Apate Deploys Undercover AI Agents to Bait Scammers and Harvest Fraud Intelligence

Australian cybersecurity startup Apate.ai is deploying fleets of autonomous AI agents to engage online and telephone fraudsters, turning the tables on bad actors to gather structural fraud intelligence for enterprise clients. Founded in 2024 based on research at Macquarie University in Sydney, the company builds automated bots that masquerade as vulnerable individuals across multiple communication channels, extracting details about scam infrastructure before human targets can be compromised.

Apate operates thousands of distinct synthetic personas featuring varied ages, regional accents, genders, and native languages. The undercover bots interact directly with cybercriminals by answering voice calls, replying to text messages and emails, opening phishing links, and participating in suspect social media groups. According to company metrics reported by TechCrunch AI (https://techcrunch.com/2026/10/14/apate-sends-ai-agents-undercover-to-get-scammed-so-they-can-gather-fraud-intelligence/), the platform has logged over 2.5 million interactions, effectively wasting more than 17 years of aggregate time for fraudulent operators.

Rather than relying strictly on legacy defenses such as reactive phone number blocking or post-transaction monitoring, Apate extracts identity and technical markers straight from the source. Enterprise subscribers receive operational intelligence—including scammer phone numbers, cryptocurrency wallet addresses, bank accounts, spoofed brand assets, and phishing links—to fortify their defenses. Brad Joffe, co-founder and chief commercial officer, told TechCrunch AI that traditional countermeasures operate after contact occurs, whereas Apate engages scammers directly to secure actionable intelligence before harm is done.

The deployment has already produced measurable results for enterprise clients across telecommunications and financial services. Australian telecommunications provider TPG Telecom has routed nearly 590,000 suspicious calls to Apate’s network of agents. Commonwealth Bank of Australia observed a 76 percent drop in publicly reported scam losses following integration, while another unnamed Australian bank deployed outbound agents to disrupt 22 scam campaigns.

The rise of counter-fraud automation comes as law enforcement agencies report high financial damages from AI-enabled schemes. Federal Bureau of Investigation metrics show the agency received over 22,000 complaints concerning AI-assisted crimes in 2025, totaling roughly $893 million in losses. Investment scams represented the largest category at more than $632 million, as bad actors increasingly utilized automated conversational agents and synthetic deepfakes of public figures and business executives.

The concept originated when founder and chief executive officer Dali Kaafar protracted a 44-minute telephone call with an unknown scammer during a family gathering to entertain his children, prompting him to explore automated countermeasures at Macquarie University. Today, Apate’s technical platform relies on a combination of commercial frontier language models and proprietary models fine-tuned on historical scam communications and university research data. To scale its enterprise portal—which allows organizations to assign targeted extraction missions to agents—the 20-person startup raised an $8.15 million seed round in August from Lobby Capital, OIF Ventures, Investible, Concept Ventures, and Baobab Ventures, bringing total funding to just under $10 million.

Currently competing as a finalist in the Startup Battlefield 200 at TechCrunch Disrupt in San Francisco, Apate plans to use its new capital for international expansion, including opening an office in London and expanding its presence in the United States.