I build automation tools that kill busywork β from Excel macros to full desktop platforms.
finsight Python Β· CustomTkinter Β· pandas Β· scikit-learn Β· SQLAlchemy β Enterprise lending analytics & automation desktop suite (NBFC/FinTech). 10 modules: executive KPIs with a Business Health Score, offline natural-language querying, SQL studio, reconciliation engine, one-click MIS packs, forecasting/risk analytics, and an audited task scheduler. 62 tests, CI on Ubuntu and Windows, ships its own synthetic lending book so it runs in 5 minutes.
visionqc Python Β· OpenCV Β· scikit-learn Β· FastAPI β Automated visual quality-control platform: classical CV defect detection (~2,500 img/s multi-threaded) + explainable ML classification (0.99 cross-val), REST API with audit trail, Docker, fully reproducible CI.
filesmith Python β Rule-based file organizer CLI: sort, dedupe (SHA-256), archive by YAML rules β dry-run by default, full undo journal.
xlforge VBA + xlforge-web TypeScript β Excel automation toolkit twice: desktop VBA (100k+ row cleaning, instant reports) and its Office Scripts + LAMBDA rebuild for Excel on the web.
Python Β· pandas Β· scikit-learn Β· OpenCV Β· SQLAlchemy Β· FastAPI Β· CustomTkinter Β· TypeScript Β· VBA Β· SQL Β· GitHub Actions Β· pytest
Dry-run by default β destructive actions are opt-in, never a surprise.
Every tool leaves an audit trail β automation you can't audit is automation you can't trust.
Measured, not assumed β benchmarks and tests over folklore.
If a non-developer can't tell what it did, it isn't done.
GitHub: @kristic8998