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Startups using Artificial Intelligence to make products for everyday life

World over, companies are making products for everyday needs using artificial intelligence. Indian startups are also at the forefront of this trend. From discovering financial fraud to healthcare support, some of the cutting-edge technologies are developed by young ventures here which have a vibrant market in the United States and Europe.

Areas of Application

Information technology

IPsoft, a company founded by an Indian-origin mathematician Chetan Dube, is revolutionising the way computer 
networksare managed. Its technology mimics the human brain and is capable of self-healing, self-learning and autonomously solving a majority of the problems that arise on computer networks. It has created a humanoid called Eliza which can identify problems, have natural conversations with users and solve problems in a few seconds. Infosys recently tied up with IPsoft, which carries out most of its R&D work out of India

Advertising and Retail

Bangalore's Tonbo Imaging, a startup that develops video processing and imaging technology for the military, is using this platform to help retail and consumer goods firms. Its cameras, embedded on digital signboards, automatically analyse a person's facial expressions, eye gaze and body language to develop insights about customer behaviour. Its customers include Kraft-Cadbury, L'Oreal and P&G. Tonbo also has a television audience measurement product. Its device in TV sets can analyse what channel is being watched as well as the demographics.


eDreams Edusoft, a Bangalorebased company uses natural language processing technology to provide automated personalised tutoring. FunToot, its product, is now being used by about 14,000 children. Another company, PrazAs, founded by BITS Pilani and IIT alumni, has developed adaptive learning software being used by students in India and the US. The technology, which can recognise handwriting, records the steps taken by students to solve problems. It alerts the tutor when a student is stuck.


Hyderabad-based Gramener helps enhance longevity of chickens. It analyses data provided by Suguna Foods, its client and one of the biggest in the poultry business. Gramener finds disease patterns to let Suguna know what precautions to take and makes recommendations about how much sunlight the birds must be exposed to, the type of feed, and even the structure of the shed in which they are housed

BPO & ecommerce

Human responses come with a set of pitfalls —emotional vulnerability, bias, and above all, lack of knowledge. Bangalorebased Vimagino has created intelligent systems called 'angels' which can sense and respond to human emotions in customer interaction.


Grey Orange Robotics, set up in 2009, builds robots that can move shelves stacked with various products to a f loor assistant who then scans a bar code to confirm the right items. The robot in turn moves the chosen products to the shipping bay where workers 
seal the packages for final transport. The robots, which look like cubes, are cal led Butlers.

Dating services

Artificial intelligence is showing the way to true love. Instead of traditional markers such as caste, community, or horoscopes, a new breed of online match-making sites, such as TwoMangoes, rank users based on education, profession and career prospects. These firms use algorithms to study users' behaviour and reaction to others on the site to suggest a partner.

Predicting Crime

Crime fi ghting has also found an ally in big data analytics. The Tom Cruise-starrer 'Minority Report', set in 2054, showed prediction of crime. Data scientists at the India laboratories of
IBM have brought that future to the present. They predict the chances of a person committing a crime, based on jail records, IBM India has deployed this analytics for the police departments of New York and Chicago and is now working with an Indian state police agency.

IBM also delivers traffi c prediction in cities such as London and Stockholm, for which the prediction algorithms are done out of India. The traffi c prediction is based on real-time information that helps IBM identify the patterns of how a particular roadway is getting congested and traffi c and transport authorities of these cities are able to change the pricing of tolls accordingly.

Corporate Enthusiasm Academic Interest

Corporates are always in search of competitive advantage. "Indian enterprises have no choice but to adopt (such) technologies as their global competitors are already using them," said Uday Chinta of IPsoft. Companies like Virgin Airlines and
Jet Airways are taking the help of Bangalore-based Vizury to analyse data and target customers. Airtel and Vodafone are taking help from Noida-based mCarbon Tech Innovation to offer customised services. IndiGo uses AI to plan how best to price its tickets much in advance.

Machine learning is being widely used by analytics companies to predict consumer behaviour. Bioinformatics firm Strand Life Sciences, founded by professors at IISc, uses artificial intelligence, data mining and visualisation to help doctors to make a rapid analysis of genome mutations. Two of the country's top avionics research centres—NAL and CSIR—have successfully tested a technology that can reduce the cost of running and maintaining an aeroplane by predicting possible damages.

Level of Growth

Entrepreneurs and technologists have shown tremendous initiative to build AI solutions. India does not have an ecosystem like in the US and Israel, where governments fund startups and provide incentives. Industry also needs to provide grants to universities to conduct research and development.

Foreign Interest

Several Indian companies operate in the global market and have a roster of A-list clients. When US Army drones fl y over enemy territory, they use image analysis technology of Tonbo Imaging. Nimble Wireless helps clients in the US manage and control remote assets. For example, when clients fail to repay loans taken for a piano, an embedded sensor disables the instrument. Unmetric, founded by IIT-Madras alumni, has a platform that can sift through billions of bits of data on social media and analyse it through self-learning algorithms. It has bagged customers such as 
Subway, Toyota, Airtel and Australian bank Suncorp

Political Encouragement

Most politicians and political parties are far removed from artifi cial intelligence. Some policymakers 
no doubt see the potential of this technology, but support from the government is limited. State institutions carry out research and development, but real-world applications are few and far between.

Terms and Concepts


The science of designing intelligent agents—a machine, a piece of software, or a mix of hardware and software— capable of perceiving the 
environment and taking independent decisions.


A system that can access knowledge created by humans and use it to take decisions.


A technique that uses principles of biological evolution to solve problems. They use an initial set of solutions that are ranked for fi tness and then combined to produce better solutions


Models like neuron 
networks in the brain that utilise multiple connections rather than ones and zeroes like in a digital computer. Used in voice analysis, medical imaging and so on.


The ability of computers to learn from experience or exploration, thereby letting them perform better in changing situations.


IBM and others use the term to describe the third era of computing when computers will discover and learn on their own.


Applications that help humans take decisions. They need not be based on AI, but complex situations demand automation based on AI.


Computers only understand the digital code. They are being taught to understand human languages, an effort that will be the basis of computer-human interactions in the future.

Artificial Intelligence Timeline

John McCarthy, a computer and cognitive scientist based in the United States, coins the term artifi cial intelligence

1956: The field of AI research is founded at a conference on the campus of 
Dartmouth College in the US. The attendees, including McCarthy, Marvin Minsky, Allen Newell andHerbert Simon, became the leaders of AI research for many decades.

1960s: Research in the US is heavily funded by the Department of Defense and laboratories are established around the world. AI's founders are profoundly optimistic about the future of the new field. They predict that "machines will be capable, within 20 years, of doing any work a man can do."

1974: In response to ongoing pressure from the US Congress to fund more productive projects, both the US and British governments cut off exploratory research in AI. The next few years were known as the "AI winter".

1980: AI research is revived by the commercial success of expert systems [a program that simulates the knowledge and analytical skills of one or more human experts.]

1985: The market for AI reaches over a billion dollars. Japan's fi fth generation computer project inspires the US and British governments to restore 
funding for academic research in the fi eld.

1990s: AI achieves signifi cant successes, albeit somewhat behind the scenes. Artifi cial intelligence is used for logistics, data mining, medical diagnosis & other areas.

1997: Deep Blue becomes the fi rst computer chess-playing system to beat a reigning world chess champion, Garry Kasparov

2005: A Stanford robot drives autonomously for 131 miles along an unrehearsed desert trail. Two years later, a team from CMU wins the DARPA Urban Challenge when their vehicle autonomously navigated 55 miles in an urban 
environment while adhering to traffic laws

2011: In February, in a Jeopardy! quiz show exhibition match, IBM's question answering system, 
Watson, defeats the two greatest Jeopardy champions, Brad Rutter and Ken Jennings, by a significant margin.