# Reverse Africa
> Community-driven reverse phone lookup and spam reporting database for Africa.

## About

Reverse Africa is a free reverse phone lookup service for African phone numbers. The database contains over 2 million community-submitted reports with real-time spam intelligence and AI-assisted caller identification.

## Key Data

- Coverage: African mobile and landline phone numbers
- Spam Reports: Community-submitted complaints with AI-assisted classification
- Number Types: Landline, Mobile, VoIP, Toll-Free
- Classification: Numbers are scored 0-100% spam based on report volume and recency
- Caller Identification: AI extracts caller company/person names from user reports

## How to Use This Site

### Phone Number Lookup
To look up a phone number, use the URL pattern:
- `https://www.reverseafrica.com/lookup/{phone_number}/`
- Example: `https://www.reverseafrica.com/lookup/0361649173/`
- Phone numbers should be in local format (leading 0) or international format (digits only, no +)

### Search Endpoint
- `https://www.reverseafrica.com/q?q={phone_number}`
- Accepts digits and + only, redirects to the lookup page

### What Each Lookup Page Contains
- **Verdict**: A summary at the top of the page with phone type, location, caller ID, and spam score
- **Caller Identity**: If available, the likely caller (company or person) based on AI analysis of user reports
- **Spam Score**: 0-100% rating based on complaint volume and recency
- **Phone Type**: Landline, Mobile, etc.
- **Location**: Numbering area
- **User Comments**: Community-submitted reports about the number
- **AI Classification**: Each comment is classified by subcategory (scam, telemarketer, debt collector, robocall, etc.)

### Scam Detection
When a number is identified as likely being a scam, the lookup page indicates that callers may be pretending to be a specific company. This is based on AI analysis of multiple user reports.

## API Access
For programmatic access, see the developer documentation at:
- `https://www.reverseafrica.com/developer/`

## Important Notes
- Data is community-contributed and should be treated as indicative, not definitive
- Spam scores are calculated from user reports and may not reflect the current status of a number
- Caller identification is AI-assisted and should be verified independently