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“My transition from SWE to Data Science/AI is still not complete; I am working on it every day.”
Being a Kaggle Grandmaster in any category is a function of daily practice. Such iteration can only ensure the sharpening of your skills and make you industry-ready.
In the 13th edition of the Kaggle Grandmaster Series, we have Peter Pesti joining us.
Peter is a Kaggle Notebooks Grandmaster and currently ranks 23rd with 15 gold medals to his name. He also holds a Master title in the Discussion category and an Expert title in the competitions category.
You can go through the previous Kaggle Grandmaster Series Interviews here.In this interview, we cover a range of topics, including:
Peter’s Education and Work
Peter’s Kaggle Journey from Scratch to becoming a Kaggle Grandmaster
Peter’s Advice for Beginners in Data Science
Peter’s InspirationsPeter’s Education and Work Analytics Vidhya: You’re a Senior Software Engineer by profession so please tell us how did your interest in Data Science and Machine Learning grow? Which sources/tools helped you in learning Machine Learning?
Peter Pesti: In the past 18-20 years, I have worked as a Software Engineer/Software Developer for many different companies. It was a great 20 years; I have worked with many excellent developers/engineers, and I have learned a lot during these years. We’ve made various software from small mobile applications to large scale ERP systems.
Honestly, I worked too much. About 4-5 years ago, there were periods when I sat in front of my monitor 13-14 hours every day. Not surprisingly, I burned out. I knew it was time to take a break and do something else.
At that time, I read about AlphaGo Zero. After I read that article, I was amazed at the level of A.I. The same day I bought my first Machine Learning Course on Udemy. I did not know what I was jumping into. The first course led to another, etc. Since then, I’ve learned a lot about ML/DL/AI. I’ve finished many online courses on Udemy, Udacity, Coursera, Edx.
My transition from SWE to Data Science/AI is still not complete; I am working on it every day.
Peter’s Kaggle Journey from Scratch to becoming a Kaggle GrandmasterAV: You’re one of the 36 Kaggle Kernel Grandmasters, That’s amazing! Can you list down the challenges you faced and how did you overcome them? What are the other possible challenges that one might encounter while creating any notebook?
PP; I think there are two main types of challenges when you want to write successful notebooks.
The first is a technical one. You have to write the code. When I wrote my first Kaggle Kernel, I made lots of rookie mistakes even though I had 20 years of programming experience. At first, it takes more time to write a simple notebook. You will make bugs; it will hard to read; the formatting will be messy, etc. If you don’t give up and practice, you’ll be better and better with time. You will have more and more reusable code, and eventually, you will be able to publish GM level kernel within an hour.
For me, the more difficult challenge was a non-technical one. When I first published it, I thought I wrote an excellent notebook, and I got only a few votes. Timing and a bit of marketing are as much important as the code itself. For example, if you write an EDA kernel for a competition weeks before the end, you won’t get any votes.
After these failures, I wrote an explanation kernel for some scoring metric Kaggle used for an ongoing competition. There was a bit of a misunderstanding about how they calculated. I thought it would be useful for others too, I did not expect that kind of success. I gave more than 100 votes and my first gold medal.AV: Among your kernels/notebooks, which ones would you recommend for beginners?
PP: EDA Kernels. In my opinion, data analyzing skills are a must for every Data Scientist. But before that, every beginner needs good coding skills. You don’t have to be a Python expert, but you will need a bit of confidence to write the necessary python codes. You will also need to learn a few libraries, like Numpy, Pandas, and a plotting tool, Matplotlib or chúng tôi for example. After you have these basics, you can start writing your own EDA notebooks.
PP: Most of the shared content on the discussion forums are related to some competition. For a beginner, for educational purposes, these topics are not useful. One exception may be the write-up topics. Lots of teams share their solution after the competition ends.
I think online courses are much more valuable for a beginner. There are many MOOC and e-learning sites from which you can choose. Udemy, Coursera, Udacity, Edx, KhanAcademy, Kaggle, and Analytics Vidhya, to name a few; Infinite possibilities.AV: Please share your check-list/approach to build an expert level notebook.
I have lots of reusable code for various notebooks (EDA, Starter kernel, metric explanations, etc.) I usually copy-paste all of it and start to adjust it to the given problem.
After I have a quick draft, I add some extra if it is necessary. For example, EDA notebooks are usually different because of different data. Most of the time, I can add a few additional plots to the notebook.
Next, I always test the code. I am looking for bugs or miscalculations.
After everything is working, I clean the code and write the documentation (code and explanation; why-s and how-s).
After I commit the Kaggle Notebook, I always check its output. There still could be errors or formatting issues. If there is anything that I don’t like, I fix it before I publish it.
After I publish, many times, I write a topic on the discussion forum. It is a bit dangerous; The community does not like self-promoting.AV: What tips would you give to the beginners who want to attain higher ranks in the Notebooks category?
Quality over speed. As a beginner, you won’t be able to compete with GrandMasters. Starter kernels and EDA-s are the most popular ones, but you have to publish fast. I’ve seen many notebooks from beginners with a few plots and a big text: “Stay tuned, I’ll update this notebook.” Don’t do that.
Do not copy/fork other people’s work. If you want to build your reputation, these kinds of shortcuts won’t work. If you are not the author of at least 85-90% of the notebook, you should not publish it.
You should publish only clean, well-formatted, well-documented codes. It clearly shows that you care about your work.
Prepare your code months before publishing. For example, I made an Object Detection training kernel three months before I published it. I shared it hours after the competition started, and it achieved a gold medal within days.
Be patient and consistent. If you work hard and don’t give up, you’ll be Kernel’s Grand Master in no time.Peter’s Advice to the Beginners
PP: It is challenging to keep up with everything; so much is happening in the industry every day. I think the only way if you choose a small part and focus on that. After I learned the basics in many areas (Computer Vision, NLP, Time series, Reinforcement Learning, etc.) I started to focus on computer vision. I read a lot about this topic every day. If I have time, I read some new papers on arxiv. Besides my job, Kaggle, learning, and my personal life, I don’t have much time left, but I do my best. I keep hundreds of open tabs on chrome 🙂AV: You can ask, as an experienced industry leader, how often do you see DL being applied to a problem and what future trends do you foresee in this regard?
It is hard to predict, but I think the change will be dramatic in the next 10-20 years.
PP: Learn, learn, learn. This industry is changing so fast, so what you’ve learned at a university won’t be enough five or ten years from now.
Building a professional online portfolio is a great way to show your knowledge. Be active on Kaggle; your goal should be at least one GM title. Three is better 🙂 Open source coding is also a good starting point.Peter’s Inspirations AV: Who are the Data Science experts whose work you look forward to?
Outside of Kaggle, I am trying to read as many blogs and articles as I could. I read everything from Google Brains, Facebook AI, OpenAI, Uber. Occasionally, when I have a bit more time, I read interesting, new arxiv publications.End Notes
Peter’s journey is a testament to the fact that you have to work on your knowledge and base every day to be a data scientist. I hope this interview gives you some important lessons for you to apply in your personal journey.
This is the 13th interview in the Kaggle Grandmasters Series. You can read the previous few in the following links-
You're reading Kaggle Grandmaster Series – Exclusive Interview With Kaggle Competitions Grandmaster Peter Pesti (Rank 23!)
Chasing a legal case requires meticulous planning, analysis, and detecting anomalies all along its course, which may take years, and in some cases, decades to conclude. Legal analytics is a branch of data science that is proving to be of immense help to attorneys in their legal work. Lex Machina, is a legal analytics firm that leverages analytics and data combined with attorney inputs to come up with rare legal insights. Analytics Insight has engaged in an exclusive interview with Aria Nejad, In-House Counsel, of Lex Machina.Kindly brief us about the company, its specialization, and the services that your company offers.
Lex Machina’s journey from a small venture-backed start-up in 2010 to its position in 2023 as the leader of the legal analytics movement demonstrates how quickly and profoundly data-driven decision-making has transformed the business and the practice of law in the United States. In short, we provide legal analytics to law firms and companies. We enable them to craft successful strategies, win cases, and close business. The practice of law is highly competitive and we help litigators gain an edge using the most accurate legal analytics in the industry. We process litigation data and reveal insights never before available about judges, lawyers, parties, and the subjects of the cases themselves. We call these insights legal analytics because analytics involves the discovery and communication of meaningful patterns in data.
With this data, for the first time, lawyers can predict the behaviors and outcomes that different legal strategies will produce. Our clients also use Lex Machina to land new clients by providing winning pitch decks that demonstrate specific subject matter expertise, familiarity with opposing parties and counsel, experience in front of a specific judge, and available bandwidth. Corporate counsel uses Lex Machina to select and manage outside counsel and set litigation strategies and tactics.Mention some of the awards, achievements, recognitions, and clients’ feedback that you feel are notable and valuable for the company.
Lex Machina was named “Greater Bay Area Top Workplaces 2023” (The San Francisco Chronicle), “Legal Tech Company of the Year 2023″ award (CIO Review), and “2024 Legal Technology Trailblazer” (National Law Journal Trailblazer Awards, 2023), Winner of the “Media Excellence” Award for Analytics/Big Data (13th Annual Media Excellence Award, 2023), “Best Decision Management Solution” (AI Breakthrough Awards, 2023), and “Disruptor of the Year” (Changing Lawyer Awards, 2023). We consider feedback from satisfied clients as the greatest award. They often use Lex Machina to evaluate the viability of the defendant, check their legitimacy, or predict their response to litigation, and at times allow them to respond to clients’ queries with insightful inputs.What is the edge your company has over other players in the industry?
Lex Machina focuses on outcome analytics – what happens in cases like yours – something that none of our competitors or their products specialize in. Outcome analytics include remedies, findings, case resolutions, and damages. Unless you know about the possible outcomes for a proceeding, you cannot design a winning formula for litigation success. That is something unique to Lex Machina. Since Lex Machina created legal analytics approximately ten years ago, several established legal publishers have released tools they call litigation analytics. Most of these take available court data at face value and present this information as graphs and charts, without doing the heavy lifting of reading, cleaning, categorizing, or fixing the many errors the raw litigation data contains.Please brief us about the products/services/solutions you provide to your customers and how they get value out of it.
If the case moves forward, legal analytics can present critical insights into the behavior and track the record of the opposing law firm and its lawyers, showcasing their success rates in contract breach cases both on the plaintiff and defendant sides. You will see how long similar contract breach cases have taken in your particular venue, in front of a particular judge, and against the company your client is looking to sue. You can learn at what point the cases were terminated, such as at summary judgment or trial. Last but not least, the data can illuminate potential damages that have been awarded in similar cases so you can weigh the potential risk against a possible windfall. Timing and damages data are critical for lawyers to estimate how much a legal matter might cost.What are your growth plans for the next 12 months?
State court expansion remains a top priority at Lex Machina. We’re adding modules on a court-by-court basis, with an emphasis on strict data quality and integrity. We currently offer legal analytics for 27 state courts, which encompasses over 3.3 million individual cases. We are proud of this key achievement in our state court journey and will continue to grow our coverage over the next year and beyond.
We recently launched our State Motion Metrics which helps users quickly assess their motion strategy and easily identify winning arguments. This is our first feature using a cutting-edge deep learning model. Lex Machina has released State Motion Metrics for the four Delaware state courts, including the Delaware Court of Chancery, as well as Los Angeles County Superior Court, with additional plans to roll out State Motion Metrics in more courts later this year.How does your company’s rich expertise help uncover patterns with powerful analytics and machine learning?
We do the heavy lifting of reading, cleaning, categorizing, or fixing the many errors that raw litigation data contains. We use natural language processing and machine learning to enhance our litigation data. This is the first step in gathering raw information, reading and analyzing each court document, correcting erroneous data, and supplementing the missing data. We use signature block analyzers to update and add the correct law firms and attorneys to all the cases they worked on, even if they don’t appear on the face of the docket sheet.
But we go even further. To be completely confident in our analytics, we supplement our technology with the second step of human attorney review. Every single Lex Machina employee who reviews cases has a legal background. We use a cutting-edge deep learning model to create the new State Motion Metrics, and Lex Machina’s attorneys apply and test the model for accuracy and completeness.
leader in Contact Centre Software solutions, NovelVox is treading fast in digital communication by redefining the way integration of multiple enterprise communication tools is applied in CRM and other client-centric domains. Its latest product, CXInfinity developed as an omnichannel conversational AI platform is the case in point. Analytics Insight has engaged in an exclusive interview with Amit Gandhi, founder, NovelVox.1. With what mission and objectives were the company set up? In short, tell us about your journey since the inception of the company?
NovelVox is essentially an outcome of my over two-decade-long experience in the software application development space, especially in the domain of Contact Center Software Applications and Integrations. The company has, since its inception, been working to address the most critical contact center integration difficulties. We offer tools to integrate an industry’s core applications – a solution optimized for any specific industry segment. We developed the first Agent Desktop Designer Studio with a drag-and-drop designer in a low code model. Our solutions do not entail agents to work on one contact center platform, access client information through CRM, accept requests in a different ticketing tool, and use other technologies, as they get a comprehensive tool at their disposal right on their screen.
Years later, NovelVox came up with CXInfinity, an Omni-channel messaging and conversational AI platform suited for all major industries. It comes with core integration and pre-built use cases to ensure optimum performance.2. What is your biggest USP of the company? 3. How do you plan to revolutionize the Indian/US market and tap the market?
If we look at the Indian and US markets scenario, we would hardly discover any difference, for both markets have similar needs. Hence, we stick to our motto of the quicker resolution, thereby intermittently introducing newer products that serve the purpose in small and big ways. It is no short of a revolution that NovelVox is currently offering the biggest integration library, enabling ready integration with more than 75 business applications, including core system integration for banking, healthcare, and credit unions, among others. We’ve enabled integrations with the industry’s major third-party applications to unify caller information while streamlining industry solutions by delivering industry-specific templates and customizations for faster responses and improved customer experience.4. How do you see the company and the industry in the future ahead?
As the contact center market is expanding rapidly, we endeavor to continually add new products corresponding to fresh concerns and demands. With data analytics becoming increasingly popular today popular in today, every firm would like to rely on it. To obtain insight into their company’s weaknesses and strengths. This massive amount of data will necessitate cloud storage as well as computing, which is exactly what we too are working on right now. Regarding the future, chatbots and voice bots are slated to capitalize on the trend.5. How are disruptive technologies like AI/Machine Learning/Cloud Computing impacting today’s innovation?
The havoc wreaked by Covid made us all realize how much we rely on healthcare and how important it is to have a system in place that is readily accessible when needed.
As a result, Artificial Intelligence and all of our goods will disrupt traditional sectors and infiltrate previously unimaginable venues. AI, ML, or Cloud Computing disrupt traditional industries and seep into arenas that were unthinkable just a couple of years ago.
For instance, we are already penetrating the healthcare and retail sectors and the next in line is the F&B industry. The idea is for everybody to benefit from the available innovative solutions. Hyper-Personalization within sectors such as the E-Commerce industry and New AI and ML Innovations with NLG is another innovation creating waves.6. Which industry verticals are you currently focusing on? And what is your go-to-market strategy for the same?
For over a decade, we have been offering customized solutions for different industries, including healthcare, banking, retail, insurance, etc. For example, we enable healthcare providers to offer exceptional patient experiences and increase operational efficiency. Integrated desktop designed especially for healthcare providers gives agents access to centers such as EPIC, Cerner, Aetna, Allscripts, Telmed IQ, and other core platforms, instant access to caller information like the last appointment status, the reason for the call, and doctor’s availability.
The integrated agent desktop works seamlessly with core banking applications for banking purposes to ensure a responsive CX and enhance value. Speaking of strategy, we would reiterate that we develop ready-integration solutions on a need-based proposition specifically for different industries.7. Kindly share your point of view on the current scenario of Big Data Analytics and its future.
For retail industries, warehouse automation is a must-have feature. It makes the whole process of transit a lot easier than ever.1. Please brief us about the products/services/solutions you provide to your customers and how do they get value out of it.
We provide warehouse automation solutions to companies across different industries and scales. If you look at it, warehouse automation is the most pertinent requirement for any business that deals with bulk items and goods. There are key components to it such as in-bound and out-bound transit, storage and minimal manual intervention. We are introducing the latest warehouse automation technologies like ASRS, AGV and ACR to make the automation process more efficient and smarter. Recently, we have launched an Autonomous Case-handling Robotic (ACR) system that can significantly enhance both the inbound and outbound efficiency of a warehouse. This ACR system will increase warehouse operational efficiency by 3-4 times and storage density by 80%-130%. The system is loaded with smart features, thereby providing higher flexibility for various warehouse application scenarios.2. With what mission and objectives, the company was set up? In short, tell us about your journey since the inception of the company. 3. What is your biggest USP that diﬀerentiates the company from competitors?
In addition to our lineage to the industry, we offer the companies turnkey solutions for warehouse automation, including high-end ACR (Autonomous case handling and robotic) systems, ASRS (Automated storage and retrieval) systems, sortation systems, pick to light systems, conveyor systems etc. Strong R&D capabilities, global sales and service network, customized solutions are also a major part of our USP.4. How do you plan to revolutionize the Indian market and what are your plans to tap the market?
We are identifying the specific needs of different industries when it comes to warehouse automation. The fastest adopting industries we have seen are E-commerce, 3PL and FMCG industries while others like logistics or postal and courier handling are gradually being more adaptive. To prepare for the future, we are focusing on the evolution of Warehouse Management Systems (WMS), Industrial Internet of Things and AI. We are offering solutions that will reduce high costs associated with managing inbound and outbound inventory in a warehouse.5. What are your growth plans for the next 12 months?
We have created a loop system, where first we review our past and current business performance to identify the areas of growth and make a future roadmap accordingly. For the next 12 months, we want to acquire new projects in-commerce, 3PL, FMCG industries and increase our customer base at the end of the period. We have decided to increase our R&D budget by investing more amounts in new product development and technology. In the upcoming months, you will be able to see new products in our catalogue for the warehouse automation sector. In the next 12 months, we’re focusing on setting new benchmarks for sales and profit with an increase in overall market share.6. How do you see the company and the industry in the future ahead?
A plan is in place to open a new factory and experience centre in the coming year, where we would showcase next-generation warehouse automation as well as material handling solutions. We also intend to open sales offices in major Indian cities as well as abroad. The industry as mentioned earlier needs to focus on the latest innovations like AI, IoT and Blockchain.7. What is your ‘Leadership Mantra’?
There is no secret formula of being a good or unique leader, the only thing matter is you have to believe in yourself. Ask and listen to the people around you, their problems, concerns and what motivates them to believe in you and your vision.
For retail industries, warehouse automation is a must-have feature. It makes the whole process of transit a lot easier than ever. Atmos Systems is a company that provides warehouse automation solutions to companies across different industries and scales. Analytics Insight has engaged in an exclusive interview with Khursheed Alam, Co-Founder, Atmos chúng tôi provide warehouse automation solutions to companies across different industries and scales. If you look at it, warehouse automation is the most pertinent requirement for any business that deals with bulk items and goods. There are key components to it such as in-bound and out-bound transit, storage and minimal manual intervention. We are introducing the latest warehouse automation technologies like ASRS, AGV and ACR to make the automation process more efficient and smarter. Recently, we have launched an Autonomous Case-handling Robotic (ACR) system that can significantly enhance both the inbound and outbound efficiency of a warehouse. This ACR system will increase warehouse operational efficiency by 3-4 times and storage density by 80%-130%. The system is loaded with smart features, thereby providing higher flexibility for various warehouse application scenarios. Atmos Systems has a strong and more than 30-year-old DNA in the development of automation solutions for manufacturing industries under the brand Saifi Con-Fab System Pvt Ltd. It has an excellent client portfolio like Hero MotoCorp, Escorts, Honda, Godrej, Eicher, Hindustan Petroleum etc. To ensure that we provide our expertise in a dedicated manner to different industries that need warehouse automation solutions, Atmos Systems was founded in the Year 2023. The decision was taken after thorough R&D for at least two years. It reaffirms our seriousness as well as expertise while narrowing the approach for a niche chúng tôi addition to our lineage to the industry, we offer the companies turnkey solutions for warehouse automation, including high-end ACR (Autonomous case handling and robotic) systems, ASRS (Automated storage and retrieval) systems, sortation systems, pick to light systems, conveyor systems etc. Strong R&D capabilities, global sales and service network, customized solutions are also a major part of our chúng tôi are identifying the specific needs of different industries when it comes to warehouse automation. The fastest adopting industries we have seen are E-commerce, 3PL and FMCG industries while others like logistics or postal and courier handling are gradually being more adaptive. To prepare for the future, we are focusing on the evolution of Warehouse Management Systems (WMS), Industrial Internet of Things and AI. We are offering solutions that will reduce high costs associated with managing inbound and outbound inventory in a chúng tôi have created a loop system, where first we review our past and current business performance to identify the areas of growth and make a future roadmap accordingly. For the next 12 months, we want to acquire new projects in-commerce, 3PL, FMCG industries and increase our customer base at the end of the period. We have decided to increase our R&D budget by investing more amounts in new product development and technology. In the upcoming months, you will be able to see new products in our catalogue for the warehouse automation sector. In the next 12 months, we’re focusing on setting new benchmarks for sales and profit with an increase in overall market share.A plan is in place to open a new factory and experience centre in the coming year, where we would showcase next-generation warehouse automation as well as material handling solutions. We also intend to open sales offices in major Indian cities as well as abroad. The industry as mentioned earlier needs to focus on the latest innovations like AI, IoT and Blockchain.There is no secret formula of being a good or unique leader, the only thing matter is you have to believe in yourself. Ask and listen to the people around you, their problems, concerns and what motivates them to believe in you and your vision. It’s the responsibility of a leader to care more about the success of his/her followers than their own success. Avoid unethical behaviour and don’t hesitate to praise your team members in front of others. Recognize the potential of others and give them a chance to become a leader and guide them towards the path of success. As long as you and your team are learning, there is a high scope of organization growth and development.
Most of the organizations currently focus on making their support conversation as cost-free as possible. chúng tôi is a one-stop solution for any brand looking to automate its support conversations. Analytics Insights has engaged in an exclusive interview with Gaurav Singh, the Founder, and CEO of Verloop.io.1. Kindly brief us about the company, its specialization, and the services that your company offers.
Verloop.io is a Conversational AI product for customer support teams. We enable B2C brands to automate, personalize and scale support conversations. From enabling automation on multiple channels (Web, WhatsApp, FB Messenger, Instagram, and many others) to provide a platform for live agent chat, chúng tôi is a one-stop solution for any brand looking to automate their support conversations. We started in the year 2023-18 and we have seen great adoption with brands like Nykaa, Decathlon, Lido Learning amongst other global brands such as ADIB and Landmark Group. The company is now investing in NLP super bots that are powered by AI and can support 92% of all customer queries without human intervention. These super bots can enhance the customer experience by 10 times and allow them to converse in multiple languages and even switch between languages. chúng tôi already supports 14 languages including Hindi, Arabic, Konkani, Tamil, Telugu, Kannada, and Hinglish (Hindi and English). The NLP super bots will be able to raise this number to 20 in the coming days.2. With what mission and objectives, the company was set up? In short, tell us about your journey since the inception of the company?
Customer Support, unlike marketing and sales, has been underserved with technologies for a long time. In the past decade and a half, brands have channeled their energies towards customer acquisition and growth. The ruling mantra had been ‘growth at all costs’ Things have started to change now as brands are now pivoted towards growing profitably. The laser focus has now shifted to retaining customers and retention starts at the customer support level. With multiple products and brands to choose from, if a brand is unable to build delightful support, customers can switch very fast. Also, in the last 10 years, most of the technology developed for customer support is internal facing/process optimization – ticketing, QA sampling, etc. None of them enable brands to build delightful customer experiences. This is the genesis of Verloop.io We are on a mission to become the operating system for customer support. In a nutshell, we strive to be the technology that brands adapt to enable their support teams in order to deliver delightful support experiences.3. What were the major challenges the company has faced till now?
When we started out, the awareness around Conversational AI enabling customer support teams was very limited. It was perceived that Conversational AI is a simple FAQ answering chatbots. Hence, we had to do a lot of awareness building in the industries. Also, a lot of clients did not see the value a Conversational AI partner brings to the table, as they kept going back to the simple FAQ or IVR bot. However, now with awareness and pilot concepts, brands are looking to actively invest in this technology. There were also some internal challenges that we had to battle. One such challenge was hiring the core team. With the SaaS space heating up, talent was always going to be in demand. However, with chúng tôi expanding its footprint globally and the opportunity to build Conversational AI at scale, we have a very good leadership team in place now.4. Can you brief us about Verloop.io’s contribution to the Conversational AI industry?
Verloop.io Conversational AI uses AI-powered technologies like chatbots to interact with people in a human-like manner, automate customer experience for large enterprises, and offer real-time and on-demand resolution and information. We aim to democratize AI by offering no-code/low-code bot builders, omnichannel virtual assistants, ticketing automation, etc. As an AI-based bot platform, Verloop is providing bot analytics, bot builder, and agent chat platform. Even the chatbot personalization is completely based upon the client’s user interactions. This definitely gives us the edge in achieving a higher milestone in customer experience across sectors.5. How is your company helping customers deliver relevant business outcomes through the adoption of the company’s technology innovations?
When you look at the customer support function in any B2C brand, you will notice three things
Knowledge is in siloed systems and high-performance agents. There is not a single source where this information can be obtained for. Combined with churn a lot of organizational knowledge is lost.
Verloop.io helps brands enable them to answer data-driven queries without interfacing with customer support, enabling live agents to access all information from a single platform and increasing agent efficiency through historical and contextual customer information Brands that have adopted Verloop have seen a 2x increase in their ‘Customer Satisfaction Scores (CSAT) and a 5x increase in the agent effectiveness within 3-6 months. This has also resulted in a significant drop in call volumes to call centers, as automation deflected a lot of queries. This in turn has resulted in annualized cost savings of more than $1Bn dollars across our clients.6. Which industry verticals are you currently focusing on? And what is your go-to-market strategy for the same?
We are focused on industries where there are large volumes of pre-sales and post-sales support required. This typically includes banking, financial, insurance, retail, e-commerce, EdTech, travel, logistics, food tech amongst many others. In terms of our go-to-market strategy, we typically focus on showcasing the value automation across voice and chat brings to the clients. This typically starts off by automating a certain portion of queries and then expanding as the brand deems fit.7. How is conversational AI evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe?
Online businesses are expanding to previously untapped markets across the globe and with this customer services are also growing at an exponential rate. The rise of natural language processing and deep learning technologies in the last 10 years has given a new amplitude to simulate human conversation and dialogues. There are businesses of all types that are investing heavily in innovating new ideas to delight the customer, achieve excellent net promoter scores and reduce their customer service cost. Conversational AI chatbot is helping customer-facing brands to move from a messenger service to a quicker automated and personalized multi-lingual live chat platform via different social media channels. Deciphering complex scenarios, knowing customer’s previous context and history, understanding human sentiments and training company-specific live chat data are equally important to improve the self-service accuracy and security standards of any Conversational AI chatbot. Even lead generation, business tools, and API integration can be a major relief for any company to provide accurate customer experience, increase sales, provide multi-channel support and improve organization efficiency. Nonetheless, millennials today prefer hands-free conversations to text-enabled bots, which can be building voice assistants and next-gen AR can take the engagement level and usage to the next heights.8. What’s your growth plans for the next 12 months?
We have seen great adoption with brands like Nykaa, Decathlon, Lido Learning amongst other global brands such as ADIB and Landmark Group. However, chat forms a certain percent of customer support and there are other channels through which conversations happen as well – we are now looking at building products that can help brands automate those channels and are able to truly deliver a seamless support experience. In terms of geographical expansion, our first and second phase of growth was in the Indian subcontinent and the Middle East from which we have seen great adoption across India, GCC (UAE, Qatar, Saudi, etc.), South Africa, and Southeast Asia (Indonesia, Philippines, Malaysia, and Thailand). In the third phase, we are planning to expand our presence in the Americas (North and South America) and Europe. We aim to establish a global footprint by 2023 and enable brands to build a truly delightful support experience for their customers.9. How can businesses efficiently extract the value from data, without increasing cost and complexity?
Over the past decade, data has become a moat – a major source of competitive differentiation for businesses. As the pandemic plays out, retention is becoming the growth strategy for a lot of brands as they look to lower their acquisition costs. And the retention starts with customer support. Leaders will need to answer many questions as they work to not only digitally transform their customer support and also chart out the next phase of growth. One important question in this regard is: What is the best way to engage, serve and support a more digitally engaged transient customer base? Answering this question and other related ones requires lots of data and the know-how to use it effectively. Businesses will need to model information from more sources, apply insights over more channels, and do all of this continuously while ensuring that the data are clean, privacy is protected, and compliance responsibilities are met. Building the capabilities to do this comes at a cost. Most companies will have to modernize their data architecture, ingest data from novel sources, design algorithms to model data and derive insights, and hire or train the talent to do it all. For a mid-size organization, the price tag for these efforts can run into millions and billions of dollars for large size companies. With bottom lines already under pressure from the pandemic’s economic fallout, businesses might wonder where they can find the resources to meet that funding requirement.10. Tell us a little about your journey as a Founder and how did you think about starting Verloop.io?
The emergence of cutting-edge technologies has encouraged the fintech industry to transform traditional modes of payments into smart ones in this tech-driven market. Technologies are invented to help in seamless transactions at a faster speed through glocalization across the world. Customers have started preferring multiple cost-effective methods for payments purposes. This is an exclusive interview with Digvijay Singh Baghel, Senior VP of Technology, Innoviti Payment Solutions, who has elaborated how Innoviti is becoming a pioneer company to provide necessary help to businesses in extracting better value from valuable transactions efficiently and effectively through its self-healing technology.1. Kindly brief us about the company, its specialization, and the services that your company offers
Innoviti Payment Solutions Pvt. Ltd. is India’s largest payment solutions provider to enterprise merchants, with a 76% market share of all payments happening in this segment. It has been a pioneer in using technology to help businesses extract better value from retail transactions than anyone else. The company processes over US$10 billion of merchant payments from over 1000 cities with a volume throughput per installation 2X of the country’s average. Bessemer Venture Partners, USA, FMO, Netherlands, and Catamaran Ventures, India are investors in the company. The company has several patents filed for with three awards— Innoviti won Mastercard’s Innovation Wizards Award, Reliance’s Most Promising Growth Consumer Finance Award and Deloitte Fastest Growing Companies in Asia award in 2023. Innoviti is the only Indian payments SaaS company to be awarded the coveted SOC3 seal of excellence for adherence to principles of trust in privacy, security, confidentiality, availability, and processing of transactions.2. What is your aim and vision with Innoviti?
The vision with Innoviti is to fuel the growth of merchants by using payment technology in unconventional ways to attract more walk-ins, drive more conversions, and enable more capital. Banks, brands, and consumers have encouraged payment technology used in all channels right from U.P.I., peer 2 peer, digital wallet, mPOS, and voice payment. Today payment platforms are not the only mode of transactions but have also assisted merchants to increase their revenues by introducing more innovative campaigns and offerings like zero cost E.M.I., flexible E.M.I., B.N.P.L. (Buy-now-pay-later), cashback, etc. At Innoviti, the team always keeps customers at the center and has designed products to provide them with a seamless, innovative, and cost-effective payments experience. It has continuously evolved the product offerings via tech innovations, empowering merchants, banks, and brand partners to provide better customer service.3. What are the types of technologies that Innoviti has been using?
Innoviti designs products focused on extracting better value out of a payment transaction than anyone else. The company recently announced, G.E.N.I.E., a smart marketing application for local mobile dealers to help them fight back online by bringing the same technology used by online merchants to attract consumers. This product supports conventional brand E.M.I. schemes and unique and exclusive E.M.I. and cashback schemes not even available online. Innoviti is leveraging on various low code application platforms (LCAP), using which our merchants and partners can design various campaigns and offerings – like zero cost E.M.I., Flexible E.M.I., B.N.P.L. (Buy-now-pay-later), cashback, etc., and get more store walk-ins, extend customized offers to consumers. Using our in-house developed analytics platform – SPARCS merchants get an x-ray view of their payment operations.4. What are the major trends that the digital payment industry is seeing?
The payments industry will witness innovative trends that shall set the tone for 2023. Some of the trends to watch out for in the payments industry includes:
QR code payments: Payments via QR codes will continue to prove their flexibility, especially in emerging markets. Dynamic QR codes based on POS machines (Innoviti’s patent) and QR on invoices are some modes that offer better flexibility, convenience, and means of reconciliation than static QR.
Tap and go payments: NFC-based contactless payment devices have enabled tap and go payments. Recently, RBI has enhanced limits for contactless card payments from ₹2,000 to ₹5,000, which is a much-needed boost to increase the transaction volume of contactless payments.
API-based payments (or Integrated Payment Systems): Companies like Stripe are leveraging the opportunity to provide APIs for embedding payments services to businesses. This has resulted in the overall growth of the payment industry by enhancing partnerships between firms.
Distributed ledger for cross-border payments: Distributed ledger (commonly known as blockchain) technologies are looking to modernize this by using “smart contracts” for cross-border payments. Although still in the early stage, the end-use cases of the DLT framework are tremendous.5. What are some challenges faced by the industry today?
While the growth has been rapid, the industry is still nascent. Some of the biggest challenges facing the payments industry include: Frauds: As different modes of payments evolve and newer technologies are being tested, the probability of fraudulent transactions also increases. As per RBI data, between April 2009 and September 2023, fraudsters siphoned off ₹615.39 crores in more than 1.17 lakh credit and debit card fraud cases. While some competitors are still struggling with various malware, compromising the integrity of transactions and customer data being shared in an unsecured manner, Innoviti is India’s first payments SaaS company to receive Coveted SOC3 Seal of Excellence for adhering to trust services principles. Transaction Failures: Failing of various transactions because downtime of primary server results in transaction failures. Smart server switching logic needs to be implemented to ensure that a connected platform processes a transaction if the primary server is down. Chargebacks: Improper handling of disputed charges and transactions can cause anxiety and loss of revenue for merchants. This problem amplifies in foreign currency transactions where the FX conversion has already been done. User adoption: Customers must trust any payment solution that they are willing to use. Fintech can provide user-friendly systems with good UI/UX, better and faster than traditional systems, but if they lack user trust, they will struggle.6. What is your biggest USP that diﬀerentiates the company from competitors?
Innoviti uses technology to turn payment transactions into a smart marketing platform that provides merchants superior payment processing and helps them create new and unique ways to attract more walk-ins, convert more walk-ins, and earn more profits. By enabling merchants to digitally collaborate with banks and brands wanting to target the same customer, Innoviti uses payment technology in unconventional ways to turn payment transactions into customer acquisition and retention tools for merchants, banks, and brands, by bringing them on to a common platform, and helping them deliver unique customer experiences. Each business gets access to 3X loyal consumers at 1/3rd the cost, accelerating sales with unmatched efficiencies.7. What is the size of the Analytics team at Innoviti?
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