Build AI Project Scheduler

I’m building an AI-driven automation tool that takes the pain out of project scheduling for my AI-focused initiatives. The core of the product is an engine that learns from historical project data, then produces an adaptive schedule that stays realistic as priorities shift.

Here’s what the engine must do:
• Task prioritization – rank upcoming work automatically, updating in near-real time as new items appear.
• Resource allocation – match the right people or assets to each task based on availability and skill.
• Risk assessment – surface schedule threats early and recommend mitigations before they impact delivery.

The initial data feed will come entirely from our own historical project records (spreadsheets, exported Jira tables, time-tracking logs, etc.), so the system needs robust data-cleaning and transformation routines before any model training occurs.

I’d like a working proof-of-concept that includes:
– A lightweight UI (web or desktop) where I can upload datasets and tweak weighting factors.
– The scheduling algorithm packaged as clean, well-documented code (Python, R, or a language you propose).
– An export option to common formats (CSV, XLSX, or JSON) so I can drop the schedule into existing dashboards.

Acceptance criteria:
1. When I load a sample dataset, the tool produces a schedule in under two minutes.
2. Changing a priority or resource constraint immediately updates downstream tasks.
3. Risk flags are shown with clear, data-backed reasoning.

If you’ve built similar ML-powered planners or optimization models, I’d love to see a brief demo or repo link with your bid.