Inspiration
Injury law moves fast where insurance companies issue "tenders" offering policy limits that can vanish overnight, leaving plaintiffs' lawyers scrambling through emails, texts, and calls to respond. Inspired by Morgan & Morgan's high-volume caseloads and Tinder's addictive swipe interface, we built "Tender for Lawyers" to help legal teams swipe right on high-impact actions at a much faster pace.
What it does
Tender orchestrates multi-channel legal inputs (emails, client portals, call transcripts) via a central AI hub. It routes to specialized agents that give clear recommendations via a Tinder-style interface.
How we built it
Python: TStreamlit + Plotly Express Data: Pandas + NumPy Caching: Deployment: Streamlit Cloud / Heroku / Railway
Challenges we ran into
Getting the local host test server to work in order to have a proper simulation.
Accomplishments that we're proud of
Produced a big potential project that would grow big.
What we learned
Legal AI needs airtight privacy (we anonymized PII via regex); multi-agent systems shine for parallel tasks but require strong orchestration.
What's next for Tender for Lawyers
HIPAA certification, integrations with Clio/LexisNexis, predictive tender scoring via ML on settlement data, mobile app, and enterprise pilots with firms like Morgan & Morgan.
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