Detect and stop agentic-AI attacks in email & collaboration

Executive Summary

Enterprise security and compliance teams at roughly 2 million Office 365 and Google Workspace customers face a new class of risk: attacker use of generative and agentic AI to automate highly personalized phishing, business email compromise and collaboration-tool abuse. These attacks are faster and more scalable than traditional social engineering, can pivot across email, chat and shared documents, and are difficult to detect with signature-based scanners alone. You could build a cloud-first solution that fuses Graph and Workspace audit telemetry with behavioral models of “agentic” activity, surfacing intent signals (automated follow-ups, credential-extraction attempts, multi-channel escalation) and executing automated containment actions (message quarantine, link neutralization, token revocation) plus one-click IR playbooks. The product would emphasize privacy-preserving on-device inference where possible, simple admin UX for non-specialist SOC teams, and out-of-the-box integrations with CASBs, EDRs and SIEMs to reduce deployment friction and aim for the targeted $3K ACV that underpins the $6.0B market estimate. Timing favors entry: rapid generative AI adoption by employees expands attacker toolsets, while consolidation on a few collaboration platforms and richer APIs makes centralized behavioral detection and closed-loop response feasible at scale. Competition is high and incumbents will move quickly, so realistic differentiation comes from low‑false‑positive agentic intent modeling, operational automation that measurably reduces mean-time-to-remediate, and a go-to-market focused on SMBs and mid-market customers who lack bespoke SOC resources; the technical and trust hurdles (false positives, telemetry access, attacker adaptation) are real but addressable with disciplined product design and channel partnerships.