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Varshini Mallikarjuna Prasanna edited this page Jan 16, 2026 · 6 revisions

Functional Specification

Universal Search Functionality – Dashboard

Document Version

  • Version: 1.0
  • Author: Varshini
  • Stakeholders: Product, Engineering (Backend, Frontend, Data/Geospatial), QA, UX
  • Status: Proposal / Initial Specification

1. Purpose

The purpose of this document is to define the functional requirements for a universal search capability within the application dashboard. The search feature will enable logged-in users to enter a single free-text query and quickly find or navigate to relevant entities across the application.

The initial implementation will focus on a simple, fast, and cost-effective keyword-based search aligned with the 1.0 MVP scope, while being architected to support future enhancements such as intent-aware and intelligent search.

2. Scope

In Scope (Phase 1 / MVP)

  • Universal search bar available on the application dashboard
  • Single free-text input without requiring users to select entity types
  • Keyword-based interpretation of user input
  • Search across multiple internal entity types
  • Ranked search results based on relevance
  • Role-based access control applied to search results
  • Direct navigation to relevant detail or context pages
  • Automatic navigation when only one confident match is found

Out of Scope (Phase 1)

  • Advanced autocomplete or predictive suggestions
  • Natural language question answering
  • Semantic or vector-based search
  • Personalized or recommendation-based ranking
  • External data or internet search
  • Voice-based search

3. User Roles

The system supports the following user roles:

  • Beneficiary
  • Volunteer
  • Organization
  • Donor
  • Admin
  • Super Admin

Search results and accessible entities must be filtered based on the user’s role and permissions. Users must only see entities they are authorized to access.

4. User Experience Overview

4.1 Entry Point

  • A single search input field displayed prominently in the dashboard header
  • The search field is visible only to authenticated users

4.2 User Input Characteristics

The search field must accept:

  • Numeric input (e.g., IDs)
  • Text input (partial or full)
  • Mixed alphanumeric input

Example inputs:

  • 0005
  • Varshini
  • dry cleaning
  • social connection

5. Searchable Entities

The search functionality must support the following internal entity types in Phase 1:

Entity Type Examples
Help Requests Request ID, title, description, category
Users User ID, name, username
Organizations Organization name
Categories / Tags Help categories, labels
Companies Company names (if applicable)

If only one confident match exists, the system should navigate directly to the relevant page without showing intermediate results.

6. Search Behavior & Ranking

  • Results must be ranked based on keyword relevance
  • Title and identifier matches should be weighted higher than description matches
  • Results across different entity types should be presented in a unified ranked list
  • Result count should be limited to ensure fast response times

7. Navigation & Context

  • Each search result must support direct navigation to the relevant detail page
  • Where possible, navigation should include contextual hints (e.g., anchors or highlights)
  • The search experience should resemble familiar “search and jump” patterns seen in common applications

8. Access Control & Security

  • All search results must respect role-based permissions
  • Users must not see:
    • Entities they are not authorized to access
    • Data belonging to restricted roles or organizations
  • Super Admins may search across all entities

9. Backend & Technical Considerations

9.1 Architecture (Phase 1)

  • Search service implemented in Python (Flask)
  • Centralized search API endpoint
  • Keyword-based query processing
  • Retrieval from internal data sources only
  • Database-native search capabilities preferred for performance and cost efficiency

9.2 Future Enhancements (Out of Scope for Phase 1)

  • Intent-aware or Gen-AI–assisted search
  • Retrieval-Augmented Generation (RAG)
  • Vector-based semantic search
  • Learning from historical search behavior
  • Autocomplete and intelligent suggestions

10. Performance Requirements

  • Search results must be returned within ≤ 500 ms for standard queries
  • The system must efficiently support partial keyword matches

11. Error Handling

  • If no results are found:
    • Display a clear “No results found” message
  • If input is invalid or too short:
    • Provide guidance or example searches

12. Success Criteria

The search feature will be considered successful if:

  • Users can locate entities without knowing exact IDs
  • Navigation to target pages requires a single search action
  • Search behavior feels intuitive and familiar
  • The system scales as data volume grows

13. Deliverables

  • Functional specification (this document)
  • High-level architecture diagram
  • Backend API contract definitions
  • UX wireframes

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