BeeSafe AI offers an active fraud‑prevention platform that uses AI‑driven agents to engage scammers across messaging, email, and social channels, identifying and tagging mule accounts before payments are authorized. The system provides real‑time cross‑channel monitoring and integration APIs for banks, payment processors, digital wallets, and online marketplaces to block fraudulent transactions at the source while continuously learning from scam interactions.
Funding
Funding not disclosed
Founders
Product
Problem
Trust-based scams such as pig‑butchering, impersonation, and romance fraud convince victims to voluntarily authorize payments, allowing fraudsters to bypass traditional rule‑based detection systems. Because these scams develop across multiple communication channels, individual platforms often lack visibility into the full fraud chain, leading to delayed investigations and costly reimbursements.
Solution
BeeSafe AI provides an active fraud‑prevention platform that intervenes early in the scam lifecycle by deploying AI‑driven anti‑scam agents to engage directly with fraudulent actors. The agents monitor inbound messages, identify mule accounts, and initiate real‑time conversations that waste scammers’ time and disrupt their operations before a payment is authorized. Detected fraudulent accounts are flagged and shared across integrated channels, enabling platforms to block transactions at the source. The system continuously learns from interactions to improve detection of emerging trust‑building tactics and to reduce false positives for legitimate users.
Target Audience
Primary customers are banks, payment processors, digital wallets, and online marketplaces that need to prevent authorized‑payment fraud and protect their users from trust‑based scams.
Features
- AI‑powered agents that automatically engage scammers in messaging apps, emails, and social platforms to disrupt fraud attempts
- Real‑time identification and tagging of mule accounts used for laundering illicit funds
- Cross‑channel monitoring that links interactions from the first direct message through to wire transfers
- Automated response scripts that simulate victim behavior to waste scammers’ resources while gathering intelligence
- Continuous machine‑learning models that adapt to new scam narratives such as deep‑fake voice or AI‑generated content
- Integration APIs for payment processors and financial platforms to block flagged accounts instantly