BeeSafe AI
Product & Competitive Intelligence
Stops scams at the source by deploying AI agents that engage fraudsters and extract intelligence.
Company Overview
Builds AI agents that engage with scammers at scale to map the fraud lifecycle, extract actionable intelligence on mule accounts and attacker infrastructure, and deliver real-time fraud signals to financial institutions, telecoms, crypto platforms, and law enforcement. Pioneered the first AI system for engaging sophisticated trust-based scammers.
Competitive Advantage & Moat
Product Roadmap & Public Announcements
AI agents that are multiplatform, multimodal, and multilingual, capable of sustaining engagement for months. Intel enabling financial services and government agencies to intercept scammers mid-transaction. Targeting financial services, crypto, telecoms, social media companies, and law enforcement.
Signals & Private Analysis
DOD Cyber Competition winners with published research provide strong credibility for government and enterprise sales. The $12B trust-based scam market is growing rapidly with AI-enabled scams (deepfakes, voice cloning, LLM persuasion). Likely raising post-Demo Day with strong defense/fintech interest.
Product Roadmap Priorities
Deploys autonomous conversational AI agents that engage scammers in real-time dialogue to waste their resources, extract intelligence, and map fraudulent operations before any victim is contacted.
An AI chatbot pretends to be a gullible victim, strings scammers along in conversation, and secretly collects all their account details and tactics to shut them down.
It's like hiring a thousand incredibly patient undercover agents who never sleep, never get frustrated, and secretly write down everything the con artist says—then hand the notes to the police before breakfast.
Uses graph neural networks and anomaly detection to identify mule accounts and map interconnected scam infrastructure across financial networks in real time.
The AI connects the dots between suspicious bank accounts, phone numbers, and websites to build a map of the entire scam operation—like a detective's evidence board that builds itself.
It's like Google Maps for crime networks—except every time a scammer talks to the AI, a new pin drops on the map and the routes between accomplices light up automatically.
Applies NLP-based classification models to incoming scam communications to automatically categorize scam type, detect novel scam scripts, and trigger early warnings for emerging fraud campaigns.
The AI reads every scam message it encounters, instantly sorts it by type (romance, crypto, tech support, etc.), and raises an alarm the moment it spots a brand-new kind of scam no one has seen before.
It's like a librarian who not only instantly shelves every book by genre but also notices when someone sneaks in a book from a genre that doesn't exist yet—and immediately tells everyone to watch out.
Company Overview
Key Team Members
- Daniel Spokoyny, Co-Founder
- Ariana Mirian, Co-Founder
- Nikolai Vogler, Co-Founder
Founder Force Multiplier
Three PhD founders who wrote the paper introducing the first AI system for sophisticated trust-based scam engagement. Combined 20+ years in ML, NLP, and security research across CMU, UCSD, Google, Microsoft, and Censys. DOD Cyber Competition winners. No competitor has this combination of published scam-engagement research and production security experience.
Funding History
- 2025 | Spokoyny, Mirian, and Vogler begin research collaboration.
- 2026 | BeeSafe AI founded, accepted into Y Combinator W26 batch.
- 2026 | Intel enabling financial services and government agencies to intercept scammers.
Competitors
- Fraud Detection: Sardine, Unit21, Featurespace.
- Identity Verification: Socure, Persona.
- Scam-Specific: Kitboga (entertainment/awareness), various telecom scam filters.
- Enterprise Security: CrowdStrike, Palo Alto Networks.
