The threat model at Kore.ai starts with scale: over a billion automated interactions annually across more than 400 Global 2000 companies. That volume means every vulnerability in their Agentic AI platform - from prompt injection to data exfiltration through agent chains - gets multiplied. The company, founded in 2014 and headquartered in Orlando, Florida, builds AI agents for customer service, employee productivity, and process automation across banking, healthcare, retail, and HR.
Security here isn't a perimeter play; it's an architecture problem. The Kore.ai Agent Platform lets enterprises build, deploy, manage, and monitor AI agents at scale, which means the attack surface includes agent-to-agent communication, tool-calling permissions, and the integrity of pre-built applications shipping into regulated industries. The platform ships with solutions tagged as AI for Service, AI for Work, and AI for Process, plus a marketplace of agent templates - each a potential vector if not hardened.
The engineering footprint spans Orlando, Hyderabad, London, Tokyo, Seoul, and Dubai. That geographic distribution complicates compliance: banking and healthcare customers in different jurisdictions mean data residency, access control, and audit logging aren't abstract concerns - they're contractual obligations. Pre-built vertical applications for banking and healthcare amplify this, because those deployments touch PII and PHI by default.
For security practitioners, the interesting problem is defending an AI-native platform where the agents themselves are the infrastructure. Hardening LLM-powered workflows against adversarial manipulation, securing the supply chain of marketplace templates, and maintaining observability across a billion-agent interaction volume - that's the concrete challenge set.
