Business Category: Data Analytics FinTech Technology
Startup Stage: Revenue Generation
Support Required: Funding Mentoring
Structure of the Company: PVT Ltd.
Executive Summary: Textplor is a tool for financial analysis useful for Lenders, Brokerage houses and Accountants. Textplor can help to analyse large textual information and give important insights about the data. Textual information covers announcements annual reports, news social media data.
Market need: • Majority of analytical tools use quantitative information to generate value-sensitive and early warning signals. • Texts in corporate filings and newspapers carry vital, price sensitive information which every lender, investor, and analyst needs to scrutinize before making any economic decisions. • The sheer volume, multiple sources, and complexity of textual information make this an extremely time-consuming exercise. An automated platform is required to extract sentiments out of a large volume of text.
Product/Service description: Texts in corporate filings and newspapers carry vital, price sensitive information which every lender, investor, and analyst needs to scrutinise before making any economic decisions. The sheer volume, multiple sources, and complexity of textual information make this an extremely time consuming exercise. An automated platform is required to extract sentiments out of a large volume of text.
Customers/Users: 1. Legacy 2. Aivot 3. VSinghi
Revenue Model: • Textplor is a SaaS product with two models of subscription- monthly and annual. • We charge INR 120,000 for annual subscription and INR 12,000 for monthly subscription (billed on quarterly basis) per user. • All upgrades are offered free to the active subscribers. • We hope to reach an annual revenue of INR 7 million by end of FY2023.
Current traction: • Sentiment extraction from large text using deep learning is major strength of our products. • To the best of our knowledge, Textplor is the only platform that provides analysis on text of Corporate Annual Report. The effectiveness of the text-based default prediction tool is tested on more than 4000 companies. • Our product does not compete with existing financial analytics products that use quantitative information. • NIS uses powerful algorithm to check whether a news is relevant to a specific company or not. Our algorithm captures sentiment correctly even when the news talks positive about one company and negative for others. • Audit related information and alerts like change in auditor complexity of audits.