Knowledge Foundry: Delivering Customized Analytics Solutions for Better Business Prospects

Raj Bhatt

Knowledge Foundry (KF) is a bespoke end-to-end analytics solutions firm. Since 2008, the company has been serving global clients with business problems across the areas of marketing and operations. The capabilities of Knowledge Foundry span statistical modeling, machine learning, text analytics, optimization and visualization solutions. It serves clients in retail, healthcare, media, telecoms, banking, and B2B.


Their marketing analytics solutions include segmentation, media mix optimization, predictive analytics, churn prediction and campaign RoI assessment. Their operational analytics solutions include forecasting, promotional optimization, retail merchandising analytics, fraud detection, and delinquency prediction. The company is also active in the evolving areas of computer vision for image analytics and video analytics.


KF was set up with an objective to deliver customized analytics solutions to clients. There are many areas where companies require customized analytics solutions:


• Advanced areas such as computer vision and text analytics, where the latest algorithms have not been productized within existing IT systems.


• Business problems where data has not traditionally been available in a single database and therefore are not available as tools in IT systems e.g., retail promotional analytics, Media Mix Optimization. 


The company saw (and still sees) most analytics service providers delivering resourcing/staffing services or process outsourcing. Not many of them are capable and/or interested in delivering high-end customized solutions for clients’ pressing business problems. That is the big need gap that KF caters to.



The Visionary Driving Unique Business Solutions


Knowledge Foundry’s CEO, Raj Bhatt, has been involved in the Indian analytics services industry since 2006. He was working in the US with consulting firms such as Booz & Co (now Strategy&) and CSMG Adventis prior to that. He returned to India and joined an analytics startup called Marketics as he saw the wave of analytics and data-driven decision-making hit Indian shores. 


At Marketics, Raj was heading a few verticals and the New Business Division that solved business problems for new prospects and clients. His team worked with retailers (Tesco, Sainsbury, Staples, Office Depot), Banks (M&T Bank, Emirates NBD, Fifth Third Bank) and Insurers (GEICO, Safeco). Marketics grew rapidly to 350+ employees and double-digit million dollars in revenue and was acquired by WNS in 2008.


Raj started Knowledge Foundry with Girish Ramachandra and a few other ex-colleagues in 2008. From the very beginning, the focus of the company has been customized solutions rather than commodity services. 


To support its unique business model, KF goes to market in alliance with IT services firms, consulting firms, and other partners. The company focuses on its core competency of delivering innovative solutions, and leverages the sales capability of its alliance partners significantly.



Dimensions for Distinctiveness

According to Raj Bhatt, the company differentiates itself on the following dimensions:


1. It focuses on customized end-to-end solutions and does not work in staff augmentation and process outsourcing.

2. The company has a low-risk, pilot-based approach to business problems.

3. KF adopts an agile methodology to deliver a solution. This reduces implementation time to weeks rather than months.

4. It is technology-agnostic. The company works with a variety of open-source languages/frameworks (Python, R, Spark) and algorithms and with all major cloud infrastructure providers (AWS, MS Azure, Google).

5. Knowledge Foundry has a track record of delivering 10X return on investment.



Disruptive Technologies Leading Innovation


Raj believes that the ability to rent GPUs on the cloud, access to APIs for well-trained ML algorithms (e.g., Google Cloud, Posenet, etc.,), and availability of open-source training datasets have thrown open the world of Machine Learning, Computer vision and Text Analytics to all companies in the world. Using these resources along with well-labeled internal data allows innovative companies to solve business problems that could not be imagined five years ago. Some examples include:


• Image-based recommendation systems in retail

• Facial recognition-based access systems

• Automated detection of diseases from medical scans

• Self-driving cars



Valued Client-Testimonials


“This team has been working with me for nearly 5 years now. They support a variety of initiatives, one of them being the development of a scalable content recommendation system to help push relevant content on our website. They also helped create a tactical framework for A/B testing of our “Increase-Rx” campaigns on a weekly basis. More recently I have been closely involved with them to develop a robust framework for identifying campaign drivers and measuring campaign effectiveness, one that overcomes the limitations of the popular ANCOVA. In summary, KF has been very responsive to our requirements, able to deal with challenges arising out of multiple data sources, and able to come up with very practical solutions.” – VP, Data Science for a Healthcare Media Company


“The team worked with us to develop the positioning of one of our core personal care brands. Their work enabled us to test and choose the most appropriate messaging plank. Using superior technical expertise, and hard work they helped us develop a clear brand mapping in a very competitive marketplace. They are a thoroughly professional team and consistently deliver to exacting timelines and high expectations. I liked the flexibility in their approach that allowed them to bring a customized solution to the table as well.” – General Marketing Manager, Large CPG company



Winning Against Challenges

Knowledge Foundry started in 2008, the year of the global recession. The Lehman Brothers and Bear Stearns fiascos happened within a few months of its founding. Prospects who had promised the company business told it to come back after a year. The company survived that period and was able to thrive when it clearly defined its offering and target market.



Futuristic Implications 


Raj believes that automation and productization will impact commodity service providers significantly in the coming years. Only those with niche solutions will be able to survive.

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