ride-insightsv0.1.3

A user fetches their Uber, Lyft, and Bolt receipts from Gmail, extracts ride details using a local AI model, and stores them in SQLite for analysis. They can then query total spending per provider, average trip cost, and identify the most frequent pickup locations. This helps track commuting costs or prepare a budget.

A freelancer or small business owner uses ride-insights to automatically collect ride receipts for tax reporting or client reimbursement. The anonymized CSV export provides a clean record of trip dates, distances, and costs without exposing personal email content. This simplifies expense reporting.

A city planner or researcher aggregates anonymized ride data from multiple users to analyze congestion hot spots, peak travel times, and popular routes. The skill's local-only design ensures sensitive data never leaves the user's machine, making it suitable for privacy-conscious studies.

A user generates an anonymized CSV of their ride history and uploads it to DataHive to earn points. The skill automatically strips direct identifiers like names and email addresses while retaining valuable mobility insights. This encourages data sharing for rewards without privacy risk.

Offer the basic skill for free to individuals who want to track and analyze their own ride history. Introduce a premium tier with advanced analytics like predictive spending, route optimization suggestions, or multi-year trends.

License the skill to companies that manage employee transportation expenses. The SQLite database and CSV export integrate seamlessly with existing expense reporting tools. Provide white-label customization for corporate branding.

Aggregate anonymized ride data from consenting users and sell insights to mobility companies, urban planners, or marketers. The skill's privacy-first design (local extraction, anonymized export) builds trust and ensures compliance. Users earn a share of revenue via DataHive points.