Understanding Leni, the world’s first virtual analyst
Lymbyc is one of the very few AI product companies in India. Satyakam Mohanty, Chief Light Bulb, Lymbyc, shares how their flagship product Leni – the virtual analyst, is simplifying complex decision-making for clients across various sectors, mostly in sales, marketing, and commercial functions
Headquartered in Bangalore, Lymbyc serves clients in India, the US, Singapore and the Middle East, including sectors like pharma, CPG & retail, e-commerce and consumer technology. The company was formed in 2012 as Ma Foi Analytics with the idea of infusing cutting edge technology into insight generation. “Our vision was to empower the business leader with insights at the point of decision making, and in real-time, as opposed to the existing processes which run into weeks and months,” says Satyakam Mohanty, Chief Light Bulb, Lymbyc, adding that taking inspiration from J.A.R.V.I.S. of Ironman, they built a world class analytics product that can crunch massive data into insights by leveraging Artificial Intelligence framework on a Big Data layer. The result, Leni, the world’s first virtual analyst, was born.
With the launch of Leni, in November 2017, Ma Foi was rebranded as Lymbyc. Mohanty explains that the inspiration for the word “Lymbyc” came from the limbic system, a part of the human brain that powers our emotions and instincts – the reason behind ‘why’ we do what we do. “We have come a long way from providing traditional consulting services to building world class solutions rooted in AI, Big Data and Predictive Analytics,” he states. The company has won many prestigious accolades and titles including Most Innovative Data Science Product by Aegis, and has been featured in Gartner’s Market Guide for Data Science and Machine Learning Providers.
The flagship product, Leni, provides complex business insights just like a real world analyst does. Leni can be trained/configured to respond to questions across the entire insight spectrum – exploratory/descriptive, diagnostic, and predictive. “It provides business users market intelligence 24/7, while solving for data variety, business ambiguity and analytics complexity,” he comments. The product has been deployed across various sectors largely in sales, marketing, and commercial functions. “Businesses are now keen on exploring Leni in newer functional areas as well,” affirms Mohanty.
Reminding that the key target verticals include pharma and healthcare, CPG and retail, e-commerce, and consumer technology, Mohanty points out that Leni uses the raw data available from various sources, including the internal databases of the client company, as well as external proprietary and public data, and analyses it to provide answers and insights to various questions posed by the user. Leni can be customised for industry specific use cases and can be deployed in short order. “By combining both predictive and prescriptive functions, Leni helps organisations in brand tracks, pricing, competitive intelligence, business intelligence, etc. This will not only increase the efficiency of an individual in doing specific tasks but also the productivity of the organisation,” he informs.
Simplifying complex decision-making
Lymbyc is focused on simplifying complex decision-making for clients, for which the most cutting-edge technologies are utilised. Mohanty highlights the features :
- Leni can make sense of any kind of data, be it transactional, social, web or market research data. It can be seamlessly integrated to any RDBMS, SQL/NoSQL database.
- She understands the user’s question and the kind of analytics action to be taken, just from their natural language query. Using an in-built NLP engine, she gains an understanding of data, domain and business user ontologies.
- She uses her analytics prowess to answer questions across analytics complexities – descriptive, diagnostic, predictive and prescriptive analytics.
- Leni has the ability to constantly learn from user input and user action, and also recommends the type of questions to be asked, based on the user behaviour and insights relationships. This is possible through a Machine Learning based recommendation engine, sitting at the heart of Leni.
- She generates the most apt visualisations based on the type of data and the type of question asked, through its AI based visualisation engine.
“Our view to new technologies and product roadmap is guided both by client needs and our go-to-market strategies. A key focus for us strategically will be to create a better partner ecosystem in parallel to our organic channels,” says Mohanty, adding that this core thinking has led to variants of Leni – the fully loaded as-advertised end-client version, and the Leni-as-an-API version for partners to build custom solutions for end-clients.
Regarding Leni, in the future, he informs that on the core product, the technology and algorithmic R&D will look to achieve two things – the first around continuously creating deeper feature set, and the second on enhancing user experience. “For instance, we are working on introducing voice enablement and a human persona to Leni to make it more user-friendly. Simultaneously we are also working towards making the technology more autonomous, to a point where our partners and possibly even our clients can do their own UI driven builds. We want Leni to be a preferred companion for every business and help them in their decision making and productivity,” discloses Mohanty.
Lymbyc has already filed two patents for its technology and third one is in the process. The team is also working on making insights more accessible to the clients through creation of a mobile application format for Leni, which will include voice based querying.
Mohanty believes that there is a huge business opportunity for AI and ML powered solutions. However, user-focused innovation is a must to address the needs of real-world problems. According to him, industries such as healthcare, pharma and retail, will make significant progress in AI adoption as they continuously realise the potential of speed and depth of insights in helping them make evidence based decisions.
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