline the process of logging and routing IT support tickets. Users can interact with chat bots to report issues, which are then automatically categorized and escalated based on severity and complexity. This ensures that critical issues are promptly addressed by the appropriate IT personnel, while also maintaining a transparent and efficient ticketing system for tracking and resolving issues.

Automated Ticketing and Issue Escalation

Born Digital conversational AI can be programmed to routinely send out forms to employees to gather information about the workplace attitude towards certain things. Regularly checking in with employees helps managers gather feedback on workplace experience and any individual issues/ concerns employees might have. Using AI technology to automate the collection of employee opinions can help managers to deal with any issues expressed in a timely manner, getting ahead of a larger issue before it occurs. Using AI to connect with employees can also help foster a sense of community in the workplace, creating a sense of understanding between employees and their managers.

Asset Management

Chat and voice bots can facilitate the provisioning of software licenses, hardware assets, and IT resources to employees. Through conversational interfaces, employees can request software installations, hardware upgrades, or access to specific IT tools and applications. The bots can then handle the necessary approvals, provisioning processes, and follow-up communications, streamlining the entire request fulfillment process and reducing administrative overhead for IT staff.

Knowledge Sharing and Training

Conversational AI platforms can be used to deliver on-demand training and knowledge-sharing sessions for IT-related topics. Employees can interact with chat or voice bots to access instructional materials, documentation, and training modules tailored to their specific needs. Additionally, bots can conduct interactive quizzes, simulations, and guided learning experiences to reinforce IT skills and best practices. This enables continuous learning and skill development within the organization, empowering employees to become more self-sufficient and proficient in handling IT tasks.

The Future of Conversational AI in internal IT support

The future of conversational AI in internal IT support is poised to transform how businesses manage their IT operations. Advanced natural language understanding capabilities will enable more accurate and contextually relevant responses, while integration with knowledge graphs and AI assistants will provide comprehensive and personalized support. Multi-modal interfaces will cater to users’ preferences, and integration with AR and VR technologies will enable immersive support experiences. Continuous learning algorithms will ensure that conversational AI systems continually improve, delivering more intelligent and efficient IT support tailored to the evolving needs of the organization.

Why Born Digital?

Implementing conversational AI into HR departments will prove to be effective for businesses, as it can make many standard processes much easier to complete while opening up time for managers and HR representatives to deal with more complex tasks, which require more attention. As these technologies get more popular in the industry, applicants and employees will start to expect to deal with a chat or voice bot, as they are the easiest and most reliable option for dealing with inquiries at any time. Using Born Digital AI solutions allow for businesses to get ahead of their competitors and streamline their HR processes, increasing efficiency and overall satisfaction.

Key features of Born Digital AI include:

Advanced Integration Capabilities: Seamless integration with any website, as well as CRM, makes Born Digital simple to implement for any IT department. Requiring no coding on the company’s end, Born Digital’s conversational AI software is convenient for businesses to implement into their pre-existing IT systems.
Multilingual Capabilities: Serving companies all over the world, Born Digital bots interact in almost all languages, making businesses accessible to a diverse clientele.
Sophisticated AI Conversations: Born Digital voice and chatbots engage in natural, dynamic conversations, replicating human interaction for clients to feel heard and understood, enhancing their experience; this is critical in IT because of the constant communication between employees and management.

Find out how you can leverage Born Digital's Generative and Conversational AI solutions to drive business results.

Digital Humans in eCommerce: 5 Use Cases

What are Digital Humans?

Digital Humans are virtual human-like AI characters, which can be implemented in any industry to improve the customer experience. Similar to chatbots, digital humans are experts at handling essentially any administrative task they are given, however, they are more technologically advanced than the chatbot. Their main difference from chatbots is the physical appearance of digital humans, but they are also able to interpret the body language of customers, judging their tone and attitude, and adjusting their virtual appearance accordingly. This added benefit of body language detection and expression gives digital humans the ability to create closer relationships with customers, which can help increase your turnover rate for online, and in-store purchases. While they are not an attempt to replace human contact within customer service, digital humans are the next step in the evolution of AI technology.

Benefits of Digital Humans

Digital humans include all the benefits of chatbots, while offering several advantages. Just like chatbots, they can handle around-the-clock customer inquiries, increasing customer satisfaction without increasing wages. They also have incredible scalability and can be customized by any business to work most efficiently for them. Managers can change the tasks digital humans deal with depending on what they need at the time, making them a multi-use technology with endless possibilities. Digital humans are not just for customer communication, they are also highly capable of executing tasks like drafting and sending emails, cold calling, and recalling past customer information.

Digital humans come with the added benefit of a human appearance, which gives them a significant advantage when compared to the chatbot. This feature can help ease any hesitations certain people may have to interact with AI, which is an apprehension many people still have. On the other hand, the appearance of a digital human can offer all the comfort of talking to a real person, without having to actually speak to a real person. Additionally, digital humans can create a safer environment for some customers who do not feel comfortable sharing some information with a real human. In retail, this can be useful when discussing potentially sensitive information like clothing size or personal preferences. For example, a woman shopping for clothing may feel more comfortable “speak[ing] to a female-presenting digital person about bra fittings” (The Verge). This kind of customization being available to customers allows them to curate their own experience and feel as comfortable as possible working with digital humans.

Use Cases for Digital Humans in eCommerce

In general, when a customer seeks to return a product, you encounter one of two situations: they either aim for a refund or wish to exchange the item.

1. Human-like Interaction

Many people have an apprehension to using AI technology, and the transactional interactions offered by chatbots and voicebots do not foster a comfortable or trustworthy feeling in their responses. Digital humans differ in that they use visual AI to mimic human body language and respond to vocal and physical cues appropriately. Combined with the benefits of any virtual assistant – recommendations, payment assistance, shipping and handling help – digital humans help build brand loyalty and customer trust. Being able to offer natural flowing conversations around the clock is a large advantage for e-commerce companies and is available with the implementation of digital humans.

2. Sales Advising

Serving as the face and voice of the brand, the Digital Sales Agent excels in providing personalized product recommendations, aiding in purchase decisions and alternative evaluations, supporting ongoing campaigns and product upsells. Its unique ability to create an emotional connection fosters customer loyalty, making the digital sales experience not just transactional but also engaging and memorable.

Moreover, the virtual agent isn’t confined to your website; it can extend its guidance to assist customers in your physical shops as well. Crossing the divide between eCommerce and physical retail, digital humans can now be found in kiosks at brick-and-mortar stores, providing easy access to all the information and assistance typically available online. Kiosks featuring digital human assistants are becoming more and more popular for many businesses in an effort to offer more high-tech and interactive solutions to customer interactions.

3. Creating Brand Image

Since their appearance is infinitely customizable, digital humans can act as a familiar face for companies that successfully market their own digital humans. Many companies have found a mascot for their business, whether it be GEICO or Michelin Tires, which fosters brand recognition and familiarity in customers; when they see the mascot, they are instinctually reminded of the products associated with it, and therefore become more likely to buy their particular brand. Companies can take advantage of digital humans flexibility and use it to promote themselves across different media streams. With higher exposure, recognition will increase, which drives customer traffic up.

4. Product Demonstrations

Digital humans are able to showcase a product and it’s unique features in an engaging and interactive way, which increases the likelihood of purchases and effectively decreases cart abandonment rate. Offering customers a view of what a product would look like used or worn by an actual human, visual AI aids revolutionize the shopping process and can help increase the trust customers have in their purchases.

5. Personal Shopping

Thanks to their human-like movement and appearance, digital humans are more capable at forming relationships with customers. A benefit of forming this relationships is an added trust between business and customer. Digital humans are able to store information about individual customers to better understand their purchase history and preferences. Digital humans can use this information to monitor new releases or restocks and notify customers of purchase opportunities.

Future of Digital Humans in eCommerce

Since digital humans are already the successor of the chatbot, it is no secret that AI technologies are being developed faster than ever before. New technologies being available to business create opportunities that were previously impossible. Digital humans are also able to leverage their human-like appearance to gain followings for their customized personality. Having a recognizable physical and digital appearance allows digital humans to gain fan-like followings, which can then be used to promote certain products through methods like brand partnerships.

Why Born Digital?

Born Digital specializes in AI technology that can be used by businesses to maximize their operations. We sell our products with the hopes that our clients can simply implement them, design them to fit their unique needs, and start enjoying the benefits of virtual assistants as soon as possible. We focus on bridging the gap between customers and businesses by implementing the most specifically designed, customer focussed services. Using the strengths of modern technology and human interaction, Born Digital digital humans are cutting edge assistants businesses can trust to handle customer facing interactions.

We believe in a future where humanity and technology seamlessly come together. Our solution uniquely combines the latest in AI to enable your business to automate an infinite number of active operations while providing unparalleled customer engagement.

Find out how you can leverage Born Digital's Generative and Conversational AI solutions to drive business results.

Applications of AI Outbound Voice Bots in Debt Collection

If you’re seeking ways to automate debt collection, streamline account receivables, and maximize debt recovery, look no further. AI outbound voice bots stand out as one of the most efficient solutions available. These sophisticated tools offer unparalleled efficiency in managing late-paying clients, boasting an impressive 78% customer response rate. What’s more, they accomplish this without the need for manual intervention, often reaching debtors precisely when traditional contact methods fail to connect.

To future-proof your automation efforts and ensure their longevity, consider seeking an omnichannel vendor. Such vendors not only manage outbound calls but also facilitate reminders via emails or SMS, handle payment transactions, and more. By consolidating these functions into a single platform, you can streamline the entire collection process, making it more efficient and effective.

How the outbound calling works

Outbound calling with an AI voice bot operates seamlessly within your debt collection framework. Here’s how it typically unfolds:

1. Initiating the Call: The outbound voice bot automatically dials numbers from your debtor database. Upon connection, it introduces itself, identifies the company it represents, and outlines the purpose of the call.

2. Authentication: To ensure security and accuracy, the bot authenticates the debtor’s identity using predetermined methods such as date of birth or other verification processes.

3. Engaging in Conversation: The bot engages the debtor in a dialogue, assessing their intention to address the debt. It encourages prompt action, amplifying the urgency if necessary, such as setting deadlines for payment arrangements.

4. Offering Payment Options: During the conversation, the bot presents various payment options for settling the debt. It may follow up with an email or SMS containing detailed payment information for the debtor’s reference.

5. Logging Call Details: Simultaneously, the bot summarizes the call outcomes and updates your database accordingly. It flags customers based on their responses, allowing for efficient follow-up actions.

6. Handling Missed Calls: In cases where debtors are unavailable or miss the initial call, the system allows for flexible campaign timing. You can configure settings to retry reaching these customers after a specified interval, ensuring persistent outreach.

7. Call Back Handling: If a debtor returns a missed call, the AI bot acknowledges their initiative, expresses gratitude for calling back, and seamlessly continues the conversation flow based on the established parameters.

8. Scalability and Database Management: The AI voice bot operates 24/7, capable of handling thousands of simultaneous calls. As a valuable byproduct, it updates your contact database in real-time, flagging discrepancies such as unreachable numbers or outdated contact details.

Benefit from Gen-AI powered solutions

Leveraging the potential of generative AI solutions can transform your collections efforts. By adopting platforms like Born Digital, you move beyond the limitations of traditional bot interactions and into a new sphere where AI engages in nuanced, human-like conversations tailored to each debtor’s situation.

Gone are the days of rigid, scripted responses. Generative AI empowers bots to provide contextual replies that foster trust and connection with your customers. Whether negotiating new payment plans or addressing sensitive financial matters, debtors are more inclined to open up to AI, perceiving it as a non-judgmental entity capable of understanding their situation.

What’s more, Born Digital offers enterprise-grade security measures that protect customer data and ensure interactions stay within pre-defined parameters. Rest assured, the bot only responds with information gleaned from your knowledge base, maintaining confidentiality and preventing unintentional miscommunication.

In addition, the flexibility of generative AI extends to linguistic and cultural nuances. You have the freedom to customize the bot’s tone, voice to cater different customer demographics in different languages and regions.

Get immediate reactions at a lower cost

With the AI outbound bot, you can recover up to 25% of the debt, capitalizing on the fact that over 80% of customers typically answer the voice bot phone calls. This means reaching more clients without expanding your workforce – and crucially, reaching them promptly.

Are you prepared for a new era in debt collection, where customers receive early notifications and are provided with multiple payment options directly on their mobile devices? Contact us today to tap into this transformative approach and connect with your customers wherever they may be.

Find out how you can leverage Born Digital's Generative and Conversational AI solutions to drive business results.

Conversational AI: 2024 Market Outlook

Introduction

The conversational AI sector has seen significant growth into 2024, prompting providers to rethink their approaches to meet client and consumer demands. Initially sparked by the global pandemic, this wave of innovation has now matured, delivering desired outcomes for businesses.

As technology advances, vendors must adapt their development and deployment strategies. Simple Q&A chatbots have evolved into sophisticated virtual agents capable of providing 24/7 support and handling complex transactions.

Improvements in conversational AI have revolutionized customer self-service, surpassing previous standards of efficiency and convenience. Consequently, both businesses and consumers now expect more tailored solutions rather than one-size-fits-all chatbots.

Four key market trends will continue to enhance the business value of conversational AI in the future:

1) AI agent deployment time will be significantly lower

The pandemic has underscored the importance of having robust customer service systems in place, as many businesses found themselves overwhelmed by sudden surges in inquiries. Those with virtual agents were better equipped to handle the increased volume, provided their AI solutions were up to the task. However, many others faced challenges, hastily deploying chatbots that were either incomplete or required significant time and effort to implement.

It’s now crucial for vendors to demonstrate that their solutions offer tangible returns on investment from the outset. When assessing a conversational AI vendor, consider:

1. Does the solution feature scalable Natural Language Understanding (NLU) capable of handling multiple user intents simultaneously?

2. Can self-learning AI help bypass the initial ‘cold-start’ phase and assist with ongoing virtual agent development and maintenance?

3. How quickly can an AI chatbot project move from development to launch? Is it a matter of weeks (preferred) or several months (less ideal)?

2) Data-driven chatbot design is more important than ever

As we look ahead, the landscape of software engineering roles is poised to undergo a significant transformation by 2025, with Gartner forecasting that half of all top positions will necessitate direct oversight of generative AI. The prevalence of conversational platforms among employees highlights the growing importance of AI chatbots in professional settings, a trend that will likely continue to evolve in the coming years.

To ensure that these interactions remain meaningful, conversational AI vendors must elevate their offerings beyond traditional design principles that have been relied upon for years. Merely providing cutting-edge technology will no longer suffice in demonstrating the utility of virtual agents as effective tools for customers.

Moving forward, employing evidence-based design principles will be crucial for virtual agent development, encompassing elements such as personality, avatar design, and website visibility. Solutions equipped with robust analytics tools and comprehensive resources, including best practices, will be essential for companies seeking to leverage conversational AI to its fullest potential.

3) Going 'chat-first' will bring the fastest ROI

According to Gartner, the future of self-service is heading towards customer-led automation. By 2030, Gartner analysts anticipate that a billion service tickets will be automatically generated by chatbots and virtual agents, or their upcoming counterparts.

This projection aligns with the growing trend of chat-based self-service, which offers a cost-effective and accessible means of automating customer interactions on a large scale. As consumers increasingly embrace this approach, businesses are poised to capitalize on its potential.

Embracing a ‘chat-first’ strategy, wherein all customer service traffic is directed through conversational AI solutions, allows businesses to leverage automation effectively. This approach can lead to reduced support costs and higher customer satisfaction scores as it plays to the strengths of automation.

Meet our Digital Humans: Sarah in Sales & Marketing​

Introduction

Defining Digital Humans

Meet Sarah

Hire Sarah or create your own Digital Human today!

Get in touch

Experience the power of Enterprise LLM by booking a custom demo today!

What's new in the Digital Studio: June 2024 release

Index Parsing Methods Improvements to provide more accurate bot reponses

Easily export and manage indexes from your knowledge base

Share specific nodes or project paths

Additional changes

Get in touch

Experience the power of Enterprise LLM by booking a custom demo today!

Digital Humans Predictions for 2024

Table of contents

Our Top 5 Predictions

1. Commercial Success and Brand Partnerships

2. Integration with AI and Machine Learning

3. Enhanced Role in AR and VR

4. Significant Roles in Metaverse and Web3

5. Multilingual Communication

Summary

Get in touch

Experience the power of Enterprise LLM by booking a custom demo today!

What's new in the Digital Studio: May 2024 release

You can now create new nodes within intents!

We've enhanced our Knowledge Base!

Project Deletion and Associated Asset Removal

Additional enhancements

Get in touch

Experience the power of Enterprise LLM by booking a custom demo today!

How to empower digital email processing with Generative AI: 5 practicle examples

Table of contents

Email classification and routing trends

1) The knowledge base approach

2) Preprocessing and response automation

3) API hooks

4) Customer insight analytics

5) Data extraction from email attachments

Business results

Get in touch

Find out how you can leverage Born Digital's Generative and Conversational AI solutions to drive business results.

Retrieval Augmented Generation:What you need to know

Table of contents

What is Retrieval Augmented Generation?

Limitations of Traditional NLG Models and the Advantages of RAG

Overcoming LLM Challenges via Retrieval-Augmented Generation

Key Benefits of Retrieval-Augmented Generation

Increased Accuracy

Better User Trust

Contextually Tailored Responses

Enhanced Personalization

Reduced Computational and Financial Costs

Use Cases of RAG

Interactive Communication:

Specialized Content Generation:

Professional Services (Healthcare, Legal, and Finance):

Summary

Get in touch

Experience the power of Enterprise LLM by booking a custom demo today!

Conversational AI for IT Support | Benefits and Use Cases

Table of contents

Challenges Faced by IT Departments

Benefits of Conversational AI

Use Cases of Conversational AI in IT

User Support and Troubleshooting

Password Resets and Recurring Tasks

Automated Ticketing and Issue Escalation

Asset Management

Knowledge Sharing and Training

The Future of Conversational AI in internal IT support

Why Born Digital?

Find out how you can leverage Born Digital's Generative and Conversational AI solutions to drive business results.

Digital Humans in eCommerce: 5 Use Cases

Table of contents

What are Digital Humans?

Benefits of Digital Humans

Use Cases for Digital Humans in eCommerce

1. Human-like Interaction

Meet our Digital Humans: Sarah in Sales & Marketing

Retrieval Augmented Generation:
What you need to know