jeevacation helps you quickly check whether names from your LinkedIn connections (or any contact list) appear in newly released public records, without manually digging through thousands of pages.
I was drawing some inspiration from the clever EpsteIn and thought could I improve this?
“Who shows up where in these files?”
Below are the fastest ways to get started.
| Task | Command | What It Does |
|---|---|---|
| Run basic scan | python cli.py search --connections Connections.csv |
Checks if names appear in the docs |
| Use AI context | python cli.py search --connections Connections.csv --use-ai |
Adds role + sentiment analysis |
| Export JSON | python cli.py search --connections Connections.csv --format json --output results.json |
Saves structured results |
| Generate graph | python cli.py graph --connections Connections.csv --output network.html |
Builds a relationship map |
| Start web UI | python cli.py web |
Launches browser interface |
| Start API | python cli.py api |
Runs REST server |
Drawing inspiration from the EpsteIn project, jeevacation takes things further by cross-checking your LinkedIn network against the documents to flag possible name matches. From there it can optionally:
- Categorize mentions (witness, staffer, attorney, etc.)
- Add sentiment context (neutral, concerning, benign)
- Build visual relationship graphs
- Monitor for new document releases
- Export findings in multiple formats
It’s designed for:
- Journalists tracking leads
- Researchers mapping connections
- Lawyers scanning references
- Curious readers exploring public filings
Instead of brute-force reading, jeevacation turns document review into something structured, auditable, and fast.
| Step | Command |
|---|---|
| Clone repo | git clone https://github.com/Montana/jeevacation.git |
| Enter directory | cd jeevacation |
| Auto setup | ./quickstart.sh |
| Activate env | source .venv/bin/activate |
| Test search | python cli.py search --connections Connections.csv |
| Mode | Command | Use Case |
|---|---|---|
| Web app | python cli.py web |
Non-technical users |
| API server | python cli.py api |
Integration into other tools |
| Docker | docker compose up --build |
Clean containerized run |
| Feature | Details | Why It Matters |
|---|---|---|
| Intelligent search | Name matching, nickname detection, false-positive filtering | Finds real hits faster |
| AI analysis | Role tagging + sentiment scoring | Adds context to mentions |
| Visualization | Co-mention network graphs | Spot patterns quickly |
| Monitoring | Auto-checks for new document drops | Stay up to date |
| Data layer | SQLite/Postgres + audit logs | Traceable and repeatable |
| Exports | HTML, CSV, JSON | Easy sharing and review |
A name appearing in documents does not imply wrongdoing. Mentions can include:
- Witnesses
- Staff
- Legal professionals
- Victims
- Passing references
jeevacation is a research and discovery tool for public records — not a conclusions engine. Always review source context.