--- title: "Delhi student builds AI-powered platform to report bribe demands" url: https://projectchintan.com/article/ai-platform-report-bribes-india-s72v3 publisher: Project Chintan author: Project Chintan Newsroom section: Society published: 2026-08-18T08:37:26.727Z modified: 2026-08-18T10:30:06.781Z language: en-IN --- # Delhi student builds AI-powered platform to report bribe demands A Delhi-based B.Tech student launched Bribes.fyi, an AI-assisted civic-tech platform that lets Indians anonymously report bribe demands. By Aug. 17, it aggregated hundreds of reports across over 250 cities, highlighting patterns by department while cautioning that data is self-reported. ## Key takeaways - Bribes.fyi enables anonymous reporting of bribe demands across multiple Indian government departments. - The platform aggregates reports into a searchable map showing patterns by city and department. - As of 17 August, hundreds of reports existed across more than 250 cities, with police departments providing the most submissions. - Over one-third of reports indicated refusals, though some users still accessed services. - Data are self-reported and not an official measure of corruption; the platform uses AI-assisted coding to build the tool. ## What Happened A Delhi student, Aryan Nishad, created Bribes.fyi, a platform designed to collect anonymous reports of bribe demands encountered while accessing government services. The project, developed while Nishad studied at Maharaja Agrasen Institute of Technology, was launched on 2 July. Users can quickly submit details about the bribe, including the government department involved, the city, the amount allegedly demanded, the purpose of the payment, and whether they paid or refused. Submissions are posted anonymously and later organized into a searchable database. The platform maps reports across Indian cities and departments, and displays a live-style visualization in which departments such as the Police, RTO, Revenue and Land Records, Passport Office, Municipal Corporation, GST, Electricity Board, Income Tax, and the Food and Drug Administration are included in its categories. Reports are searchable by city and department, enabling patterns to emerge from multiple submissions rather than relying on a single account. As of 17 August, Bribes.fyi contained hundreds of reports from more than 250 cities. The police departments accounted for the highest number of submissions, according to the platform’s public-facing data. In addition, the platform notes that more than one-third of reported incidents were marked as refusals, though some users indicated they still received the service they sought. The site cautions that its data are self-reported and should not be treated as an official measure of corruption. Technically, the project is notable for its use of AI-assisted coding. Described as “vibe coding,” this approach uses AI tools to generate and refine software through natural-language instructions rather than writing every line of code manually. The broader aim is to show how citizen-sourced experiences can be organized into a usable civic data resource, rather than to confirm corruption levels on its own. ## Why It Matters Bribes.fyi illustrates a path for converting individual experiences into a collective data set that can be analyzed for patterns across locations and government departments. By enabling anonymous reporting and providing a centralized map and search interface, the platform pushes a data-forward approach to everyday corruption experiences, potentially informing public discussion and policy considerations about governmental service delivery and accountability. ## Background The project emerged from a university setting and is described as a privacy-first space for reporting bribery incidents without requiring user accounts. The creator, Aryan Nishad, is identified as a B.Tech student in Delhi. The platform’s design centers on turning private transactions into shareable, searchable information in order to reveal patterns that might be overlooked in isolated reports. The development approach employs AI-assisted coding, a method that accelerates building functional software by leveraging AI to draft and refine code based on natural-language prompts. ## Key Facts - Creator: Aryan Nishad, B.Tech student at Maharaja Agrasen Institute of Technology, Delhi - Platform: Bribes.fyi - Launch date: 2 July - Reporting method: Anonymous submissions including department, city, amount, purpose, and payment status - Data presentation: Searchable database with a map and department/category views - Departments currently tracked: Police, RTO, Revenue and Land Records, Passport Office, Municipal Corporation, GST, Electricity Board, Income Tax, Food and Drug Administration - Geographic reach by 17 August: Reports from more than 250 cities - Reported refusals: More than a third of cases marked as refusals - Data caveat: Self-reported; not an official measure of corruption - Technology note: Built with AI-assisted coding (vibe coding) to generate and refine software via natural-language instructions ## What Happens Next The material available focuses on the platform’s existence, its design, and the extent of the initial data collection as of mid-August. No scheduled or official next steps are documented in the provided material beyond ongoing data collection and public display of submissions. --- Canonical: https://projectchintan.com/article/ai-platform-report-bribes-india-s72v3 Reported from: Multiple Sources