SmartTender

#Week 6 (Sprint 5) — Readiness Scoring Epic

Epic Overview

This sprint focuses on implementing and integrating the Tender Readiness Scoring feature — enabling teams to assess their suitability for specific tenders based on their company profiles and AI summarization data.

The sprint includes backend model design, API development, frontend integration.

---

Sprint Timeline & Assignments

Backend: Define Scoring Model & Database Setup

Assignees: Gift Mbatha & Refiloe Baloyi
Objectives:

• Design PostgreSQL tables for readiness scores, matched criteria, and recommendations.
• Define relationships between CompanyProfile, Tender, and ReadinessScore models.
• Prepare SQLAlchemy models and migrations.

Deliverables:

• readiness/models.py
• DB migration script
• Documentation of scoring model schema in /docs/api-contract.md

---

Backend: Implement Scoring Service & Endpoints

Assignee: Gift Mbatha
Objectives:

• Implement business logic in readiness/service.py:
  • Compare tender requirements with company profile attributes.
  • Calculate a readiness score (0–100).
  • Generate a short recommendation summary.
• Create FastAPI endpoints in readiness/routes.py:
  • POST /api/readiness/check
  • GET /api/readiness/history

Deliverables:

• readiness/service.py
• readiness/routes.py
• Unit tests for readiness logic

---

Frontend: Add “Check Readiness” Button & Modal

Assignee: Monthati Gaosekwe
Objectives:

• Add a “Check Readiness” button on each tender card.
• On click, open a modal that calls the readiness API.
• Display score, matched/unmatched criteria, and recommendation message.

Deliverables:

• frontend/src/components/Tender/ReadinessModal.jsx
• frontend/src/pages/Dashboard.jsx (button integration)

---

Frontend: Build Readiness History Page

Assignee: Monthati Gaosekwe
Objectives:

• Create a page to display historical readiness checks.
• Fetch data from GET /api/readiness/history.
• Sort results by highest match score.

Deliverables:

• frontend/src/pages/ReadinessHistory.jsx
• readinessService.js

---

AI Integration: Natural-Language Explanations (Optional)

Assignee: Lentswe Kunene
Objectives:

• Enhance readiness scoring with natural-language reasoning using an AI model.
• Integrate HuggingFace transformer or local LLM to produce an explanation field in the readiness result.

Deliverables:

• ai_explanations/service.py
• Integrated AI output into readiness API response

---

Testing & Quality Assurance

Team-wide effort
Objectives:

• Run unit and integration tests across backend and frontend.
• Verify scoring accuracy, response formatting, and frontend data rendering.
• Perform manual API tests using Postman.

Deliverables:

• tests/test_readiness_service.py
• tests/test_readiness_routes.py
• QA checklist report in /docs/testing-report.md

---

Sprint Deliverables Summary

Area	Deliverable	Owner
Backend	Scoring model, DB schema, service, endpoints	Gift Mbatha & Refiloe Baloyi
Frontend	Readiness modal & history page	Monthati Gaosekwe
AI	Explanations	Lentswe Kunene
QA	Testing report & validation	Entire Team
Documentation	Document	Nthabeleng Moleko

---

Prepared by: Nthabeleng Moleko Module: Software Engineering & Design
Project: SmartTender SaaS Web Application
Sprint: 5 – Readiness Scoring Epic