The problems this team brings to us.
How it works for your team, day to day.
AI events in the tools you already run
Every policy decision — allow, redact, flag, block — streams to your SIEM as a structured event with user, tool, classifier, and policy attribution. Splunk, Chronicle, and Sentinel ingest natively; XSOAR and Tines pick events up for automated playbooks. Your existing detection content gets an AI signal without a new console to watch.
Detections built for AI-native attacks
Prompt injection — direct and indirect — data-exfiltration patterns, jailbreak attempts, and anomalous agent behavior are first-class detections, not regex bolted onto a web proxy. Sessions carry risk scores that rise as signals accumulate, so triage starts with the sessions that matter.
Response that reaches the session
One click quarantines a compromised session, locks the user's AI access, and preserves the full interaction history for forensic replay. Because enforcement is inline, response isn't advisory — the next prompt in a quarantined session simply doesn't go through.
The questions this team asks first.
What formats do events ship in?
Structured JSON with user, tool, classifier, policy, and verdict fields, delivered via native SIEM forwarders or webhook. Field mapping guides ship for Splunk, Chronicle, and Sentinel.
Will this flood us with alerts?
Enforcement handles the routine cases silently — redactions don't page anyone. What reaches the SOC is the risk-scored minority: injection attempts, exfil patterns, and quarantine events, all tunable per policy.
Does this replace our SIEM or DLP?
No. It gives them the AI-layer signal they structurally can't see. Existing DLP keeps covering email and endpoints; AccuroAI covers prompts, tool calls, and agent actions, and feeds everything back into your stack.
Can we run detections on historical data?
Yes — interaction logs are retained on your schedule and queryable, so new detection logic can be evaluated against past sessions during an investigation.