grep, jq, ETL, and forensic indexing collapsed into one local SQL primitive
Your audit trail should be a database you own, not a SaaS UI you rent.
Scan directories and query file metadata with SQL. Plus: Transform CSVs into SQL tables, extract data from HTML with CSS selectors, parse Markdown and XML into queryable JSON.
2-minute win: Find all PDFs modified in the last 30 days
Bonus: Turn CSV files into queryable SQL tables automatically
Guide 2: Turn Email Into SQL
Use Singer taps to pull data from GitHub, Jira, GitLab, Salesforce, or 600+ other sources. Join across platforms.
2-minute win: Query all GitHub commits from the last 7 days
Why Not Just Write a Script?
You could. But:
Scripts become dead ends.
Six months later, you can't remember what format you used or where you saved the output.
surveilr outputs permanent, standard SQLite databases.
Open them years later with any SQL tool and keep querying.
Scripts don't compose.
You can't easily join your email script's output with your file scan script's output.
surveilr stores everything in one queryable database.
Cross-domain joins just work.
Scripts have no schema.
You're parsing JSON with jq and hoping the structure doesn't change.
surveilr normalizes data into stable SQL tables.
Query with confidence.
Ecosystem Integration
surveilr isn't the destination. It's the ingestion layer.
Once your data is in SQLite, you can use any tool in the SQLite ecosystem:
— Fast analytical queries on SQLite files
— Query in your editor
— Build dashboards from SQLite
.
Run This Now
Pick your 2-minute win:
Option 1: Query your filesystem
CODEsurveilr admin init -d fs.db
surveilr ingest files -r ~/Documents -d fs.db
Option 2: Query your email
CODEsurveilr admin init -d email.db
surveilr ingest imap -u [email protected] -p "app-password" -a imap.gmail.com -d email.db
Option 3: Query GitHub (Ingest Singer taps)
CODEsurveilr admin init -d github.db
surveilr ingest files -r ./github-tap-script.py -d github.db
surveilr orchestrate adapt-singer (convert data to views)
Then open the
.dbfile in any SQLite tool and start exploring.
Learn More
— Download and install
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