AI SecuritySecurity Operations
Prophet AI
AI SOC agents that autonomously triage, investigate, and respond to alerts and run threat hunts
Prophet AI Overview
What it does
Prophet AI is an agentic AI security operations center (SOC) platform that autonomously works the alert queues burying SOC teams. Its AI SOC Analyst agent triages each alert, builds a dynamic investigation plan, and executes it by retrieving and correlating context from SIEMs, security data lakes, and connected security tools before assigning severity and recommending remediation. Companion agents extend the platform: AI Threat Hunter runs natural language hunts and AI Detection Advisor evaluates detection quality and coverage gaps.
How it works
The platform connects to existing SIEM, endpoint, cloud, identity, email, and threat intelligence tools with read-only access, ingesting alerts, events, custom detections, and organizational context; a proof of value takes about 30 minutes to set up. Each alert moves through a five-stage agent workflow (plan, investigate, respond, adapt, report), with agents learning from analyst feedback and from playbooks ingested as guidance. Agents show their full reasoning and evidence for every conclusion so analysts can verify decisions, and a Dig Deeper interface answers follow-up questions across investigations. Findings, severity ratings, and remediation steps flow into existing case management and collaboration workflows.
Credentials and traction
SOC 2 Type II, ISO/IEC 27001:2022, and ISO/IEC 42001:2023 certified, operating an integrated management system that unifies information security and AI governance, with independent third-party assessments of GDPR, CCPA, and HIPAA controls completed with no exceptions noted. Named a Rising in Cyber winner in 2026. Customers include Cabinetworks Group, Zip, Clari, and JB Poindexter & Co, with deployments at a Fortune 500 enterprise and a national health provider.
Key Capabilities
mapped to solution categoriesPerforms initial triage of incoming alerts automatically, classifying and prioritizing them to cut tier-1 workload before a human touches the queue.
Identifies and dismisses false-positive alerts with documented rationale, reducing noise reaching human analysts.
Investigates alerts end-to-end from trigger to verdict and closes them out autonomously, so the full volume of raw alerts gets analyzed without resource-constraint concessions.
Lets analysts drive investigations and threat hunts through natural-language questions instead of query languages.
Automatically gathers and attaches context — threat intelligence, asset and identity data — to alerts during triage and investigation.
Generates investigation summaries and incident reports for analysts and leadership from completed investigation activity.
Recommends the next response actions to take based on investigation findings.
Applies ML classification to incoming alerts to filter false positives, group related events, and route high-confidence detections to analysts, reducing L1 analyst workload.
Inserts AI-generated analysis, triage decisions, and enrichment into existing SIEM and SOAR case management workflows rather than requiring analysts to use a separate interface.
Accepts natural language queries over security telemetry and translates them to structured queries, enabling investigation without requiring analyst proficiency in SPL, KQL, or SQL.
Suggests the next investigative or containment steps for an alert or incident, with the supporting reasoning, so analysts can confirm and act rather than deciding from raw telemetry alone.
Compliance
certificationsIntegrations
compatible toolsImplementation & support
Info last updated on July 25, 2026
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