The startup offers a brand authenticity platform that utilizes artificial intelligence to analyze large data sets for identifying counterfeit products and fake content. This technology enables businesses to effectively monitor digital channels and safeguard their brand identity from the risks associated with counterfeiting.
Funding
$3.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Online platforms and marketplaces face challenges in identifying and mitigating fraudulent activities such as fake accounts, counterfeit goods, and scams, which erode user trust and revenue. Traditional methods often struggle to keep pace with the evolving tactics of bad actors who exploit loopholes for financial gain. This results in financial losses, reputational damage, and regulatory scrutiny.
Solution
Pasabi offers an AI-driven fraud prevention platform that provides continual threat intelligence to detect and classify multiple fraud threats at scale. The platform leverages behavioral analytics, reputational data, and network analysis to identify patterns of suspicious behavior indicative of fraud rings and prolific offenders. By connecting behavior and intent, Pasabi enables platforms to understand the scale of the challenge, enforce policies with confidence, and automate actions to safeguard users and revenue. Pasabi's technology adapts to evolving tactics used by fraudsters, ensuring that platforms can maintain a trusted and authentic user experience.
Target Audience
Pasabi serves online marketplaces, review platforms, banking and insurance companies, and online communities seeking to combat fraud and ensure a safe user experience.
Features
- AI-powered engine that analyzes reputational, network, and behavioral signals to detect fraudulent activity
- Cross-platform intelligence leveraging a repository of known bad actors
- Cluster analysis to identify fraud rings and connected accounts
- Risk scoring and labeling for efficient decision-making
- Continual monitoring to identify emerging threats in real-time
- Automation capabilities to maximize resource efficiency
- Integration methods to feed decisions into existing moderation and enforcement workflows
- Comprehensive dashboard with cluster views, reporting, audit trails, and data exports