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Trust in a cybersecurity platform should come from clear evidence, not marketing language alone. This center brings together RakshaAI’s current approach to security, privacy, data handling, AI-assisted decisions, corrections and product limitations, while clearly identifying work that is still planned.
Learn about the security principles behind RakshaAI and the precautions users should continue to take. A risk result supports a decision, but it should never be treated as permission to ignore normal account, payment or identity safeguards.
OpenReview how RakshaAI addresses personal information and data submitted through its services. The privacy policy explains applicable purposes, rights and practices instead of relying on a broad “zero data collection” promise.
OpenUnderstand the types of public sources, user-submitted reports and technical signals that may contribute to an assessment. This also explains what RakshaAI does not have access to and why every result has limits.
OpenSee how available signals can contribute to Trust Scores, supporting explanations and recommended actions. The methodology separates observed evidence from interpretation and avoids presenting automated output as certainty.
OpenReview known limitations, including new threats, incomplete evidence and the possibility of false positives or false negatives. Important financial, legal, employment and identity decisions still require independent verification.
OpenIf a public report or risk classification appears inaccurate, the correction channel allows the affected person or organization to request review and provide relevant context or supporting evidence.
OpenSecurity researchers and users can privately report a suspected vulnerability to the RakshaAI team. Please avoid exposing sensitive technical details publicly before the issue can be assessed.
OpenA public dashboard for uptime, active incidents and historical service interruptions is planned. Until it is available, this card clearly marks the capability as planned rather than suggesting that monitoring information is already public.
Authentication, authorization, rate limits, data handling and enterprise controls will be documented before any broader API release. Early-access discussions do not imply unrestricted or production-ready access.
OpenRelevant security, privacy and assurance requirements will be assessed as enterprise services and data flows mature. RakshaAI will describe completed work separately from planned controls or certifications.
No automated system can detect every scam. RakshaAI provides risk intelligence based on available signals and should be used as a decision-support tool, not as a guarantee that a website, document, person or transaction is legitimate.
RakshaAI aims to minimize the personal information required to provide its services and to explain how submitted data is processed. RakshaAI does not sell personal information. Specific processing and retention terms are governed by the published privacy policy.
Read the privacy policy