💰 Financial Performance

Revenue Growth by Segment

Not disclosed in available documents. The company operates a subscription-based model with a 'Hobby Investor' tier at INR 0 and an 'Active Investor' tier at INR 4,999 per year.

Geographic Revenue Split

Not disclosed in available documents, though the product is 'Made with love in India' and uses data from C-MOTS Internet Technologies Pvt Ltd, suggesting a primary focus on the Indian market.

Profitability Margins

Not disclosed in available documents. Pricing for the premium tier is INR 4,999 per year, which is inclusive of GST.

⚙️ Operational Drivers

Raw Materials

Financial data feeds (100% of core product data), AI processing credits (valued at INR 500 for premium users), and software development labor.

Import Sources

India (Data provided by C-MOTS Internet Technologies Pvt Ltd).

Key Suppliers

C-MOTS Internet Technologies Pvt Ltd (primary data provider).

Capacity Expansion

The platform is currently expanding its feature capacity to include Concalls, more screening ratios, and qualitative data to increase the value proposition of the premium tier.

Raw Material Costs

Not disclosed in available documents. Procurement strategy involves sourcing 10 years of financial data and commodity trends for 10,000+ products.

Manufacturing Efficiency

The platform offers 800 stock alerts and unlimited key insights for premium users compared to only 10 alerts and 20 insights for free users, representing a significant scaling of digital service delivery.

Logistics & Distribution

100% digital distribution via web and mobile platforms.

📈 Strategic Growth

Growth Strategy

ASHWINI aims to drive growth by converting free 'Hobby' users to 'Active' investors (INR 4,999/year) by offering 80x more stock alerts (800 vs 10), unlimited concall notes, and advanced Excel automation features. Future growth is targeted through the addition of qualitative data and concall analysis tools.

Products & Services

Stock screening tools, Screener AI insights, Commodity price trackers, and shareholder search engines.

Brand Portfolio

Screener, Mittal Analytics.

New Products/Services

New features in development include Concalls, qualitative data modules, and expanded screening ratios, intended to increase premium conversion rates.

Strategic Alliances

Partnership with C-MOTS Internet Technologies Pvt Ltd for data provision.

🌍 External Factors

Industry Trends

The fintech industry is shifting toward AI-driven qualitative analysis. ASHWINI is positioning itself by integrating 'Screener AI' and developing concall note features to move beyond basic quantitative screening.

Competitive Landscape

Competes with other financial data providers and stock research platforms in the Indian market.

Competitive Moat

The moat is built on 10 years of historical financial data, a proprietary custom ratio engine, and high switching costs for users who have integrated their research into the platform's Excel automation tools.

Macro Economic Sensitivity

Highly sensitive to stock market participation rates; a decline in retail investor activity would likely reduce the demand for 'Active Investor' subscriptions.

Consumer Behavior

Increasing demand for DIY (Do-It-Yourself) investment research tools among Indian retail investors.

Geopolitical Risks

Low, as the company is focused on Indian financial data and domestic 'Made in India' development.

⚖️ Regulatory & Governance

Industry Regulations

Subject to Indian data privacy laws and financial data redistribution regulations.

Taxation Policy Impact

Standard GST applies to all subscriptions; the INR 4,999 price is inclusive of GST.

⚠️ Risk Analysis

Key Uncertainties

The primary uncertainty is the accuracy of third-party data provided by C-MOTS, which could impact the reliability of the screening results.

Geographic Concentration Risk

100% focused on the Indian equity market based on the data sources and 'Made in India' branding.

Third Party Dependencies

Critical dependency on C-MOTS Internet Technologies Pvt Ltd for all financial data feeds.

Technology Obsolescence Risk

Risk of being superseded by more advanced AI-native financial research tools if the 'Screener AI' does not evolve rapidly.

Credit & Counterparty Risk

Low risk as the business model is based on upfront annual subscription payments.