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ConstructionSaaS · Web application · AI/ML

AI project scheduling app rescue

We rescued an AI-assisted project scheduling product 48 hours before a customer demo: rebuilt an undocumented codebase locally, fixed six core Gantt features, persisted user settings, and kept the AI chat working through a model-provider outage.

Illustration of AI project scheduling app rescue

Problem

The client had inherited a codebase with no documentation, a manual build process and broken core features, and had a customer demo within days.

Solution

The team rebuilt the development setup without documentation, then fixed saving in the review screen, task dependencies, percentage-complete shading in bars, start-date propagation, and column width and show/hide on the grid, persisting hidden columns and workweek, holiday and working-hour settings with the file. When the chat feature failed during a model-provider capacity incident, the integration was switched to another provider through LangChain for the demo. Changes were reviewed live with the client and pushed incrementally.

Key features

  • Local build of an undocumented Angular front end and Python back end
  • Save in the review screen
  • Task dependencies in review and generate screens
  • Percentage-complete shading in Gantt bars
  • User start date propagated to the generated chart
  • Adjustable column widths and dynamic show/hide columns
  • Hidden columns and schedule settings persisted with the saved file
  • AI chat stabilised by switching model provider during an outage

Tech stack

  • Angular
  • Anthropic
  • Claude Sonnet
  • GitHub
  • LangChain
  • OpenAI
  • Python
  • Syncfusion
  • TypeScript
  • langchain_openai

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