Detection Engine
Detection that improves itself over time
Native access to your detection logic means every triage outcome feeds back into the rules that fire.
Trusted by top security teams
Compounding Intelligence
Alert quality improves automatically as your team works
When an alert resolves as a false positive, AI traces it to the source rule and proposes a fix via GitHub pull request. Your team reviews and approves it. The same false positive doesn't come back.
Proactive Coverage
Build detections from threat descriptions, not just known patterns
Detection coverage is limited by how many rules someone had time to write. Describe a threat behavior in natural language and Panther generates a complete Python detection with filters, dynamic severity, and test cases.
Complete Context
Agents read and modify your detection logic because it lives in code
Because detections are structured Python with version control, agents can read exactly why an alert fired and write a specific fix rather than a general recommendation.
Autonomous Action
Detection improvements ship through the same review process as your code
Detection engineers stay in control of what fires and why. The role shifts from writing every rule manually to reviewing AI-proposed improvements: same quality bar, fraction of the effort.
Tealium cut detection creation time from 4–5 hours to 10 minutes. That's the alert quality loop in production.
Explore the Platform
Alert Triage & Automation
Panther doesn't summarize alerts and wait for instructions — it investigates.
Detection Engine
Native access to your detection logic means every triage outcome feeds back into the rules that fire.
AI SOC Agent
An agent that runs on a schedule, responds to natural language queries, and takes action with complete context.
Analytics & Reporting
Built-in dashboards and MITRE ATT&CK mapping, from alert trends to program maturity.
Data Pipeline
All your security data, in one place.
