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Maxime Moisan
I build AI agents, data pipelines, and automations.
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Document Q&A system that turns PDFs into searchable knowledge bases. Upload a report, ask a question in plain English, get an answer with numbered source citations and relevance scores. The retrieval layer chunks documents into overlapping passages (600 chars with 100-char overlap to avoid splitting context at boundaries), builds a TF-IDF vector index, and ranks results by cosine similarity. The answer is extracted from the highest-scoring passage with cross-reference to the original text. Built the conversational web UI with a chat-style interface. Python + FastAPI backend, scikit-learn for vectorization, PyPDF for text extraction.
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Endpoint health monitoring system that runs concurrent checks against 10 services (HTTP APIs, webhooks, database connections) using asyncio. Each check measures response time at p50/p95/p99 percentiles, tracks uptime over 24h windows, and triggers alerts when thresholds are crossed. Failed checks retry with exponential backoff (1s, 2s, 4s) before marking an endpoint degraded. Supports HTTP, TCP, and DNS protocols. The dashboard shows a real-time status board with per-endpoint heatmaps, incident timeline, and aggregate uptime. Built with Python + FastAPI + asyncio/aiohttp. Designed to run as a lightweight self-hosted alternative to commercial monitoring tools.
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Nightly price intelligence pipeline that scrapes 15 consumer electronics products across 13 retailers (Amazon, Best Buy, Walmart, B&H Photo, Adorama, Newegg, etc). Each store gets its own isolated scraper actor so a DOM change on one site doesn't take down the whole batch. Prices are normalized at scrape time (unit vs bulk), tracked over 30-day windows, and surfaced in a dark-theme dashboard with per-product trend lines and savings alerts. Exports to CSV for downstream analysis. Python + FastAPI backend, BeautifulSoup with fallback selectors, Chart.js frontend. Scheduled via cron at 03:00 UTC with retry and exponential backoff on failures.
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