Google search for internal databases. Our users can interact with databases in plain English
In the next five years, the demand for data analyst roles will grow by 700k in the US alone with the supply projected to be 30% below the demand. Nearly 25% of a data analyst’s time is spent on fulfilling ad hoc requests. The competence level of AI in the market has also evolved to convert natural language to querying languages at much greater accuracy and speed rivaling experienced data analysts. All three factors combined together provide a strong tailwind for us. Now is the right time for us to build our AI to take care of the ad hoc requests, relieve valuable time for data analysts, and hence solve the supply gap. We believe our value proposition will be a strong problem solver for enterprise businesses in their data analytics arsenal.
Our product will be serving an evolving blue ocean market. We have put together one of the world’s best AI technologies for our product’s Natural Language processing capabilities. As we are one of the earliest products to solve this problem, our product evolution through early customer feedback will maintain our competitive advantage over newcomers. We also deploy the best security and privacy practices for our customers’ data. In fact, our setup doesn’t even require visibility into the customers' data enabling better customer trust in us. The existing substitute products in the market typically serve the analyst persona and have hardly scratched the use cases for the business user persona that we are targeting.
Our MVP is ready to be deployed. In line with our product and financial goals, in the next quarter, we want to onboard five enterprise customers as beta testers. We want to offer our product free of charge to these customers and collect their feedback which is critical to the evolution of our AI to handle complex business queries. We have planned our public launch of our AI towards the end of 2021 after completing the improvements realized from our beta trial. $10k will help us focus on customer feedback and product improvements during our beta trials by taking care of our infrastructure costs, customer support, and product development expenditures without the need for additional fundraising during the beta testing phase