Can software write content for you?

We are living in an era characterized by digital marketing, where having a strong online presence is vital for success. As much as you invest in building your product, improving your services and carving a niche for yourself, it is also absolutely essential to maintain an up-to-date website or blog that gives a voice to your firm and speaks of all that it has to offer. A study by Google claimed that 97% of consumers use the web to search for local businesses.

The aim is to provide information to site visitors and rank higher in search engine results (think SEO) to drive more traffic to your page. Such a 24*7 virtual showroom allows potential customers to check out your business from the comfort of their homes, while boosting marketing, selling and brand-building.

The importance of a strong online presence cannot be underestimated. But with other aspects of the business to look into, it is seen as a difficult and time-consuming task, which leads one to think if content generation for websites and blogs can be automated.

There is a plethora of tools out there that use keywords and RSS feeds to search the web for articles relevant to your domain and industry, make slight modifications if necessary, and republish them on your site. While such keyword-based automation tools may help improve your visibility on search engines and save time with their “set it and forget it” principle, the output will lack a fresh voice, originality and a personal touch. Keeping these tools aside, how about having an Artificial Intelligence (AI) backed platform that allows you to have the best of both the worlds?

We’re talking about a platform like PHRAZOR by vPhrase that takes key parameters in structured format as input and generates content in the form of crisp narratives exclusively for you within a few seconds. ‘How come it is authentic and quick at the same time?’ you may ask. The answer lies in the fact that such a language generation platform can be easily configured with the domain knowledge and expertise of your best employees. It studies and understands your business and then produces output in the voice and tone of your organization.

The Indian business news and online trading website, makes use of PHRAZOR to power live market commentary on their website. Based on live stock market feed, prices of top stocks, their index movement, market indices and indicators are fed into the platform, which understands the same and generates comprehensible content, coupled with statistical summary, to be published on the website. Tata Consultancy Services also avails the services provided by PHRAZOR to generate valuable website content at a high speed for its clients across multiple business domains.

Apart from textual content, audio and video can also be auto-generated, saving a great deal of time and other resources. In an age where companies are looking for global market domination and solving business problems smartly, where the usage of social media is skyrocketing, where businesses are having a virtual version of themselves available online, it is only wise to let AI assist you in making headway towards your goals.

The media and entertainment industry goes gaga over AI

The Indian media and entertainment industry is expected to grow at a compound annual growth rate of 13.9% to reach 37.55 billion USD by 2021, outshining the global average of 4.2%. Its success can be largely attributed to the increase in digitization and internet usage over the last decade. Although it has been raking in more moolah, it continues to face the same problems- namely, limited scope for new opportunities, accurate audience measurement, tracking ROI and attribution, managing increasing business costs, finding an effective and sustainable business model, analyzing performance and staying ahead of the competition, among others.

Artificial Intelligence (AI) is here to address these issues, while sticking to the major goals of the industry – providing timely and quality content and seeing to it that it is received well, cutting down costs and maximizing profits. Here’s how:-

For the uninitiated, Virtual Reality (VR) is the use of computer technology to create a simulated environment, whereas Augmented Reality (AR) is the use of computer technology to enhance the real environment by overlaying a new environment on top of it. Although AR and VR have a lot of potential in the gaming and entertainment industry, and also for educational and military purposes, their use is currently restricted due to high associated costs. AI is bringing a renewed energy to this space by helping with better content authoring and correlation, contextualization, improving the quality of data and accuracy of images.

AI aids in production of content in all forms – textual, audio and video. The Indian business news and online trading website, makes use of vPhrase’s data analytics solution, PHRAZOR to power live market commentary on their website and also to generate quarterly earnings analysis reports for various companies. The platform automatically produces crisp, accurate and comprehensible content within seconds, after being fed with structured data and statistics. Another example is the video of Obama delivering a speech he never gave. Such automation of content generation using AI saves a great deal of time and other resources. The 20th Century Fox recently used AI to create a horror movie trailer within 24 hours, which would have taken atleast 30 days for a manual edit.

We aren’t entirely new to the movie recommendations provided by Netflix. The system is based on AI that learns about our personal preferences over time and gives suggestions depending on the movie choices we’ve made in the past. It helps acquire audiences for new shows.

Periodic performance reports help media houses track their growth and analyze where they stand among their peers. These reports mostly contain tables, pie-charts, graphs and numbers – all of which are difficult and time-consuming to comprehend. Enter AI, specifically Natural Language Generation (NLG), and we have complementary, automated narratives that explain performance in an intelligible manner, thus providing better insights and aiding faster decision making. For instance, Viacom18 and Sony Entertainment Television have partnered with vPhrase to generate smarter reports on programs and channel performance based on the rating data provided by BARC. Here’s a snapshot:-

AI has revolutionized the healthcare, finance and banking sectors. With it now fuelling changes in how audiences consume entertainment, the media industry is growing more advanced.

AI to revolutionize the banking sector

Leading banks like JPMorgan Chase, Bank of America and CitiBank have been in the limelight recently for adopting artificial intelligence (AI) technology to help them gain a competitive edge and generate more revenue. Keeping up with the ever-growing data and increasing customer expectations, cutting down costs and boosting work-force productivity are major challenges banks face – AI is here to help them address these issues.

Massive volume of data generated at high speed requires quick analysis and decision making, so that current market opportunities can be tapped to maximize profit. With the paucity of time and limited intellectual capabilities of humans, deriving accurate, unbiased, error-free and actionable insights on the fly doesn’t seem feasible. Not anymore. Having an AI-powered solution in place automates data analysis, while cutting down time and cost by a humungous amount. It finds application in loan processing, market data analysis, client portfolio analysis and insurance policy payout processing among others.

Banks spend almost 40 percent of their time on documentation- there are executive summaries, investment portfolios, loan agreements, etc. By automating data analysis and writing of reports using a natural language generation platform like PHRAZOR, banks can use this time constructively towards higher value activities. Well-researched, lucid, personalized narratives can be generated for clients, as well as everyone along the hierarchy within a matter of seconds. For instance, HDFC Bank partnered with vPhrase to automate the generation of branch manager performance reports. It helps in improving organizational productivity and striking a chord with your clients – the success formulas for an ambitious firm.

Natural language processing (NLP) bots play a major role in enhancing customer service. For instance, The Royal Bank of Scotland’s Luvo can answer frequently asked banking related questions and perform simple tasks like money transfers. Erica – the intelligent personal assistant deployed by the Bank of America, leverages predictive analysis and cognitive messaging to give financial guidance to its approximately 45 million customers. HDFC Bank has tied up with to facilitate chat-bot banking.

Sentiment analysis is another popular application of NLP. It can be applied to news articles and reports, social media and web content to understand the client’s sentiments about the firm and the investor’s views about the market.

AI software, armed with knowledge of the ongoing laws and latest banking regulations, serves as a good consultant. It is updated with the latest information, such that it doesn’t miss any rule and steers clear of any legal hassles involved in this space.

NLP in conjunction with machine learning techniques can be used by financial firms to detect possible illegal insider trading, by mining through e-mails, message boards and regulatory filings. Lloyds Banking Group has been using this method to identify fraudulent phone calls. Also, patterns can be detected in e-mails, transcripts of conference calls or annual securities filings to predict or detect fraud early.

In the case of Deutsche Bank, quantitative investing models and stock price prediction have seen significant improvement with the integration of an AI-enabled solution. Coming to stock trading, the US cash equities trading desk at Goldman Sachs’s New York headquarters went from employing 600 equity traders in the year 2000 to just 2 recently – the reason being that automated trading programs have taken over most of the work. Reports claim that more than 70% of the trading today is actually carried out by automated AI systems.

Finie, a voice-powered, AI-based intelligent personal assistant, can be integrated within a bank’s mobile app. It allows individuals to interact with their banking accounts using voice input. Rather than resorting to standard, template based questions, one can ask questions like, ‘Do I have enough money for the opera today?’ or ‘Did I spend more on shopping this month than the last one?’ Finie learns better over time about your financial management, offers personalized advice and also completes banking tasks. Mobile banking apps like Moven and Simple let users track their spending and increase their savings with a card linked to their smartphone app.

More power to AI as it goes on to become the most defining technology for the banking industry!

Business problems that AI can solve

PwC recently conducted a worldwide survey and concluded that a majority of top executives agree that artificial intelligence (AI) will have a huge impact on every aspect of business and offer unprecedented growth opportunities in nearly every sector. It is estimated that AI will cause global GDP gains to hit the $15.7 trillion mark by 2030.

The advent of social media, mobile computing and IOT technology has led to massive amount of data in a variety of formats being generated every second. Businesses need to exploit this data to boost revenue and have an edge on their competitors. However, here’s the catch – The rate at which this data is produced is significantly higher than the rate at which it can be analyzed. Secondly, there is a huge gap between the demand and availability of analysts, which causes the business expenditure go on the higher side. Thirdly, the insights generated from the data would be subject to human bias and error.

Does this mean going easy on those meticulously chalked out business objectives and ambitious plans? Certainly not! A single big data analytics platform that seamlessly integrates into your existing architecture can help you tackle all these problems. Fed with the domain knowledge and technical expertise of your best analysts, it can derive accurate and actionable insights from data on the fly, thus helping you tap current market opportunities to maximize profit. Automation of data analysis leaves ample time towards activities that involve strategic planning and decision making. With its AI-based business intelligence solution PHRAZOR, vPhrase is helping firms automate data analysis and generate insights from data within seconds.

There is more to AI apart from data analysis. Natural Language Generation (NLG), a subset of AI is not only helping organizations robotize the tedious task of documentation but also generate narratives in conversational language that the client would understand. As clients feel valued and more involved with the firm, their satisfaction increases – which in turn is good for the business. By automating report generation, organizational productivity goes up by several notches. PHRAZOR, that serves both as a predictive analytics and natural language generation tool, is being used by Kotak Wealth, MasterTrust and Motilal Oswal for client investment portfolio analysis and reporting. It also provides recommendations and options for direct execution.

In a recent interview with the Wall Street Journal, the principal of Deloitte Consulting LLP stated that deploying NLG across the organization for business unit reporting led to a significant increase in efficiency of the firm. The process that required eight analysts earlier needed only one after the adoption of an NLG solution, allowing them to redeploy seven analysts to higher-value activities.

AI is being embraced by firms that dare to be tougher in face of growing challenges and aim to do intelligent business.

Watch this space for more!

Difference between NLU and NLG explained

“Hey Siri, how many days is it until Halloween?”

“10 days to go.”


“Can you wake me up at 6 tomorrow?”

“Sure. Alarm set for 6:00 am”


“Are there any popular eateries around this place?”

“Yes, there you go”

*presents a list of places sorted in the order of importance*

We commonly have such kind of conversations with our intelligent personal assistants, which are adept at understanding the context of the query and presenting results in spoken language, sometimes also providing useful links, maps for directions, etc. Such systems are based on Natural Language Processing (NLP) – a combination of computer science, artificial intelligence and computational linguistics – aimed to help humans and machines communicate in natural language, just like a human to human conversation. An effective NLP system is able to comprehend the question and its meaning, dissect it, determine appropriate action, and respond back in a language the user will understand. Alan Turing stated that if a machine can have a conversation with a person and trick him into believing that he is actually speaking to a human, then such a machine is artificially intelligent. This test eventually came to be known as the Turing test and passing it has been one of the most sought after goals in computer science. It is what NLP systems aim to achieve.

Apart from personal assistants like Siri, Alexa and Google Assistant, some other applications of NLP include social media sentiment analysis, summarizing information and e-mail spam filtering. NLP is a vast subject that comprises of speech recognition, speech synthesis, Natural Language Generation (NLG) and Natural Language Understanding (NLU). While speech recognition software transcribes spoken language, speech synthesis software focuses on text to speech conversion.

NLU attempts to understand the meaning behind written text. After having the speech recognition software convert speech into text, NLU software comes into the picture to decipher its meaning. It is quite possible that the same text has various meanings, or different words have the same meaning, or that the meaning changes with the context. Knowing the rules and structure of the language, understanding the text without ambiguity are some of the challenges faced by NLU systems. Popular applications include sentiment detection and profanity filtering among others. Google acquired provides tools for speech recognition and NLU.

NLG does exactly the opposite. Given the data, it analyzes it and generates narratives in conversational language. It goes way beyond template based systems, having been configured with the domain knowledge and experience of a human expert to produce well-researched, accurate output within seconds. Narratives can be generated for people across all hierarchical levels in an organization, in multiple languages. Firms like vPhrase are leading this space with their NLG platform PHRAZOR. Data analysis, automated report writing, etc. are applications of NLG.

Most real-world applications are based on one or a combination of NLP technologies. For instance, if we were to consider a personal assistant like Siri, the software architecture can be as depicted below:

NLP is increasingly becoming an important area of interest and major tech giants like Google, Apple and IBM are investing heavily to make their systems more human-like. According to a study by Tractica, the global NLP market is expected to reach $22.3 billion by 2025. These systems are already trending and it is only a matter of time before they redefine the way we interact with technology on a daily basis.

AI is all set to empower medicos

From radiologic imaging to organ transplantation, laser treatments to IVF, synthetic cells to artificial hearts and bionic eyes – the healthcare industry has seen it all. And now, artificial intelligence (AI) is here to revamp the space with 63% of healthcare executives worldwide already realizing its potential and investing in it.

Analyzing and putting massive volumes of patient data to practical use, while working in a time-constrained environment and catering to a horde of people every single day certainly isn’t a cakewalk. AI and Robotics are here to improve healthcare processes, assist doctors and treat patients earlier and more effectively. This would also enable medical professionals to focus more on urgent and challenging assignments rather than repetitive and monotonous tasks.

AI is used in conjunction with computer vision and deep learning to develop platforms that can accurately analyze X-rays, CT scans and sonography reports. The platform is reliable and intelligent as it is fed with knowledge and experience of the best in the industry. It significantly outperforms a human expert with its ability to mine through records and images at a much faster pace, provide diagnosis and treatment options, along with its rationale for suggesting the same. Armed with a quicker and clearer understanding, the doctor can now make a better decision about how to take the case further.

Such platforms equally benefit the patients by encouraging them to play a more active role in their medical care. They double up as reporting tools to generate narratives that the patient can actually make sense of. For instance, consider the following snapshot of a blood test report:-

It is difficult for a layman to understand that kind of medical jargon and the relevance of the numbers given. Instead, picture your patient reading through the following:-

This one provides a more complete picture and gives the necessary information in a language that is comprehensible. The patient feels satisfied and well-informed. Natural language generation platforms like PHRAZOR by vPhrase are helping leading organizations in the healthcare domain up their game by leveraging AI technology to add value to the services they provide to their patients. Also, different sets of people – the patient’s family, doctors, nurses – would be interested in different aspects of the same report. The platform can be configured to meet each one’s need.

Virtual assistants and health tracking apps such as Microsoft HealthVault and DoctorOnDemand are bringing the ‘care’ back in healthcare. These can answer simple health related queries and track one’s health, remind people about their medication, cure mental illnesses, allow online consultation with a doctor and do so much more.

Enter robotics and we have exo-skeletons that help paralyzed people to walk and robots that assist doctors during surgery. Medicine dispensing systems such as those by ScriptPro allow pharmacists to save time and cover peak hours without employing additional staff, while reducing waiting time and increasing customer satisfaction.

There is much more to AI than simply optimizing healthcare processes- it has a revolutionary potential. It is here to eventually shift the focus from treatment to prevention. Growth in the AI health market is expected to reach $6.6 billion by 2021, which is a whopping 40% annual growth rate. It’s time the medical community embraces this new technology to serve the world better.

Top use cases in automated report writing

Documentation is one thing that most employees loathe, especially when it needs to be done periodically for a large number of clients and co-workers and more so, when it needs to be tailored to meet each one’s needs and expectations. The task is not only an arduous and time-consuming one, but also brings down organizational productivity significantly. Employees feel satisfied on accomplishment of tasks that challenge them and require their precious skill-set. Documentation or report-writing is nowhere close to that.

Leading firms have taken a step ahead by delegating the task of report-writing to an artificial intelligence enabled solution based on natural language generation (NLG). Such a platform seamlessly integrates into your existing architecture and saves you a huge number of hours each day. It is secure and reliable, having been configured with the knowledge and expertise of your best workers. It is fed with data in a structured format, which it thoroughly analyzes and crisp narratives in conversational language are produced as the output, within a matter of seconds. Reports can be generated for everyone- ranging from the junior-most employee to the director, and even clients – all in the style and tone of your organization. What’s more, the platform does away with human errors and doesn’t even ask for sick leaves!

It can be used across various domains for a multitude of purposes, some of which have been listed below:-

  1. Financial reports: Analysts have a tough time while trying to understand the massive amount of financial data that changes within fractions of a second. It is crucial to derive insights from this data at the right time to exploit current opportunities and maximize profit. However, due to limited human intellectual capabilities, it isn’t always possible. After the analysis phase, there are equity reports, stock analysis reports, quarterly earnings reports, etc. to present. With the goal being to explain performance to the reader, these reports need to be written in a language that’s comprehensible. An NLG platform solves both these problems for a financial services firm.
  1. News reports: The same platform can serve as an aid to a journalist. For instance, to write sports news, live scores, details about the venue and the players, their past record, etc. needs to be given as input to the software, and well-framed sports summaries are generated in multiple languages. This frees up journalists to focus on pieces that need to be more intricate and involve more research and information gathering.
  1. Medical reports: To analyze X-rays, CT scans and other reports, natural language generation is used in combination with computer vision and deep learning. Images, tables stating the symptoms and other patient data are given as input to the platform that successfully churns out detailed narratives explaining the patient’s health. It may also give advice, along with the reason for coming up with the same. Doctors can build up on that to proceed further. This simplifies their job, making it more accurate and less time-consuming.
  1. Legal reports: In large lawsuits, many documents need to be reviewed, understood and their summary needs to be provided – it is a task assigned to paralegals. After such information discovery process, lawyers need to identify and analyze the arguments that can help them win the case. With an NLG platform, the first step can be automated and more time can be allotted to the second one.

vPhrase’s patent pending platform PHRAZOR has been adopted by organizations across various domains to enhance productivity and make most out of the time available by automating data analysis and report writing.

And if such platforms contribute towards striking a chord with your customers too, there should be no looking back.

Striking a chord with your customers, the AI way

In the words of Jeff Bezos, “If you do build a great experience, customers tell each other about that. Word of mouth is very powerful.”

It was stated in a report by EY that 71% of customers decide whether or not to trust their financial services provider based on how they’re treated, while 50% of respondents cited communications as a major factor that shapes their trust.

According to the experts at Forrester Research, there is a direct correlation between client satisfaction and increased revenue.

The importance of having happy, contented clients cannot be underestimated.

Now, picture your client receiving her quarterly portfolio statement in the following format:-

Can you be sure that she has understood what exactly all those numbers and financial terms indicate?

Such reports don’t do much to help clients figure out where their investments are heading. They feel less informed about their financial choices and need to rely heavily on agents in case they decide to get a clear understanding. What clients expect is a personalized outreach.

Now, consider the following:-

A ‘narrative’ of this kind empowers the client. It gives a voice to the data. It is self-explanatory and presents all that the client needs to know, in a language that’s simple and comprehensible. It accomplishes the actual purpose of sending out a quarterly portfolio statement – improving client engagement, explaining fund performance and telling them how exactly your firm is helping them progress towards their financial goals. It helps them connect with you better.

If a wealth manager was to provide such a tailored portfolio commentary to each investor, it would mean a great deal of time spent analyzing raw data and writing. The task is an arduous one and scalability would always be an issue.

This is where Natural Language Generation platforms step in. They automate the task of analyzing client profiles and generating personalized narratives in conversational language. What’s more, these platforms are secure, reliable and seamlessly integrate into your existing architecture to produce well-researched output within seconds. They are fed in with the domain knowledge of your experts and can be configured to reflect the tone and style of your organization. With data analysis and report generation now faster, automated and simplified, your analysts can concentrate on higher value activities that involve strategic planning and decision making.

Intra-organization, such platforms also serve as big data analysis tools by deriving insights on the fly and helping organizations make data-driven decisions better and faster.

AI-backed solutions like vPhrase’s patent pending platform PHRAZOR are leading the way in this domain. They use a combination of advanced analytics, natural language generation, machine learning, and other core artificial intelligence concepts. With these, organizational productivity and customer satisfaction shoot up significantly.

Leading firms are realizing that to outshine their competition, they not only need to attract new customers but also work harder to retain the existing ones. And increasingly, they are discovering that one of the keys to doing so is by raising engagement through high-quality, personalized communications.

Say yes to embracing innovation to catalyze growth and have happy customers over!

Will automation lead to mass unemployment?

In a popular study published by Carl Frey and Michael Osborne, it was stated that 47% of U.S jobs will be automated within the next two decades.

With Wendy’s announcing plans to have automated kiosks over at its stores, Foxconn replacing its workers with Foxbots, Amazon planning to robotize its brick and mortar stores and Adidas’ robotic shoe makers producing running shoes, other companies are likely to follow suit. Naturally, this has sent a wave of unrest across all sectors and there is an increased fear of losing jobs.

But the research arm of McKinsey & Company has another story to tell. It concludes that the near-term impact of automation will be to redefine jobs rather than to eliminate them. The fear of automation should instead be seen as an opportunity for augmentation. Moreover, there is still a long way to go before we get to Artificial Super Intelligence (ASI), which isn’t something to be intimidated by either.

Let’s travel back in time and recollect how bank tellers felt apprehensive about the then newly launched ATMs. The number of bank tellers did fall from 20 per branch in 1988 to 13 per branch in 2004, greatly reducing the cost of running a branch. This allowed banks to open more branches in response to customer demand. The number of branches rose by 43%, thus employing more people whose work now was focused on sales and customer service rather than routine activities.

The automation of shopping through e-commerce along with an accurate recommendation system in place, encourages people to buy more and has increased overall employment in retailing.

With robo-journalists helping them with basic, standard reports and articles, journalists can allot more time to write smarter pieces that involve extensive research and information gathering – their robo-colleagues share their job, instead of stealing it thus favoring the firm’s growth and success.

The State Bank of India has automated passbook printing, thus allowing their staff to attach more weightage to tasks like loan processing and currency conversion.

The same pattern can be observed across all industries. Also, jobs that seemed far-fetched a few years back-data analysts, information architects, user interaction specialists-have now sprung up thanks to technological advancement.

Indian business news and online trading website, that hosts real-time financial data of various companies relies on VPhrase’s artificial intelligence backed platform PHRAZOR to derive insights from data and publish it as narratives in natural language – a form that most of its readers would understand, thus helping it connect with them better. With a solution like this in place, it is easier and less time-consuming for users of the site to make sense of tables and charts that once came across as an indecipherable matrix of numbers and finance jargon.

Although automation has taken over some blue-collar jobs in the past, the current scenario shows that there has been an increase in demand for specialists in Artificial Intelligence and Robotics. The white-collar jobs will likely be upgraded in a way that would require a better skill-set and roles will be redefined, but they certainly won’t vanish – also there might be several new jobs in the offing.

Automation shouldn’t be perceived as a human versus machine war. We should rather embrace this change and gallop together towards a better future.

Leveraging Artificial Intelligence to augment Big Data Analysis

With gobs of data available just a click way, an organization’s overall success is directly proportional to the speed and accuracy at which this data can be processed into useful information, analyzed and acted upon.

Business intelligence tools do a good job at presenting this massive data, procured from various sources, in a pictorial or report format.  However, is this representation of data really understandable? Consider a sales manager who has to go through scores of sales reports and performance reviews of his team. Every month, he receives consolidated sales reports that look something like this one:-

Comprehending a report like the one above is a cumbersome and time consuming task. More so, there is a probability of missing out on useful insights due to limited human intellectual capabilities. Automated narratives that actually explain what the numbers in the report indicate in terms of performance and how relevant they are to the reader, is a great way out.

With automated narratives, the report would now look like this :-

This is certainly clearer, more detailed and explains all that one needs to know to aid decision-making.

Having a “virtual expert” over to generate such narratives is the smartest decision leading organizations are making today. The virtual expert is well-equipped with the analytical skills, domain knowledge and technical expertise to automate the process of data analysis and write lucid reports for you. It not only revolutionizes the way data is approached, but also seamlessly integrates into your existing architecture, while cutting down time and cost by a humungous amount. The output is generated in the form of comprehensive narratives in conversational language, within a matter of seconds. The virtual expert is based on Natural Language Generation, a subset of Artificial Intelligence (AI), concerned with generating language from input data and aimed at robotizing data analytics and report writing.

Business analysts spend hours trying to make sense out of pie-charts, graphs and tables and crunching numbers that never seem to stand still in the world of finance. Natural Language Generation (NLG) solutions automate this tedious, repetitive and resource-intensive task, giving out crisply written narratives coupled with statistical summary as the output. It is now easier to derive business insights and focus on decision making and strategic planning. The data isn’t subject to human bias, misinterpretation and error hence the output generated is highly accurate.

Intra-organization, such platforms can be configured to generate reports for everyone, whether it is an asset manager, a technical lead or an executive. The reports can be customized as per the level of detail and type of information needed. They go way beyond template-based report generation software and internally work on algorithms that emulate a human expert, albeit in seconds, and with much larger and complex data as input.

Having sent out quarterly customer portfolios, can you be certain that they understand where their investment is heading, or how good they are doing? In most cases, the answer is a big NO! The customer, in spite of being the most important entity here, doesn’t feel much involved. Automated narratives not only explain to the customers all that they need to know about their portfolio in simple language, but also do so in the tone and voice of your organization. This significantly improves customer engagement, making them resonate with your brand much better.

Such a virtual expert aids data analysis, empowers you to achieve optimum resource utilization, increase productivity by several notches, and generate more revenue.

Case in point, in a recent interview with the Wall Street Journal, the principal of Deloitte Consulting LLP had stated that deploying Natural Language Generation across the organization for business unit reporting led to a significant increase in organizational efficiency. Earlier, the process that required eight analysts, needed only one after the adoption of an NLG solution, allowing them to redeploy seven analysts to higher-value activities.

Also, with rapidly increasing data available in different formats across a variety of sources (termed as ‘Big Data’), it is crucial to do data interpretation on the fly and draw conclusions to exploit the current market trends and maximize profit. It is important to sift data real-time, reveal patterns that aren’t very obvious and generate accurate results. NLG platforms like PHRAZOR that not only provide automated narratives and interpretable reports, but also double up as big data analytics tools, serve the purpose. Thus, you can rest assured that insights aren’t buried, opportunities aren’t lost and you are making the most out of the data available, no matter how overwhelming it is, at the right time.

With Forbes declaring NLG as one of the hottest tech trends for the year 2017, it is here to stay and redefine the way we do business. It takes efficiency, innovation and progression to a new level, enabling leaders to stay ahead of the competition and be well equipped to tackle challenges in unprecedented ways.