Providing an in-database analytical engine to deal with the problem of voluminous data enabled Fuzzy Logix to grow quickly and expand to newer markets
The growth of voluminous data is both an area of opportunity and a challenge for a business; on the one hand it holds the potential to tap into insight that could change the way business is done and on the other, it poses the challenge of dealing with data with efficacy.
Partha Sen and Michael Upchurch, who were colleagues at Bank of America, faced the same dilemma. Though there were engines that could help analyse data, the bottleneck lay in moving sample data to these engines. As data grew in volume, the challenge heightened and moving data became labour-intensive and data scientists were bogged down by the cumbersome and time consuming work of selecting and moving data.
Sen and Upchurch started experimenting with the idea of bringing the engine to the database instead of moving data to the engine. They came up with a product embedded in the database engine which gave them startling results and they achieved a near 70 per cent time efficiency. The duo also made parallel processing possible, making it 50-100 times faster, making this a game changer.
Thus was born Fuzzy Logix, as an in-database analytics company, in 2007 in the U.S. with self- financing from the founding duo. The proposition was so compelling that it caught the attention of the industry and attracted large customers. In the first seven to eight years, the company ran on internal accruals and generated reasonable revenues that allowed it to expand in the U.S.
We are called upon when organisations face issues with asset performance and SLAs are not efficient. We tell the potential customers to give us the most difficult problem and see if we can resolve it
In 2012, the management eyed the international market and grew by having sales offices in Europe and then in India, to service India and the Southeast Asian markets. “Although there was interest, the Indian market was not ready because of the absence of good quality of data,” explains Suvro Banerjee, managing director (Asia Pacific). By late 2015, the Indian market opened and the company had signed up deals with a few leading companies. “We are learning how businesses work in India. We had to be patient as the Indian market is different, but we made a conscious decision to stay.”
The company started an engineering centre in 2014 in India and hired the talent from IIT Kanpur. Gradually, it has been able to move much of the development work done in the U.S. to India. In 2015, Fuzzy Logix also received Series-A funding of US$ 5.5 million from New York-based New Science Ventures that was used to expand the team and build the product offering. The company has increased its team strength in India from 10 to 30 while globally, it employs 65 people. Since inception, it has established six more sales offices in Europe. While the high level design strategy is planned in the U.S., the development happens in India. The American expansion has slowed, though it continues to have the highest number of clients at 16, followed by five in Europe and three in Asia, across industries. Its clientele includes the likes of Blue Shield of Tennessee, Caterpillar, Lloyds Bank, Tesco, Gilliard and HDFC Bank, among others.
Toughest task first
“We are called upon when organisations face issues with asset performance and SLAs are not efficient. We tell the potential customers to give us the most difficult problem and see if we can resolve it,” explains Banerjee. This way, Fuzzy Logix is able to prove the efficiency of its systems and create a business case that is more convincing than any marketing pitch.
The company also is certified by vendors such as Teradata and Hadoop which adds to its credibility.
It follows two models, the first of which is for traditional platforms wherein it offers a one-time license with a lifetime validity for any number of users. The second model is a pay-per-use model which is more popular in India.
One step ahead
The first of the big challenges Fuzzy Logix faced was the inertia and resistance to change. “Those with an appetite for risk try us,” says Banerjee. “We also tell our customers not to throw away their existing solutions but to only migrate the most difficult problems to us. Once they have the confidence, then they gradually effect a total migration,” he adds.
Getting clear and dependable data is the second challenge. The third is that being a small company, it lacks the bandwidth of servicing disparate locations. To overcome this, the company is seeking funding to expand its global presence and expects to receive a fresh round soon from New Science as well as other investors.
While there is competition and that is strengthening, Fuzzy Logix has the early mover advantage and the 800 plus algorithms it has created will be difficult to match. “Such development takes time. So though we are smaller, we have time on our side,” says Banerjee with modest confidence. It is the only company with specific focus on the ‘in-database’ space and plans on continuous improvement of its product to suit the growing needs of its users.
Research and Development
Research and development forms a key part of the product development strategy for the company, which spends about 10 per cent to 15 per cent of its top-line on it. “That is also one of the attractions for IIT graduates as they get to work in this area,” he points out.
Apart from the core product, Fuzzy Logix has also developed complementary products that will facilitate the use of its products with other similar products so that the customers do not have to abandon their earlier investments.
The company is also developing data model templates based on basic business logic to speed up the time to market.
Making analytics ubiquitous
Making data analytics more affordable and widespread in an organisation, with simpler and efficient application will remain the main goal for Fuzzy Logix, which has been growing at a rate of 30 per cent to 40 per cent, which it expects to maintain in the years to come. “It should not be confined to the business intelligence group or the data scientists but benefit every department,” opines Banerjee. For that, the analytics engine should be made as simple to use as the smart phone. The company’s vision is to make it more universal, not confined to specialists.
With new infusion of funds, Fuzzy Logix expects to strengthen its presence in existing markets and grow new markets. It will continue to strengthen its in-database engine and believes that data analytics should be accessible to every department in every organisation as the insight can help improve operations.