TrusLex

Metrics and categorization when checked for a state like Louisana
Metrics and categorization
Dashboard ensuring data visualization for other countries
Metrics and categorization when checked for a country like India
Homepage to upload files we want to query about
Dashboard ensuring data visualization for US states
When clicked on notable case specific for Louisiana (hyperlink)

Inspiration

What it does

How we built it

Challenges we ran into

Inspiration

We built TrusLex to transform fragmented AI litigation records into a structured, queryable system for geospatial and temporal legal analysis.

What it does

TrusLex is an interactive litigation analytics platform that visualizes AI-related lawsuits across jurisdictions, industries, timelines, and claim categories.

How we built it

We built it by creating a normalized legal-data pipeline, mapping case metadata into a searchable schema, and surfacing it through a web-based geospatial dashboard with dynamic filters.

Challenges we ran into

The biggest challenges were cleaning inconsistent case data, defining reliable taxonomies for legal claims, and ensuring the analytics layer did not distort complex legal context.

Accomplishments that we're proud of

We built a functional legal-intelligence prototype that converts raw case records into an accessible analytics engine for rapid trend discovery and policy-facing insight.

What we learned

We learned that effective legal-tech products depend on strong data modeling, careful classification logic, and transparent visualization of uncertainty in evolving datasets.

What's next for TrusLex

Next, we plan to expand the ingestion pipeline, improve classification accuracy, add case-level drilldowns, and scale the analytics stack for broader AI litigation monitoring.

Built With

Submitted to

Trustworthy AI Hackathon

Created by

I worked on the frontend, and honestly it was my first time doing this much front-end work, so it was a bit intimidating at first. But during the hackathon I learned a lot while building the UI, making it look clean, and helping make the app easy to use. It was a really fun experience because I got to step out of my comfort zone and still contribute something meaningful to the project.

Chiranjib Samantaray
I worked on the data side of the project, taking the raw DAIL spreadsheets and transforming them into the structured JSON needed for the dashboard. I turned the tabular case data into visual‑ready information that powers the maps, charts, and case detail views. and I worked in front end a bit on filters with data retrieval and worked with Dipesh on backend.

Saketh Bandlapalli
I was responsible for developing the dashboard and backend architecture of TrusLex, building the system that transforms raw AI litigation data into an interactive and accessible platform. On the backend, I implemented the Node.js server to handle data processing, routing, and structured integration of the litigation datasets, ensuring efficient data flow and scalability. On the dashboard side, I designed and developed the interactive visual interface that allows users to explore AI lawsuit trends by state, industry, and time, making complex legal information clear, searchable, and insight-driven. My focus was on creating a seamless connection between data and visualization to deliver meaningful, policy-ready insights.

Dipesh Amit Shah

Updates

Chiranjib Samantaray started this project — Mar 01, 2026 01:42 AM EST

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