According to Sphericalinsights report, the global robo-advisory market size was valued at USD 4.13 billion in 2021 and is expected to grow at a compound annual growth rate (CAGR) of 29.7% from 2022 to 2030. The widespread digitalization in banking, financial and insurance sectors is the reason to drive the demand for intelligent chatbots and robo-advisors.  

Intelligent Chatbots – Continuing to Evolve with LLMs and Generative AI 

Chatbots are automated tools stimulating human conversations to answer user queries. They evolved from a simple Q&A interface to intelligent conversation AI with technology innovations such as LLMs and Generative AI. 

Intelligent chatbots powered with neural networks can easily manage open-ended user queries and specific user requests. Some organizations are integrating intelligent chatbots with RPA tools to trigger basic automated tasks for improved customer experience.  

Use Cases of Chatbots in Banking

Automating mundane banking operations – Banking AI Chatbots can automate mundane customer service tasks such as processing account applications etc. eliminating the costs associated with employing multiple representatives. By automating customer support for simple and redundant queries, banks can help their skilled and focused employees to deal with complicated and tricky issues faced by customers. 

Automated Insurance operations – Insurance companies may enhance productivity, cut costs, and streamline processes with the aid of automation and banking chatbots. Underwriting, claims processing, customer support, and policy administration are a few examples of these responsibilities. 
Automation can also assist insurers in offering better customer service by facilitating quicker response times, 24/7 accessibility, and individualized interactions. This may aid in raising client retention and satisfaction levels. 

Automated customer service – Banking AI Chatbots allow customers to have convenient and personalized interactions with their bank, eliminating the need to wait on hold or visit a branch. They can provide helpful advice, manage finances, transfer funds, and answer questions in real-time – making customer service more efficient than ever.  

Robo-Advisors to Automate Advisory for Digital Banking, Insurance and Investment  

Robo-advisors are built on artificial intelligence algorithms trained intensively on a specific subject matter, so they are capable of providing automated intelligent advisory services. Different types of organizations have started adopting robo-advisors as part of ascendant digital and AI culture. 

Organizations from BFSI industry are hugely investing in Robo-advisors, especially investment and capital markets firms are availing them to help their customers with investment advisory and automated portfolio management. 

Use Cases of Chatbots in Banking

Advice or suggestions for banking customers – Robo advisors have established themselves in the banking and financial services sectors to offer personalized services to customers. It also provides better efficiency and diversification. 
As they are designed with algorithms that can swiftly evaluate massive quantities of data and deliver individualized suggestions based on a client’s goals, risk tolerance, and investment preferences, Robo-advisors can be useful in navigating complex transactions. 

Helping in navigating complex banking transactions – Difficult investment management tasks like asset allocation, rebalancing, tax-loss harvesting, and portfolio optimization can be handled by Robo-advisors. These jobs in the past needed a human advisor to invest a lot of time in data analysis and decision-making. Robo-advisors give real-time updates and notifications on market developments and other variables that can affect a client’s investment strategy. And this can assist investors in staying informed and deciding on their portfolio in an informed manner. 

Robo-advisors in insurance policies purchase and claim processing –  Robo-advisors can be used to assist people in locating the best insurance plans depending on their requirements, spending capacity, and risk tolerance. They can also give advice on which policy may be best for a person and assist in helping them comprehend their available options. 
Robo-advisors might be helpful for handling claims as well. They may guarantee that the necessary evidence is provided and assist people in promptly and easily submitting their claims. By evaluating claims data to ascertain whether a claim is legitimate, and if the policyholder is eligible for settlement, robo-advisors can also help with the claims assessment process. 

With Veltris, Equip your Business with Intelligent Chatbots to Deliver Personalized Experiences to Prospects and Customers

Veltris has been providing intelligent conversational chatbots, intelligent virtual assistant, NLP, NLU and NLG powered AI solutions to our customers in different industries.  

Our expertise includes: 

  • Developing intelligent chatbots that learn with every interaction, and they adapt to the nuances of the human users. 
  • NLP solutions that integrate and process data from different channels to deliver conversational chat between users and businesses. 
  • NLP solutions that automate parsing the content, extracting potential business rules, and recommending corrective actions. 

Leveraging our extensive research and unparalleled AI work, we are now providing Generative AI and LLM (Large Language Model) solutions that help organizations reinvent their businesses. 

Artificial Intelligence and Big Data: How they Work Together Artificial Intelligence and Big Data: How they Work Together

Artificial Intelligence (AI) and Big Data are two technologies that aim to shape a future for humanity. These innovations have the potential to drive advancements across tech sectors worldwide. They form a trio, alongside Machine Learning (ML) working together to create outcomes. 

While AI and Big Data can function independently their connection runs deep. Each of these trending buzzwords in the technology industry complements the other, resulting in achievements.

What is Big Data and Artificial Intelligence?

Artificial intelligence is a technology that empowers computers to think and perform tasks like humans. It mimics intelligence. Holds immense promise, for simplifying our lives. Within Artificial Intelligence, two key components come into play – Machine Learning and Deep Learning. 

Machine Learning allows computers to learn from data sets acquiring knowledge that can be applied in situations.

Subsequently, Deep learning helps to create a neural network that is very similar to the human brain network. To illustrate, the intelligence that we can observe in autonomous vehicles and medical robots is based on Deep learning techniques. It automatically detects the situation and makes decisions with the knowledge it acquired from multiple data sets. 

Big data is the driving fuel of all these intelligent performances. Without data, AI cannot do anything but stand as a technology framework. Although it has always been around, the inability to extract and utilize data in the way has overshadowed its importance.

As the name reads it is all about huge amounts of data (text, audio, images) that can be practically analyzed by machines. By strategically analyzing the huge sets of data we can extract required data patterns to predict the future. The source of the data would be multifarious and only by refining it anyone can make use of it. 

Combining Big Data and Artificial Intelligence

The connection between AI and big data becomes clear when we consider how they work together. For instance every search query made on Google is a form of data. Similarly, billions of people generate search queries, on various topics. This collective body of queries constitute Big Data. However, this raw and unprocessed information remains useless until it is transformed into insights. 

Using the appropriate algorithm, these data sets will be analyzed and structured into meaningful insights. Also, the sorted data should be modeled to training machines to enable them to use it for intelligent decision making. By training the computer it acquires more knowledge and the ability to perform the jobs intelligently. According to Bayes theorem AI systems are figuring out the probability of a future event. Analyzing the data history and training the machine to formulate the probability it helps to predict the future event. 

In essence, computers cannot exhibit behavior without analyzing and studying data patterns. Through this process it can produce an output that demonstrates intelligence.

Let us now explore how Big Data and Artificial Intelligence work together:

The practical applications of Big Data and Artificial Intelligence are visible across different industries and business sectors. Particularly, sectors, where no substantial anomalies have detected this technology, can be applied effectively. 

1. E-Commerce Sector

Artificial Intelligence and Big Data have revolutionized the E-Commerce industry by introducing chatbots, suggestions, push notifications and enhanced user experiences. By analyzing user shopping behaviours and purchase histories, AI powered by Big Data provides insights for businesses to drive their operations with a thinking perspective. Also, online retailers can deliver customized shopping experiences while efficiently improving their services.

2. Marketing Industry

In the past, businesses used to spend a huge amount of money on branding and marketing their products. However, things have changed with the emergence of intelligence and Big Data, in the field of marketing technology. 

Nowadays the digital marketing industry operates with a business proposition than making random choices. Experts in the industry are driving marketing campaigns by delivering targeted content to the audience. Many companies are utilizing AI powered content curation models to meet their business content needs.

3. Automobile Industry

Ever since AI has expanded its scope of work on vehicles, it has been progressing behind the scenes. Although it hasn’t reached confidence yet there are experiments and trial runs happening worldwide. Deep learning models are used to train computers in vehicles to make decisions. Moreover, AI technology is responsible for powering features in vehicles such, as radar systems, accident detection capabilities, smart cameras, sensors, lane controls and GPS systems.

4. Smart Gadgets

AI systems ability to recognize voice commands and process natural language is significantly improving people’s lives by making them much easier. 

Today mobile platforms are encouraging their users to embrace the simplicity of voice search to accomplish tasks easily. 

Leading technology companies, like Amazon, Google and Microsoft are devoted to creating speakers that can communicate with users and empower them to control their homes effortlessly. By utilizing data models, machines are being trained to understand users’ voices and tones resulting in the delivery of services promptly. This seamless integration of AI and Big Data has made all these services possible. 

5. Manufacturing Industries

The manufacturing industry is one of the sectors that benefit from AI and Big Data technologies. AI has simplified both complex tasks within this industry making it more productive and less prone to risks. By enhancing the intelligence of robots and empowering them to make decisions, AI has revolutionized how industries operate compared to methods. Additionally, AI has played a role in fostering a production process through collaboration with research and development teams within industrial settings. Moreover, it has led to a reduction in accident rates while improving resource utilization and production capacities on a scale. 

6. HealthCare 

AI powered healthcare has brought forth cost treatment practices that offer solutions for the general public. Innovations such, as telemedicine, virtual diagnosis and robotic surgeries have greatly enhanced the healthcare sectors outcomes. There are ways in which AI and Big Data have revolutionized the healthcare industry. Patients now have the convenience of reducing their hospital visits and can consult with physicians, from the comfort of their homes. Additionally, doctors can swiftly diagnose patients and potentially save lives using intelligent devices during the treatment process.


The connection between AI and Big Data is inseparable as they work together to produce outcomes for purposes. It’s important to note that their impact extends beyond the sectors mentioned here. This partnership has potential to disrupt aspects of our world and human endeavors.

How Artificial Intelligence in E-commerce Has Evolved In 2020 And The Benefits It Has Incorporated How Artificial Intelligence in E-commerce Has Evolved In 2020 And The Benefits It Has Incorporated

Customers are the life-breath of all businesses. Every collective strategy, innovative technologies, the intuitive business design tries to improve the customer experience. The advent of Artificial Intelligence turbo-charged the approaches and helps to frame out astounding business practices at scale. Moreover, by 2025, AI revenue is expected to supersede to $36.8 billion, says the research report by Tractica. 

The personalized replies to customer inquiries, sending reminders about the wish lists and giving tailored alerts on shopping deals are some of it. Moreover, businesses are dynamically inventing new modes of communication to engage customers. AI contributes to the process with more accurate data and enabled eCommerce shops to find the right customers. 

Likewise, the way artificial intelligence (AI) revolutionized the industries are diversified including in the eCommerce, let’s check the gleaming changes AI brought into the eCommerce sector and its benefits.

Customized Recommendations:

Recommendation engines are an inevitable counterpart of online shops. Amazon revealed that around 35% of its revenue is generated by engaging a recommendation strategy. Recommending the relevant accessories and good to have with the purchased product elevates the cross-selling strategy. This further leads to an increase in sales and customer retention ratio.

The popping notification reads “customers who bought this item also bought” are spinning by these engines with appropriate machine learning techniques. Analyzing the previous purchase list and repeated page views, intelligent recommendation engines filter the result and helps all eCommerce businesses to propel the business. This resembles an experienced sales professional who can suggest the best products and accessories. 

Introducing AI to the engines equipped it to make the decision fast and enabled the system to bring forth personalized recommendations.  It is evident from the data that recommendation is making a significant impact on the retail sales process. It embraces user search history, user preferences, and customer behavior. Also, it is dynamic in nature and intelligent to accommodate new user trends and behaviors. 

Personalized Communication: 

Customer communication is the soul process of successful business continuation. Once customers steps into the shop, the way they greeted, navigated and communicated impact a lot to make a purchase decision. 

Here is where the role of intelligent chatbots comes into play. AI-powered chatbots are shifting the conventional mundane customer interaction. With the support of ‘natural language processing and machine learning tactics, intelligent chatbot communicates like real human beings.

Understanding the misspelled words and different styles of sentences, AI chatbots provide personalized communication. Companies are building business-appropriate chatbots to cater to customer inquiries. To initiate interactions, answer doubts, gathering feedbacks, real-time engagement AI is helping eCommerce businesses to upscale their business with the trends. 

Predictive Marketing and Sales:

The art of business forecasting involves complex data analysis and intricate business modeling. It not only burns out the time but also continues to make trouble all the way across the business. The massive surge of data stacking is such a mountainous task to handle with limited resources. 

However, since AI took over the task of data management, businesses could gain significant advantage all across their sales cycle. It prevents the marketing team from misleading data rush on certain seasons and saves plenty of time. Plus, it eliminates redundant data collection and processing. It makes for the productive utilization of big data resources and delivering optimal results to predict business. 

Thus, the AI-enabled data-driven business approach helped them to make accurate lead scoring and sales prospect. Besides, analyzing historical and real-time data, artificial intelligence allows the strategists to formulate better decisions for business growth. Including market trends, demographics, user behavior, seasonal shopping habit of people, AI helps to forecast the sales and therefore enables to frame out an effective marketing strategy.  

Intelligent Visual Search Engine:

The power of visual search is too high to ignore. It might have occurred to anyone-  struggling to find out the solid details of something which has found very fascinating but impossible to go for a deep personal inquiry. However, visual search engines mitigate all the trouble and facilitate to search for anything with a decent snap.

Imagine you are traveling and a stranger is flipping an international home decor magazine. When you ta a glance your eyes get stuck with an amazing wardrobe. You’ve no idea whether just a concept model or a piece for sales and where you can buy it. Getting all the information without trouling the reader is far easy with visual search engine technology.  

The use-cases of intelligent visual search engine technology are numerous. To find the particular people/things from the pool of images, locate a certain product with a snap, to gather up similar product catalog for online shoppers, etc. Thus, visual search engines are revolutionizing web search with new definitions. 

Advanced Voice Search:

Voice searches are becoming more conversational with advanced machine learning patters. Unlike the type search, voice search is more accurate and would give the most truthful answer to the query. As a result, in the eCommerce sector, this game-changing technology offers a fantastic customer experience with the engaging mode of search.

Yet, it works on Automatic Speech Recognition that covers the voice input to text. Partnering with AI, more tech- giants are already made greater leaps in this technology to enhance the web search experience. 

Using intelligent algorithms and data patterns, the process of bringing up the most accurate result is redefining the search engine optimization patterns. There is no need for such a list of search results more, but the most precise voice optimized link will hit the user. In addition, voice search is getting a lot of alterations and expected to come more communicative in the future with advanced AI technology.

Empowered IoT Devices:

IoT hides great fortunes for eCommerce businesses. Since customer data play a prominent role in the eCommerce business, IoT is the very source to gather accurate user information. To formulate personalized user experience, customized product recommendations, market optimization, predict sales leads and simplify the decision making, IoT devices would help eCommerce shops in several ways.

Moreover, the use cases of IoT has been leveraging in eCommerce warehouses as well. Employing IoT sensors to identify inventory and for automated alerts helps companies to prepare themselves for seasonal sales drives. Also, IoT solutions for common people such as Amazon Dash Button simplifies the everyday purchase with its automated reordering service. 

Hyper-automation (warehouse):

The impact of AI is not confined to apps and website use cases, it has more scope across every aspect of an eCommerce business. Hyper-automation of the warehouse is another fascinating benefit of AI for eCommerce companies.  It enables the whole warehousing process more productive with AI-driven intelligent robots. 

Plus, AI helps to automate the whole process in agility. Once a purchase order hits the system, from checking the stock to packing the product to ship will be carried out by these intelligent robots. Thus, eCommerce companies can improve efficiency and productivity to a great extent.  

Augmented Network Security:

Security is a big matter of significance in the eCommerce sector. Any level of ignorance in security policy and practice can spoil the entire reputation. Also, customers are more concerned about their personal and payment data transactions. Though AI it is possible to keep the intruders away and figure out any kind of attack. Further, via deep learning techniques, AI helps security protocols to carry out intelligent action in real-time.

However, cybercriminals are vigorously roaming to eavesdrop customer data stacks. The payment gateways, customer data systems are seems to be the favorite dishes. Hence, analyzing the previous attempts and real-time irregularities in the network, AI can take quick counteraction.

Effective Big Data Management:

The amount of data runs across and process through the e-commerce server is enormous. Including customer data, inventory data, order and dispatch registry and transaction details the list goes long as the business expands. It was a tedious process before the age of AI for it requires clutter-clear data structuring and filtering. 

AI pause no restriction on the data structure to handle it. It gives greater flexibility and accommodates structured and unstructured data in the same location. Moreover, it doesn’t hinder the scalability of the business and quickens the data processing with greater accuracy. 

Automated Content Creation:

 Content is an imperative factor for eCommerce business. Every product requires a clear description to explain how it can solve the problem. Besides, each product has to self testified its features in the most convincing way. It incorporates key keywords and accurate information. Also, it keeps analyzing the content and its effectiveness and alters it as the buyer likes to read.  

AI mitigates all sorts of product content issues on an eCommerce website. AI helps to automate product descriptions and helps to gather the most relevant and recent content from different sources. 


The amazing makeover that eCommerce shops made through AI and its allies are as vivifying as it is. Also, it is evolving day by day. In the near feature, we can witness momentous advancement across the eCommerce shopping experiences such as immersive shopping and autonomous last-mile delivery services and etc. 

How AI is on the cusp of a Data Revolution? How AI is on the cusp of a Data Revolution?

How will it transform the world as we know it? 

While Artificial Intelligence sounded like a clarion call from a dystopian sci-fi society a few years ago, it has permeated into our everyday lives to seamlessly enhance how we search, purchase and communicate. Artificial Intelligence is the ability to use algorithms to create predictive models from copious amounts of data by machines, which then use these inferences to make recommendations that are personalized and highly accurate. AI technologies are already powering brands to engineer a better consumer experience like the “product recommendations” we see after browsing Amazon, or similar playlists lining up on your music app. All these are examples of AI in action. 

To a layman, Artificial Intelligence evokes images of futuristic self-driving cars and robots laboring in operation theatres, but machine learning is following a similar trajectory to digital marketing or cloud computing, that means AI will soon be embraced in all business models to understand consumer behavior to give them exactly what they need. 

AI is still in its nascent stage but it is already driving a plethora of industries to achieve the previously impossible. Machines can amplify our cognitive strengths, enhance the amount of data we can process, and cut down the time required to conduct higher-level tasks to an unimaginable level. This is why Customer Service companies are deploying AI to facilitate conversations through chatbots, present personalized customer service by scanning huge data and quickly transcribing the best response. AI intervention increases the volume of requests handled many-fold, which would otherwise require more human resources.

 AI is also behind the “suggested responses” to messages on android devices which are recommended after sifting through millions of similar conversation examples and learning patterns of the appropriate responses. The ability to find addresses through digital maps in intricate localities is due to the AI that has learned to read street names and addresses from billions of street view images. AI basically reduces complexity and gives users the most relevant results. 

Apart from making buying easier, AI is also revolutionising the medical field, where the time is taken to diagnose and screen diseases is greatly reduced by machines that aggregate the patient’s medical history, running it against similar complexities from millions of patient’s records to define what is wrong, and give quick suggestions that are life-saving. AI can also analyze a patient’s medical history and inputs about their lifestyle to predict potential dangers. 

AI reduces the chances of error, which can sometimes cost companies millions of dollars, as in the case of fraudulent transactions. HSBC uses AI to detect fraudulent transactions in which humans would take ages to scan, as millions of transactions take place every single day! The AI uses information like IP addresses, customer behavior and history of the customer to detect fraud, and this has significantly reduced the rate of fraudulent transactions in the US, ever since HSBC implemented AI there. The AI is also programmed to flag down questionable transactions for humans to evaluate.

In China, AI is being used with mass-surveillance to address issues of public safety, respond to crimes using AI facilitated facial recognition. 

AI is transforming heavy factories where robotic arms can carry out unprecedented levels of customization, following new directions in which a human can reprogram using a tablet. The inexhaustive agility of machines and the creativity of a human is being used to augment an AI that follows the nuances of a robotic worker that completes mammoth physical tasks without exhaustion. 

This would undeniably increase productivity by leaps and bounds. 

Artificial Intelligence is the future. In business, AI can optimize internal business operations, enhance features of a product, carry out relevant market research with accuracy and even optimize sales by pushing personalized marketing to customers. In the agriculture industry, AI can predict future crop yields by analyzing enormous amounts of data about soil properties, historical harvests, weather patterns, etc. Watch out for our upcoming blogs on Artificial Intelligence and how this technology is predicted to redefine software development, support, data privacy, etc. 

At the moment, our tryst with AI pertains greatly to our smartphones and devices, but soon AI would be instrumental in diagnosing potential diseases, warning against natural disasters or helping solve major problems like water depletion. The synergy of machine learning and human creativity will achieve what humans alone could not fathom. From predictive searches to AI-enabled market research, the AI revolution is on the cusp of changing how we commune with the world around us.

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