[Tech30] How these tech veterans set up Euler Systems to help businesses with their AI needs

By Alok Soni|1st Nov 2017
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Euler Systems uses data science and AI to help businesses that may not be native AI and data businesses.

Remember this famous quote by Dan Airely?

Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it...

If you replace ‘big data’ with ‘AI’ and/or ‘data science’ in the above sentence, chances of you being correct today are pretty high. The businesses today are generating and collecting much more data than their predecessors. But it’s no more about collecting this enormous amount of data. With great power comes great responsibility, and with great data comes great analysis. Data science and AI are the tools to make sense of massive amount of data.

Delaware-based Euler Systems, our startup in focus, uses data science and AI to help businesses that may not be native AI and data businesses. Founded in January 2016, the company counts some of the veterans in technology among its founding members and advisors.

Euler Systems founders
Euler Systems co-founders (from L to R) - Krishna Raghav, Sandeep Kadam, Himanshu Nautiyal

A TechSparks 2017 Tech30 startup, Euler Systems is already breaking even. Here’s their story:

What does Euler Systems do?

Euler Systems uses AI and statistical learning to optimise pricing, revenue, and cost. The company augments experts with virtual assistants. Its current work includes trader assistants for asset managers, revenue manager assistants for hotels, and retail merchandising, pricing, stock selection, and pipeline maintenance assistants for retailers. Krishna Raghav, Co-founder of Euler Systems says,

Our philosophy is to work with incumbents that are and will be disrupted by the Valley. Until now, these firms have built out IT systems, but now they need to actually respond and beat the Valley. We help them do that, whether it is intelligence, full AI implementations, pricing, with the goal set to raise their valuation.

Related readWill the real AI startups please stand up?


It’s all about the people

HImanshu Nautiyal, CEO, Euler Systems

Himanshu Nautiyal, CEO of Euler, is an AI and data science leader from early 2000s. Previously, he had worked for eGain, ClosedLoop, Yahoo! and built India's first jobs aggregator.

Krishna Raghav, the other Co-founder, comes from a hedge fund background and understands ecosystems across spaces. Sandeep Kadam, the third Co-founder, has built Internet scale systems at Yahoo! and Saavn and can engineer learning systems. He is a protege of company’s top investor and advisor, Anurag Gupta, who co-founded Saavn.

The six-member team has previously AI, data science, structured financial products; co-funded B2C startups and manages global equity portfolios.

Krishna says, “So we bring full stack AI capital allocation strategy and execution, finance and investing experience to build high performance tech for our clients.”

Euler Systems is backed by Silicon Valley-based investors, a hedge fund in London and senior bankers.

How does it work?

Krishna Raghav, Co-founder, Euler Systems
Krishna Raghav, Co-founder, Euler Systems

Euler Systems helps companies unearth latent equity value in soft assets, like customer relationships, behaviour and transactions. Selecting high return on invested capital (ROIC) projects to ensure tech goals fits financial goals. The founders’ experience in varied sectors (banking, hedge funds, marketplaces) allows them to operate as generalists across multi-sector client projects to build ML/AI IP within the sector.

The company broadly provides three solutions:

1. AI and machine learning - Euler Systems used AI for demand forecasting for a hospitality e-commerce client in Silicon Valley resulting in an increase in productivity by eight percent. It also helps with personalisation, search and recommendation which, according to its claims, has increased click-through-rates (CTRs) by 20-30x for internet scale online properties.

2. Data classification - Euler Systems can classify millions of datasets on the fly with high accuracy for e-commerce companies. It can also help in customer intent life deduction for large insurance companies.

3. Big data and engineering - Euler Systems build big data and analytics engine, data visualisation engines and data mining discoveries to aggregate data across spaces like e-commerce, music, online travel agencies, jobs, social networks. Implementation of search across multi-lingual music, e-commerce products and jobs.


Also readWhy your startup needs to have an AI-driven strategy and be prepared for a possible ‘AI world war’


Market, traction and plans

Sandeep Kadam, Co-founder, Euler Systems
Sandeep Kadam, Co-founder, Euler Systems

Euler Systems look at their market size by that of their clients’.

Backed by angel investors ($500,000 funding), Euler Systems has reached breakeven. It has hit an annualised recurring revenue run rate of $1 million. Its clients include American and Indian firms, startups and unicorns, disruptors and incumbents, spanning retail, e-commerce, travel, entertainment, and financial services.

The company is aiming to hit $2 million ARR by the end of the current FY (and $10 million in the next FY). The founders are looking to infuse external equity into the products for distribution.

AI and ML in India

Consulting firm McKinsey sees AI to be a $126-billion industry globally by 2022. Machine learning is now a big industry in India with a market size of $8 billion worth of exports.

Some of the startups using AI for business solutions include Niki.ai for chatbot, Mad Street Den for e-commerce/retail solutions, Embibe for education, Locus.sh in logistics and Arya.ai for banking and insurance. AI startups focussed fund Pi Ventures closed $13 million of it $30 million fund recently. Its founding partner Manish Singhal says,

Lack of good quality data and talent could be one. Although I must say that all AI startups need to put more attention on their AI architectures and validation frameworks to really do a good job. That is one area we often find has gaps.

For now, Euler Systems seems to take care of the above statement, but we’ll figure out its success with time.

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