Self-initiated internal product. Odds Desk uses public data only. It is not client work, a tradin...Self-initiated internal product. Odds Desk uses public data only. It is not client work, a tradin...
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Self-initiated internal product. Odds Desk uses public data only. It is not client work, a trading tool, or financial advice.
I built this because a research brief is only as trustworthy as the source snapshot behind it. Catalog freshness, derived summaries, file identity, and editorial status need to stay consistent across every generated artifact.
The workflow synchronizes a public catalog, exports one canonical bundle, generates and validates a summary, regenerates a manifest, checks declared SHA-256 values against disk, and produces a dashboard and Markdown brief from the same saved files.
The workflow fails closed. If a required validation fails, the bundle stops, the evidence is preserved, and no buyer-ready issue is produced.
The gallery shows a July 30, 2026 snapshot with 675 saved markets, 36 unverified research leads, zero verified cards, and four of four declared hashes matching disk. The state remains RESEARCH_PREVIEW.
Best fit: public API ingestion, reproducible research bundles, validation pipelines, provenance checks, fail-closed editorial workflows, and automated briefing systems.
Testing my app! 🧰🚀 Everything is finally coming along.
I’ve been working on this project for a little over two weeks. Initially it was just me working with one AI agent, but I was still manually coding most of it, so I was moving like a turtle 🐢very slow.
Then I decided to implement Codex into my project to automate more of the development and it has been amazing. Now I can focus more on prompting, testing, reviewing the code and making the technical decisions instead of manually coding everything.
I also created my own AGENTS.md bible with all my project rules and instructions to make sure Codex follows them as the final authority when working on my code.
The idea is simple: create one useful and intuitive ecosystem of tools that Shopify merchants can add to their stores to help customers make purchasing decisions faster and with more confidence.
Still testing, building and adding more tools. Let’s see where this goes! 🚀
And if anyone finds the idea interesting. I’m definitely open to collaborations, ideas or partnerships. Feel free to reach out!
AI Property Maintenance Automation
AI-powered property maintenance automation designed to streamline how property management teams handle tenant maintenance requests.
The system takes a maintenance request, analyzes the issue, determines its priority and category, recommends a suitable vendor, and automatically creates a structured work order.
Workflow:
Tenant request → AI analysis → Priority & category → Vendor matching → Work order
Built with: Python, Flask, SQLite, HTML, CSS, JavaScript, and AI-assisted request classification.
This project was built as a portfolio demonstration of AI automation for property management operations.