# Lekha-Jokha AI

- **Event:** [Built with Opus 4.7: a Claude Code hackathon](https://cerebralvalley.ai/e/built-with-4-7-hackathon)
- **When:** Apr 21 at 12:00 PM – Apr 27 at 2:00 AM (EDT)
- **Where:** Online
- **Team:** [Harshanand sharma](https://cerebralvalley.ai/u/Harshdev)
- **GitHub:** https://github.com/Harshcoderhacker/lekha-jokha
- **Demo video:** https://youtu.be/MI4h7Mc-3oI
- **Gallery:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/150

Lekha-Jokha is an AI-based investigation tool that aims to empower citizens, journalists, and scholars to make sense of the discrepancy between government claims and actual available public data.

In India, important information related to politicians, public expenditure, audit reports, and various schemes exist. But there is no single source where all such information can be found. Hence, it becomes highly difficult for any citizen to hold their government accountable based on factual data.

This system leverages the Claude Opus 4.7 agent as a reasoning engine to orchestrate multiple domain-specific agents (Assets, CAG, Schemes, News, and RTI). On receiving an input query in natural language, our system:

Extracts structured information regarding politicians’ declaration of assets 
Finds out pertinent CAG audits reports
Analyses allocations and utilization of schemes
Provides news signals
Finds RTI requests to bridge data gaps

Then all this extracted information gets aggregated into a structured dossier of "Claimed vs Actual" discrepancies with proper citation.

Unlike the conventional approach of dashboards, the Lekha Jokha is an AI-powered investigator that finds discrepancies in the fragmented data available in the public space.

---

Markdown version of https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/150. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt