Panther’s SIEM iteration into the AI security space has been a real shift in our security team’s capabilities. With AI Auto Triage, the triage process is quick, and the Panther AI integration enables automated threat hunting. Having threat intel pushed into the MCPs has also been helpful. The price-to-capability balance feels fair, and it’s the only SIEM I’ve seen so far that has pushed this heavily into SIEM + AI integration. The standard plug-and-play integrations are limited to a typical security tech stack; however, it isn’t difficult to ship logs to S3 and normalize them directly in Panther. Using a Snowflake datalake, queries are efficient and it’s one of the more seamless ways I’ve used to query log sources at scale. We also have monthly visits with the Panther team to help integrate and upgrade our instances, uncover new release items, and help us engineer the platform for success. Lastly, the UI/UX is easy to navigate. Most SIEMs are difficult to work with, with buttons doing various things across different areas. This is a SIEM through and through: if you know what you want to find or what detection you want to build, you can do it easily since the backend query structure is SQL and the detections are all detection as code.

What I like best about Panther is how quickly it helps us move from alert to action. It’s powerful and highly automated, with strong native integrations that made setup and onboarding easy across teams. Features like enrichment and AI-assisted analysis make SOC investigations much faster and simpler, and the support team is consistently responsive whenever we need help.

Panther is a compact, powerful SIEM with AI Analytics that are currently evolving by the day. Each category is easy to browse and use, there are several integrations that can be requested, the price is very competitive with other tools on the market, and the custom rule builder is very well designed.