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keremercin/README.md

Hi, I'm Kerem Ercin

Python Automation Engineer | Document AI, RAG, APIs, Internal Tools

Python automation, document AI, and data systems

I build practical Python systems that turn messy documents, web data, and manual workflows into reliable software.

  • Python, FastAPI, SQL, PostgreSQL, web scraping, OCR/PDF extraction, and RAG
  • API-first automation with structured outputs, tests, observability, and clear failure handling
  • Remote async collaboration from Turkey (UTC+3)

Best fit: document workflows, support and lead intake, data extraction, API integrations, internal tools, and AI features that need grounded outputs rather than a fragile chatbot demo.

Engineering portfolio map

Selected Proof

1) legal-doc-ai-pipeline

OCR/PDF ingestion, hybrid retrieval, grounded Q&A, citations, audit trail, FastAPI endpoints, tests, CI, and benchmark artifacts.

Reliable document AI delivery loop

2) ai-automation-toolkit

Webhook-first backend for support summaries, lead enrichment, and document intake with explicit payload contracts and failure-mode documentation.

3) rag-eval-observatory

RAG evaluation API with precision/recall/MRR tracking, failure taxonomy, SQLite run history, regression-ready benchmark outputs, tests, and CI.

4) lead-support-doc-intake

Local-first operations dashboard that classifies inbound events, enriches payloads, and routes leads, support tickets, and documents.

Additional Projects

5) ecommerce-price-intel

E-commerce price monitoring API with snapshot endpoints, alert detection tests, and dashboard-ready analytics outputs.

6) finance-loan-approval-prediction

ML pipeline with model comparison, metrics artifacts, model card, and FastAPI inference service.

7) gym-customer-churn-prediction

Applied churn prediction pipeline with reproducible training artifacts and deployable API endpoint.

What I Can Build In First 30 Days

  • Ship a Python/FastAPI automation service around your existing workflow
  • Build a scraping or data extraction pipeline with clean CSV/JSON/API outputs
  • Add OCR/PDF extraction, RAG search, or semantic search over internal documents
  • Create evaluation baselines, tests, and CI checks so the project is not just a demo
  • Turn a manual spreadsheet/browser/reporting process into a repeatable backend job

Portfolio Index

See PORTFOLIO_INDEX.md for one-page project summary (problem, stack, measurable output, demo path).

Weekly Write-ups

Contact

Pinned Loading

  1. ai-automation-toolkit ai-automation-toolkit Public

    Webhook-first Python automation backend for support summaries, lead enrichment, and document intake

    Python

  2. ecommerce-price-intel ecommerce-price-intel Public

    E-commerce price intelligence pipeline with snapshot API, alert detection, and dashboard

    Python

  3. legal-doc-ai-pipeline legal-doc-ai-pipeline Public

    Production-style legal document AI pipeline with OCR, retrieval, grounded Q&A, API, and demo UI

    Python

  4. rag-eval-observatory rag-eval-observatory Public

    RAG evaluation harness with retrieval metrics, failure taxonomy, and API-first regression workflows

    Python

  5. lead-support-doc-intake lead-support-doc-intake Public

    Local-first intake automation dashboard for leads, support tickets, and document workflows

    Python

  6. legal-doc-ai-workspace legal-doc-ai-workspace Public

    Local-first legal document workspace with multi-document extraction and grounded Q&A

    Python