The complete AI SOC platform

With native access to your data, detections, and organizational knowledge — every decision makes your SOC smarter.

Trusted by top security teams

Decisions don’t disappear. They compound.

Panther connects your data lake, detection logic, and AI layer into a single closed-loop architecture, so when your team confirms an investigation outcome, that judgment feeds directly back into the detection that fired it. Every triage makes the next one better. The SOC gets smarter. The noise gets smaller.

Single prompt to full investigation

Panther AI doesn't summarize alerts and wait for instructions. It investigates, pivoting across your data lake, reviewing alert history, and pulling live context from your identity provider, code repos, and ticketing systems. Every investigation delivers a definitive risk classification with transparent reasoning, not a probability score.

Autonomous investigation. Complete context.

Definitive risk classification. Not a probability score.

Proactive coverage that expands beyond what you've written rules for.

Senior detection engineer in every seat.

Detections are only as good as the logic behind them. Panther is built on Python, not a proprietary query language or a black box, meaning every detection rule is readable, testable, version-controlled, and modifiable by AI. This is what makes the closed loop possible.

Describe a threat. Get a production-ready detection.

Detection-as-code. With the workflow your team already uses.

Every false positive makes your detections smarter.

All your security data. In one place. Yours to keep.

Your data lives in your own Snowflake or Databricks instance — no vendor lock-in, no ingestion budgets forcing you to leave logs behind, no retention policies limiting what Panther AI can pivot across during an investigation. The foundation of the closed loop is complete data.

Ingest from anything. Normalized on the fly.

No proprietary query language, no vendor lock-in.

Full visibility into your security program.

Every alert makes the next one easier.

Panther's closed-loop architecture captures every triage outcome, every investigation, every detection improvement and feeds it back into the system. Alert volume drops, and institutional knowledge stops living in senior analysts' heads and starts living in the platform.

Built together. Not bolted on.

Panther was built cloud-native in 2018 on Python, SQL, and structured data lakes — not because it was trendy, but because it was right. Those same choices turned out to be exactly what large language models need to be effective.

Built for the full security lifecycle.

Complete context

Native access to everything an agent needs. Your data lake, detection code, alert history, enrichments, runbooks, and external tools via MCP; all in a single workflow.

Compounding intelligence

Every alert makes the system smarter. Panther learns from your team's decisions and encodes that knowledge into the platform.

Proactive coverage

Your team can now hunt like experts. Build detections in natural language and hunt across your data lake, without detection engineering bottlenecks.

Autonomous action

From prompt to investigation, and beyond. Clear risk classification, benign alert closure, detection improvements—all with audit trails.

What happens when teams run on Panther.

85% Reduction in false positives

90% Reduction in investigation time

70% Reduction in alert volume

80% Auto resolved alerts

Bolt-on AI closes alerts. Panther closes the loop.

See how Panther compounds intelligence across the SOC.

Detect, investigate, and respond to threats at cloud scale — powered by code and AI.