Cxo Insights: Anand Mahurkar, Founder & CEO, Findability Sciences

Findability Sciences is an Enterprise AI Company that helps businesses worldwide realize the potential of data. Findability Sciences works with 40 Global clients and has presence across US, India and Japan. The company enables customers across industries and geographies to accelerate their Data-to-AI Journey enabling them to build their own IP and data science capabilities, besides executing strategically to derive real financial ROI. In simple terms, Findability Sciences drives digital transformation in traditional enterprises by making them data superpowers.

Anand is an Artificial Intelligence (AI) and Data Technology innovator and a seasoned professional who believes in accelerating transformation in traditional enterprises through the power of data, helping them become “data superpowers”. His education provided a solid ground for a career of over 30 years of experience in leading global businesses. Ever since his first job, he was determined to build his own venture in advanced technology like Artificial Intelligence. His entrepreneurial spirit, persistence, and consistency with the changing dynamics of technology helped him establish Findability Sciences, a company with the goal to equip enterprises with ‘The Ability to Find Information’.

Recently we have engaged in an interview with Anand Mahurkar, Founder & CEO, Findability Sciences. He shared his views on how are disruptive technologies like AI impacting today's innovation and also share his journey so far.

Introduction.

Findability Sciences is an Enterprise AI company that helps enterprises accelerate growth and optimal ROI. We provide services that help businesses to upscale themselves and grow using the potential of data. We started our journey of enabling customers across industries and geographies to make them AI-ready in 2018. Our award-winning proprietary platform, Findability.ai, empowers businesses worldwide as we solve their most complex and critical business challenges. In simple terms, we drive digital transformation in traditional enterprises by making them data superpowers.

Kindly brief us about the company, its specialization, and the services that your company offers.

While we were building this company from scratch, the initial step was to build the scope and size of the company. We progressed technologically, adding Big Data, Cognitive Computing, and Automated Prediction technologies to our portfolio of services. In 2018, we got a push from Softbank through Series A funding and a joint venture that helped us address the Japanese market. As of now, we are a global company with more than 40 clients around the globe. We’re headquartered in Boston and have a solid presence in India and Japan because we think these markets show tremendous potential.

We built products around AI, helping our clients speed up their AI transformation journey and help them make better decisions based on the insights from their datasets. Thus, we have specialized expertise in developing AI platforms and tools that can be leveraged to improve the financial ROI of our clients.

Some of the key products and services that are a part of our portfolio are Findability. Accelerate, ERP.MAX, Findability. Inside, Findability.AI, Findability. DSL. The former key product, FS. Accelerate is our latest offering that helps organizations build the foundation for enterprise data and AI adoption. It combines the expertise of our partner product offerings from some leading AI firms, including IBM, Snowflake, SAP, and Automation Anywhere. These are complete solutions to boost the financial state of your company, helping clients across verticals such as Manufacturing, Telecom, Retail, Professional Services, Financial Services, and Government.

How are disruptive technologies like AI impacting today's innovation?

According to a recent report by Bain & Company, the AI market is experiencing widespread awareness and acceptance among both organizations and providers. This shows that artificial intelligence has limitless potential. Businesses may now be equipped with in-depth insights and practical recommendations by utilizing AI without going through the time-consuming normal processes since business operations are becoming more data-driven than ever.

AI has been used to implement many technologies like Computer Vision, Machine Learning (ML), and Natural Language Processing (NLP) – it helps in AI-based virtual assistants are becoming essential to most organizations’ customer service lifecycle and engagement strategies. Also, based on wide data from multiple sources, AI can help predict business outcomes, allowing companies to make rapid decisions. With AI at the backend, companies deliver a smarter, enhanced, and seamless experience in the solution’s native environment for end-users. These AI solutions can be utilized for price optimization, prediction and forecasting, segmentation and targeting, sales prospecting, customer service, and more.

What, as per you, are the five important things that Findability Sciences should be looking at today?

As an enterprise AI company, the essential thing for Findability Sciences is to help enterprises reap the maximum benefit of this technology; therefore, the five important things are:

 Focus on Getting the Data Fabric in Place: When traditional enterprises establish a robust data framework, organizations can leverage data effectively for AI purposes. Organizations must have the correct data infrastructure architecture (IA) to gain better insights and have the ability to make more accurate predictions.

AI White-Labeling: Many traditional organizations understand the importance of AI but struggle with its adoption and deployment. Properly and efficiently embedding AI into existing infrastructures requires companies to “white-label” AI to create configurable and customizable solutions can lead to a capability differentiator for enterprises.

Building a COE (Centre of Excellence) for AI: AI needs an “all hands-ondeck” approach as an AI implementation requires an organization to centralize and organize its data infrastructure. Building a COE with team members from multiple areas of an organization and outside vendors can be a windfall for AI transformation.

AI-ified ERP Systems: AI microproducts or toolkits that can be used to connect to ERP systems through middleware. This middleware can link to data within the organizations from the ERP systems. The middleware can then feed into the leading AI platform to develop, select, and deploy ML models to provide highly accurate predictions and forecasting.

NLP and Computer Vision: These technologies will allow customers, vendors, and employees to ask questions that can be easily answered through automated processes, as in a chatbot.  It can scan documents and retrieve relevant information instantaneously. AI has enabled quality assurance teams to analyze inputs, outputs, and simulated data for anomalies.

Explain the challenges customers face to have AI in place and how are Findability Sciences helping businesses.

We are an enterprise AI company, so our customers mainly include enterprises wanting to leap ahead with AI technology to improve business intelligence for faster processes, better financial ROI, develop better products and services, and a few others depending on the industry. To reap these benefits, businesses must set up an information architecture (IA) that allows AI to develop insights.

The main concern lies in having a sound data infrastructure in place, or they will struggle to maximize the value of their data. Organizations must utilize data in the same way that oil firms use crude oil and farmers use their land and crops to generate profit:  identify the sources, plant the “seeds,” extract the impurities, refine, store, and pipe them, build the infrastructure for distribution, nurture, cure, safeguard, and yield it. AI solution providers can work with enterprises on these obstacles and implement frameworks that will strengthen the infrastructure architecture (IA) so that it can more successfully implement AI.

Kindly mention some of the significant challenges the company has faced till now.

In the initial years of starting Findability Sciences, beginning the journey alone and bootstrapping the business was difficult. Financial challenges were a huge hurdle and scaling the operations without external support was also challenging. However, we focused on building the scope and size of the company. We rapidly introduced new solutions, including Big Data, Automated Prediction, etc., to generate revenue, which helped us create yearly profits.

Our game-changing moment was in 2018 when Softbank decided to invest in our company through Series A funding and set up a joint venture with us to cater to the Japanese market with enterprise AI solutions. We have consistently focused on demonstrating value by providing innovative solutions to customers. Despite the challenges, we have grown tremendously from a single-person company to now with 150+ team members working with prominent organizations across the globe. Our perseverance has helped us attract the best teams and resources we have today.

How are Big Data and AI evolving today in the industry? What are the most important trends that you see emerging across the globe?

Big data and AI are proving their value to organizations of all sizes and industries. Enterprises that use AI and big data are realizing tangible business benefits, from improved efficiency in operations and increased visibility into rapidly changing environments to optimizing products and services for customers.

Some emerging trends that we foresee are:

• Predictive Analytics: Big data analytics has always been a fundamental approach for companies to become a competing edge. They apply basic analytics tools to prepare big data and discover the causes of why specific issues arise. Predictive methods are implemented to examine modern data and historical events to know customers and recognize possible hazards and events for a corporation. Predictive analysis in big data can predict what may occur in the future. This strategy is highly efficient in correcting analyzed assembled data to expect customer response. This enables organizations to define the steps they must practice by identifying a customer's next move before they even do it.
• Hybrid Clouds: Hybrid cloud provides excellent flexibility, and more data deployment options by moving the processes between private and public clouds. An organization must have a private cloud to adapt to the aspired public cloud.
• Natural Language Processing: Big data, AI, IoT, and machine learning are pushing the boundaries of human and technological interaction. It gives these technologies a human face through natural language processing (NLP). Raw processing will help people engage and interact with various intelligent systems with nothing but human language. The more advanced of them will do so with a level that comes with the nuances of the language in use.

What are your upcoming plans?

We are planning some solutions based on the market gaps and consumer demands we have noticed; these solutions lined up for the following year. We can confidently sustain the success streak ahead by empowering enterprises to become AI-driven and thriving.