“Our Strategy is to Outperform the Competition Using AI and ML” Says Sridhar Seshadri

Artificial intelligence and machine learning are making deeper strides into everyday operations. But unfortunately, not many businesses are able to leverage the new-age technologies because it requires a hectic process of model building and requires regular monitoring, given the changes in data can impact the model tremendously. Spotflock, an AI product building and servicing company says model as a service is what differentiates them as a key player operating in a diverse set of verticals. Analytics Insight has engaged in an exclusive interview with Sridhar Seshadri, an ex-Meta & ex-EASports industry veteran and Co-Founder of Spotflock Technologies.

 1. Kindly brief us about the company, its specialization, and your products.

As a Deep Tech company, Spotflock Technologies specializes in Artificial Intelligence – ML, NLP, Chatbots, Computer Vision, Blockchain, IoT, and AR/VR. We delivered multiple product licenses & solutions to Energy/Utility segment, EdTech, Cyber Security, Healthcare, Well-being, FinTech, Media & News, Social & Mobile Gaming, & Social Media verticals.

We currently focus on eGov, SportsTech, and B2C platforms. Our core product is Intellihub, a DeepTech enterprise offering that reduces time and effort for large corporations in digital transformation. 

2. How is Intellihub contributing to making products and services for private and public sector entities?

Intellihub contributes to enterprises and government departments in various ways. From automating business processes and gaining insights through business intelligence and artificial intelligence to evidence-based audibility through blockchain. 

Our core offering is in Deep Tech, a universal self-servicing AI platform with IoT extensions and microservices. Our hybrid cloud platform can add proprietary algorithms and best-of-the-breed handpicked AI algorithms from various platform pioneers like H2O, Google's Tensorflow, Weka, etc. 

We have implemented AI to assist public sector entities like micro-irrigation, energy, telecom, governance, and grievance management services.

3. Which industry verticals are you currently focusing on? And what is your go-to market strategy for the same?

Spotflock is focused on AI & Blockchain solutions for e-governance and Sports Tech. We use DeepTech for e-governance using core AI, business analytics, business intelligence, and blockchain-based solutions. 

Spotflock's sports tech vertical has recently built AI-powered e-commerce platforms, applications that manage booking and scheduling, community-based applications, and analytics for golf academies. 

Our strategy is to outperform the competition using cutting-edge AI and machine learning technology. With a clear and compelling data strategy, ensuring clients' success, which translates into Spotflock's growth.

4. How has the adoption of Deep Tech in India evolved over the last few years?

India is a thriving hub for cutting-edge deep-tech companies with huge potential to develop products and services for the global markets. Per Nasscom's India DeepTech Startup Report, in the last 5-7 years, the Indian deep-tech ecosystem has grown significantly, with over 3000 deep-tech startups in India as of 2021, growing at a staggering rate of 53% CAGR in the last ten years, hence employing over 4000 individuals spread over 14 potential deep-tech unicorns.

India is at an early stage of adopting deep tech, and there is tremendous potential across the sectors, and the need for mindset change is the order of the day. Once Indian corporates adopt these tools and start tasting the success, we will be the fastest adopters of tech, and I am sure in the next three to four years, the landscape in India will be ripe for Deep tech. 

5. What is the edge your company has over other players in the industry?

Spotflock, over the years, has built a competitive advantage in three areas, i.e., platform, products, and processes. Our hybrid AI platform's cloud supports other platforms, and our SDK for Data scientists supports all 3rd party best of breed platforms with support for interoperability and model-as-a-Service offering. 

We have built products focusing on portfolios such as energy, finance, blockchain, healthcare, sports analytics, and e-commerce, thus enabling our Service Integrator partners to sell repeatable offerings and solutions. Finally, about the process, we have created a corporate culture that attracts the best talent; we focused on increasing our core technology competencies to create value for our customers. When faced with stiff competition, these areas gave us that competitive edge.

6. Would you like to highlight a few use cases where AI has benefitted the organization tremendously?

We have multiple use cases of AI/ML in energy consumption, savings, and smart electricity price bidding offering. We created a load forecasting model for exchanges with models giving up to 92% accuracy with recurring DSE methodologies like dataset cleaning, correlating different databases, and missing value imputations with the model with an accuracy of 80% after which few in-house methodologies were used to increase the accuracy. In addition, we have use cases in automated attendance management systems using CV, drowsiness detection using CV and smart triaging using ML.