💡 Sprint Task: Recommendations + Funding Plan Generation

🎯 Goal

Use the district’s profile and funding data to generate an AI-powered Funding Plan (list of recommended grants and strategies), store it in the database, and display it on the Dashboard — with the ability to refresh or regenerate if needed.

🪜 Task Breakdown

1. AI Integration (via n8n)

• [ ] Pass all relevant district data + funding responses from the database into the n8n agent.
• [ ] Ensure clean JSON structure for prompt context (no RAG).
• [ ] Create an n8n workflow that:
  • Receives incoming request (webhook).
  • Sends data to the AI model with a tailored “grant plan” prompt.
  • Returns the structured response (recommendations + plan summary).

2. Funding Plan Generation

• [ ] Define what the “Funding Plan” includes:
  • [ ] List of top recommended grants.
  • [ ] Suggested next steps or deadlines.
  • [ ] Matching scores or reasoning (optional).
• [ ] Format AI response consistently (object with fields: plan_id, recommendations[], summary, etc.).
• [ ] Handle errors (fallback if AI fails or returns incomplete data).

3. Database Integration

• [ ] Create a funding_plans table in Supabase (or update existing schema).
• [ ] Save generated plans per district:
  • [ ] District ID
  • [ ] Plan content (JSON or text)
  • [ ] Created_at / Updated_at
• [ ] Support multiple versions (so regenerating doesn’t overwrite old plans).

4. Dashboard Display

• [ ] Add “Funding Plan” widget or tab in the Dashboard.
• [ ] Show:
  • [ ] Summary section (“Your current funding plan”).
  • [ ] List of recommended grants (with names, amounts, and sources).
  • [ ] Button: “🔄 Refresh Recommendations.”