Conversational AI is a highly lucrative technology for enterprises, helping businesses prevent customer attrition, enhance experience, and become more profitable.   

While AI-powered chatbots and virtual assistants are the most popular forms of conversational AI, many other use cases exist across industries.    

Discover business applications, benefits, and strategies for implementing Conversational AI within an organization, peer-reviewed by the global academic community.   

Conversational AI for Business Success: How to Amplify Artificial Intelligence 

On January 4, Pavlo Yalovol, Intetics VP of Innovation, presented the scientific paper ‘Conversational AI for Business Success: How to Amplify Artificial Intelligence’ written by Boris Kontsevoi, Intetics CEO and President, at the virtual stage of the eighth edition of International Conference on Information System Design and Intelligent Applications (ISDIA). 

Read also: AI-Powered Coding Assistants—Friend or Foe for Developers? Pavlo Yalovol, Intetics Vice President of Innovation for ITID Lviv 

The ISDIA 2024 conference brought together researchers, scientists, engineers, students, and industry practitioners to exchange theories, methodologies, new ideas, experiences, products, and applications in all areas of intelligent computing methodologies. Participants explored how AI, ML, and other innovative technologies enhance and safeguard our interconnected world.  

Get a glimpse of the key presentation insights, and feel free to access the full paper by reaching out. 

AI in Action: Advancements, Capabilities, and Transformative Benefits 

Conversational AI and virtual voice assistants with natural language processing (NLP) and machine learning under the hood have emerged to simplify daily routines by handling tedious, time-consuming, or complex tasks. NLP deciphers human language, while ML enables learning from data, making these technologies proficient in human-like interactions.  

The adoption of AI experienced a 10% surge from 2021 to 2023, attributed to the proactive efforts of IT professionals. Projections indicate a substantial annual increase of 38% in the global AI market value from 2022 to 2030.   

Recent research by McKinsey highlights the financial advantages of incorporating conversational AI, positioning companies with a competitive edge, and driving heightened investments in AI development. 

Conversational AI’s Potential across Industries 

AI-driven chatbots and virtual assistants enable seamless conversations, automate mundane tasks, and gather valuable customer insights across Healthcare, Finance, E-commerce, Education, and other industries:

Featured Case Study: AI-Powered Virtual Nurse Helps Over 100,000 Patients Worldwide to Monitor Their Health Daily 

Advancements in NLP: Models & Algorithms 

Recurrent neural networks for generating word sequences enable tasks like text prediction, handwriting recognition, and speech recognition. Explore the newer NLP models, which can answer intricate research questions and process information across multiple languages. 

Different Types of NLP Models 

There are four key neural network architectures:  

• Feedforward Neural Networks (FNNs): Process data unidirectionally from input to output. Suited for tasks without sequential/temporal dependencies. Applied in classification and regression.  
• Convolutional Neural Networks (CNNs): Ideal for grid-structured data like images. Use convolutional layers to detect patterns. CNNs are used in image recognition and object detection.  
• Generative Adversarial Networks (GANs): Composed of a generator and discriminator network. The generator creates data; the discriminator differentiates from accurate data. GANs are employed in image generation and data augmentation.  
• Recurrent Neural Networks (RNNs): Designed for sequential data processing. Feedback loops allow the learning of patterns in sequences. RNNs are applied in language processing and time series analysis. Challenges like vanishing gradients are addressed by LSTM and GRU variants. 

The Ethical and Reliability Challenges of AI 

Discover core challenges faced by conversational AI that businesses should be aware of: 

• Understanding Context: AI may struggle with broad contexts and subtle nuances, leading to misinterpretations.  
• Data Bias Risks: Reliance on incomplete or biased training data can lead to skewed and unfair interaction outcomes. 
• Human Oversight Necessity: Expert review is essential to mitigate risks of unexpected consequences from AI autonomy.  
• Vulnerabilities to Exploitation. AI systems can be exploited for disinformation and propaganda. 
• Consumer Trust. McKinsey survey reveals high consumer trust in AI, often surpassing human expertise. 
• Realism and Validation. AI should not be the sole decision-making tool; rigorous human testing and validation are crucial. 

NLP API Options: A Look into Leading Choices 

There are various APIs (Application Programming Interfaces), which encompass a range of functionalities, including sentiment analysis, entity recognition, text categorization, language detection, text generation, and more.  

Therefore, when selecting an API, several key factors should be taken into consideration: customization and control, complexity of use case, platform compatibility, and integration ease. Some of the prominent NLP APIs are OpenAI GPT, Google Cloud Natural Language API, Google Dialogflow, Amazon Comprehend & Lex, IBM Watson NLU & Assistant, Microsoft Azure Cognitive Services, Wit.ai, spaCy, Algorithmia, and others. 

Key Steps to Developing a Successful Conversational AI Business Model 

Formulating a successful conversational AI business model implies these crucial steps:  

• Defining the niche. Identify a specific domain where conversational AI solutions can provide value. The niche should align with the expertise of the business and cater to a genuine market need.  
• Creating a high-quality product. The product must possess natural communication, complex query understanding, accurate responses, and scalability.  
• Leveraging NLP tools. Integrating NLP enhances the AI’s ability to engage with users intuitively.  
• Integration with existing systems. Seamless integration with established business systems (CRM, ERP, help desk software, etc.) bolsters the AI’s capabilities and elevates the overall customer experience.  
• Developing a go-to-market strategy. This strategy should encompass the following elements: target audience definition, needs and preferences analysis, and marketing plan.  
• Monitoring and optimization. Utilize analytics tools to glean insights from customer inquiries and employ these insights to drive continuous improvements that enhance system performance. 

Conversational AI can enhance lives when used appropriately and aligned with user expectations. Here are a few examples and numbers:  

• Business Process Optimization. Up to 25% cost reduction and 30% productivity growth with record management, task management, auto-scheduling, email filtering, and fast onboarding and training powered by CAI.  
• Enhanced Decision-Making. Up to 95% of information accuracy thanks to easy report generation, advanced analytics, and smart recommendations.  
• Advanced Customer Interactions. Customer satisfaction increases by up to 50% with service/product recommendations, intelligent comparison, and a robust sales funnel.  

Successful implementation demands meticulous planning, experimentation, and continuous monitoring to achieve desired outcomes.  

Are you considering starting to plan and implement conversational AI technologies for your niche? Get started with advanced approaches and industry solutions now. 

More about Conversational AI Business Applications: 

• Conversational AI. The New Era of Human-like Automated Communication. 
• AI Transforming Healthcare Solutions with Conversational Intelligence in Medical Virtual Assistants 
• Chatbot Center of Excellence: Chatbots Turnkey Development 

The post Conversational AI for Business Success: Peer Reviewed Strategy to Build Profitable AI Model [Paper Presentation at ISDIA 2024] appeared first on Intetics.

This data was obtained through research by Albert Mehrabian, Professor Emeritus of Psychology at the University of California, Los Angeles, and American anthropologist Ray Birdwhistell.  

That’s all clear. But you may ask: how does this apply to my business?  

It’s all about the missed opportunity. Getting the correct meaning of the emotions of your clients or partners brings many benefits. Here emotion recognition technology also referred to as Affective Computing, comes in handy. 

Emotion recognition software powered by Artificial Intelligence and Machine Learning interprets human emotions from non-verbal visual data. By leveraging those unspoken reactions, businesses can better understand their customers. As a result, they can improve the customer experience and increase their profits.  

In the article, we will find out what emotion recognition is, how it works, and where one can use it. Let’s start! 

What Is Emotion AI? 

As a natural progression of facial recognition technology, emotion recognition is a field of computer vision that is gaining more and more attention in mass media. It involves facial emotion detection and the automatic assessment of sentiment from body language, voice patterns, gestures, facial expressions, and other non-verbal signals.  

The technology comes from the model of six universal expressions, proposed by Paul Ekman, an American psychologist and a pioneer in studying emotions and their relation to facial expressions. According to the model, there are seven universal facial expressions of emotions: anger, contempt, disgust, enjoyment, fear, sadness, and surprise.  

Emotional AI Use Cases 

Emotion AI products and solutions are incorporated into many industries to help deliver an emotionally rich experience. It can aid in the diagnosis of mental and neurological disorders in healthcare. Help educators engage students more in the lessons they are teaching. Assist talent acquisition specialists in locating the best prospects for hiring.  

Let’s explore the most common industries utilizing emotion detection solutions. 

Healthcare

Medical centers use AI facial recognition to determine patients’ emotions in the waiting rooms. That helps doctors prioritize those patients who are feeling worse and get them to appointments sooner.

Another project is designed to help children with autism spectrum disorder understand the feelings of others. The system is installed on Google Glass. When another person is near the child, the glasses use graphics and sound to suggest that person’s emotions. Tests have shown that children socialize faster with such a “digital advisor”.

Finance & Banking 

The typical use case in the finance sector is banking apps with the integrated functionality of Emotion AI. It uses the already embedded sensors to detect facial expressions. You can utilize eye tracking, as front-facing cameras on recent smartphones may now be used to precisely track a user’s gaze position. If the customers’ attention is lost and they begin to roll their eyes away, then that is something to notice and make changes.  

Recruitment

Another area in which emotion detection technology is in demand is recruiting. Large companies are implementing artificial intelligence to monitor employees’ behavior and psychological state. Cameras with video analytics modules installed in the office can detect signs of stress among employees and give alerts to HR departments.

Current State

Despite the many benefits of technology, there are some concerns too. The emotion recognition disputes growth has been influenced by privacy and transparency issues, racial bias danger, and ethical considerations.  

In May, Microsoft announced it would stop allowing broad access to cloud-based AI technology that infers people’s emotions. But it turns out that the corporation will keep its emotion identification capacity in an app used by persons with eyesight loss, despite their acknowledgment that technology has “risks.”  

Microsoft and Google will continue to include AI-based capabilities in their products despite rising worries over creating and applying “controversial” emotion recognition in software applications. 

Since we are aware of these issues, why is there such a massive demand for emotion detection technology? Remember a rule: only how technology is utilized determines whether it is intrinsically good or bad. And many other sectors, as mentioned above, are already gaining from the use of emotion recognition software. 

So, does emotion recognition matter to your industry? Despite doubts around the overall technology concept, this does not imply that the technology isn’t worth the effort. In fact, the opposite is true: as the demand for emotion recognition expands, facial recognition models and algorithms will evolve and keep getting advanced, secure, and more applicable to real-life situations. 

How to Build an AI Emotion Recognition Solution? 

Here comes the Intetics AI and ML Center of Excellence, created to help you find a solution to your bold technological ideas. 

We accumulated expertise in various technologies, unique customer project experiences, efficient methodologies, and best practices. Let’s train your program to investigate, assess, foresee, identify, and communicate! 

Here is the tech stack we use in AI/ML projects for our clients:

• TensorFlow
• StanfordCoreNLP
• CatBoost
• Scikit-Learn
• NLTK
• Keras
• GPT-2

And this is how your machine will learn:

Check Your Emotions and Get Advice with Our Fun Demo

Just follow the link emotions detection AI demo. 

Follow the path of companies prioritizing AI breakthroughs that recognize, understand, and react to human emotions while fostering more robust customer relationships.

Still wondering how to apply emotion recognition solutions for your industry to add extra value to customer experience? Reach out today and step up your Emotion AI journey.

Related Materials:

Intetics Created a Machine Learning Algorithm that Recognizes Human Emotions to Improve Wearables for Sport Fans

The post How AI Facial Recognition and Emotion Detection Helps Businesses. Check Yourself with Fun Demo. appeared first on Intetics.

However, some medical companies have long gone side by side with modern applications. One of the worthwhile developments is the Intetics Remote In-Sourcing Team® project, which served a medical company uniting clinics of various specializations. Thanks to convenient tools for scheduling appointments, checking health insurance, and tracking the business income stages, the project increased the company’s profit and helped to serve 5 million patients per year.

Project Features

Intetics Client was a medical company led by a doctor who realized that existing applications or tools for managing medical practice did not meet the needs of both patients and doctors themselves. As a result, the company decided to implement a universal portal that would optimize patient care and medical business development.

The most challenging task was finding a developer who would understand all the healthcare sector specifics because the Client is an expert in the medical field, not an IT professional. The company needed a team that would develop a full engineering cycle from sketch to finished application.

Intetics’ Remote In-Sourcing Team® took on the Client’s idea, starting to develop the specific tools that can work both integrated and separately:

• Collection and retention technologies for clinic patients;
• Automation of routine personnel tasks;
• Creation of patient admission schedules;
• Requesting data from other medical organizations;
• Creation of recommendations for care based on insurance rules;
• Development of a symptom checker and much more.

The Client’s basic request for the healthcare awareness of engineers was met, so the company has been working with the client for 10 years, creating and implementing 100% of their products. Moreover, the collaboration continues to expand — the team of engineers maintaining the portal and other tools has grown from 5 to 50+ specialists.

The Main Objectives

E-health systems consist of elements responsible for data storing, gaining access to e-records by doctors, and developing a unified base of terms, guidelines, and common standards. Thus, the project’s goal was to create an informative, user-friendly, and completely secure portal. In addition, the Client needed various tools to track certain indicators:

• Business profitability;
• The quality of patient care and their satisfaction with the company’s medical services;
• Company productivity and ways to improve it through the automation of workflow tasks;
• The overall efficiency of the company and separately for specialized clinics.

Thanks to this combination of tools, three tasks are solved at once:

1. For a business owner — fulfilling the control over the activities and efficiency of the business.
2. For doctors — keeping medical records as accurately as possible, saving data on prescriptions and medications, and systematizing and analyzing the available information about the patient.
3. For patients — receiving the highest quality medical care and having access to their appointments and e-records.

The project development and the objectives’ achievement required many diverse specialists: team leads, project managers, technical developers, system analysts, QA engineers, and, of course, designers.

Project Creation: Technologies and Solutions

The implementation of the Client’s idea required the use of various technologies:

1. AWS. Amazon Web Services is a massive cloud infrastructure with a host of security certifications – PCI DSS Level 1, ISO 27001, FISMA Moderate, FedRAMP, HIPAA, SOC 1, and SOC 2 verification reports.
2. .NET Core. This development platform allows engineers to create applications suitable for various platforms: Android, iOS, Windows, Linux, and macOS in three programming languages ​​(C#, F#, and Visual Basic).
3. SignalR. It is a library for ASP.NET developers that makes it easy to add real-time components to applications. SignalR also “opens the door” to a new type of web app that requires fast communication with the server. For instance, when doctors request patient information from other healthcare facilities.
4. WebRTC. It is a tool that provides streaming audio data, video data, and content between applications in real-time (important for timely communication of patients with doctors in case of the impossibility of an in-person visit to the clinic). The tool is actively used by such large-scale projects as Google Meet, Jitsi Meet, and BigBlueButton.
5. Entity Framework. It is a database solution for programming in the .NET family of languages.
6. OpenCV. It is a library of computer vision, image processing, and general-purpose numerical algorithms.
7. xUnit. It is a free, open-source unit test tool for .NET with broad community support.

Also, the project’s development required the use of Microservices, React, Swift, Kotlin, HTML5, Java, JavaScript, TypeScript, PHP, WordPress, Kazoo, Google Speech to Text, Web sockets, Vaintiv, ZeroBounce, MS SQL Server, and PostgreSQL technologies.

The client’s request was satisfied in several stages:

• Creation of a program layout from Intetics, which would provide equal access to information for specialists and patients;
• Introduction of the ability to register, change profile settings, add medical information, and upload the necessary documents;
• Launching the symptom checker;
• Adding the function of interaction with other medical institutions to request info about a patient (for example, treatment regimen or reaction to a particular drug);
• Introduction of business instruments.

The last stage was the implementation of business optimization tools and testing the application before the final launch.

Remote In-Sourcing® Team’s Work Result

“The Intetics Remote In-Sourcing Team® helped us start a digital business in parallel with the medical field. We are growing together, and we have big plans. I appreciate the work that the Intetics team is doing for us.”

The result of the company’s work completely satisfied the Client

The Client also noted the general results of the work:

1. The development team created a digital business from scratch, bringing the project idea to life, and now constantly supports the use of the portal.
2. Unlike previous failed attempts to create an integrated system, the new project was crowned with success, as the Client trusted the help of professional vendors.
3. According to the latest data, the annual turnover of patients is 5 million and is constantly increasing.

The entire path of creating a medical portal from the start of work to the launch took 10 months. However, the cooperation did not stop there — the system is constantly updated and supplemented with new useful functions.

In general, the digitalization of medical services is the right way of innovation. Such portals will significantly simplify the circulation of medical documents and increase the efficiency of doctors’ work. Also, special apps will help to make the medical business more successful. The main thing is just to find an experienced vendor to implement the project and support its further usage.

The post Intetics Remote In-Sourcing Team Created and Supports One of the Largest Health Portals in the USA, Serving 5M People a Year appeared first on Intetics.

This year’s award consists of 25 categories divided into four groups, including:

• Project categories,
• Products & Solutions categories,
• Company & Individual categories,
• Special Award for the best emergence from the pandemic used cloud computing to profound effect.

Intetics became a finalist in two categories: Best Cloud Project and Cloud Professional of the Year. 

1. Best Cloud Project

The category is meant for an end-user organization’s most effective cloud project. It illustrates how the use of cloud technology positively affected or even transformed the business. 

Judges were impressed by the featured Сase Study, where the Intetics Remote In-Sourcing® team enhanced the client’s cloud solution by moving to microservices and elasticity. The client’s solution is an international recruitment website with a complex infrastructure. The project involved platform migration to Amazon Web Services. It opened an opportunity to use more than 30 newest AWS services by the project team. 

2. Sergey Dudal, Cloud Professional of the Year

This category recognizes the professionals who excel in pioneering or advocating cloud within a company. With far-reaching effects, it is designed for those who have driven cloud projects, transformation, or simply the company’s direct journey into cloud storage or SaaS. The judges are looking for those who made visible and lasting changes to their business through the cloud. 

Intetics Cloud Solutions Center of Excellence and Project Manager Sergey Dudal became a finalist. He manages a team of initiative experts, willing to gather and utilize best practices, research, support, and training in the cloud industry. Sergey was awarded the Best CoE Leader of 2021 due to his promising initiatives and work within the Cloud CoE. 

Having achieved many breakthroughs in AWS, he keeps growing and assisting colleagues in enriching their expertise in the cloud. Under Sergey’s management, dozens of Cloud and DevOps projects were finished. Each was aimed at delivering the ultimate value to the clients’ businesses.

The award winners will be announced at a live awards ceremony on 22 September at One Whitehall Place, London, UK. Stay tuned!

The post Finalists in 2 Categories: Best Cloud Project and Cloud Professional of the Year. Intetics Participates in Cloud Excellence Awards 2022. appeared first on Intetics.