Where Our Data Comes From
RakshaAI is a private platform. Our trust scores and scam reports are based on publicly available threat databases, automated technical analysis, and community-submitted reports — not government databases or law enforcement records.
Important: RakshaAI is a Private Platform
RakshaAI is operated by Ehatech Services Pvt. Ltd., a private Indian company. We are not affiliated with, endorsed by, or representing the Government of India, any state government, RBI, NPCI, TRAI, MeitY, police, or any law enforcement agency. Our reports are informational only and do not carry legal authority. Always verify independently before taking financial or legal action.
1. Automated Technical Signals
For website checks, our system automatically analyses several publicly accessible technical properties of the domain or URL you submit.
2. Public Threat Intelligence Databases
We query well-known, publicly accessible threat intelligence feeds. These are not exclusive or proprietary government feeds — they are the same databases used by security researchers and browsers worldwide.
3. Community-Submitted Reports
Indian users can report suspicious websites, UPI IDs, and phone numbers directly on RakshaAI. These community reports are a core part of our detection — especially for newly created scam accounts that have not yet appeared in major blacklists.
The reported identifier (URL, UPI ID, or phone number), the category of suspected fraud, and optional description text provided by the reporter.
Reports are reviewed before they affect public trust scores. Automated filters catch obvious spam. Reports with multiple independent submissions receive higher weight.
Community reports are user-submitted and can contain errors. A report does not constitute proof of fraud. We include community report counts in our output so you can weigh the evidence yourself.
If a report about your identifier is incorrect, you can request a review via our report correction process.
4. Business Verification Data
Businesses that apply for a RakshaAI Trust Badge go through a document verification process. Verified details are used as a positive signal in trust score calculation.
- ✓GST registration number (verified against public GST database)
- ✓Aadhaar-based identity verification via OTP (KYC, not document storage)
- ✓Supporting business documents uploaded and reviewed by our team
- ✓PAN and MCA data where applicable
5. Official Indian Resources We Reference
We cite and link to official government resources in our guidance. We do not have real-time database access to these systems unless they provide public APIs.
6. AI Pattern Analysis
We apply machine learning models trained on India-specific scam patterns to improve detection of novel threats that have not yet appeared in public blacklists. Our models were trained on:
- ✓Confirmed scam websites, UPI IDs, and phone numbers from public sources and community reports
- ✓Structural patterns common to fake government portals, impersonation sites, and investment fraud pages
- ✓UPI ID patterns associated with fraud (naming conventions, VPA patterns, handle types)
- ✓Phone number patterns reported in Indian cybercrime datasets
Limitation: AI pattern analysis can produce false positives. A high risk score from pattern analysis alone — without community reports or blacklist matches — should be treated as a caution signal, not a definitive verdict.
7. What We Do Not Have Access To
To be transparent about our limitations, here is what we explicitly do not use:
- ✗FIR data, police records, or crime databases (not publicly accessible)
- ✗TRAI subscriber records or telecom operator databases
- ✗NPCI transaction records or UPI payment history
- ✗Bank account or financial transaction data
- ✗Aadhaar or national ID database lookups (beyond voluntary KYC for business verification)
- ✗Court records or judgments
- ✗RBI enforcement or blacklist databases (not publicly queryable)
Questions or Corrections?
If a report about your website, UPI ID, or phone number is incorrect, you can request a review. If you have questions about our methodology, read our detailed explanation.