CISO Tribune

Vendor comparison · 2 companies

Panther vs RunReveal

Panther is an AI SOC platform that ingests and normalizes logs at petabyte scale, lets teams write detection rules in Python, and automatically creates detections using AI and natural language. RunReveal sells a unified platform that handles the security lifecycle from data ingestion through investigation and remediation. CISO Tribune files both under AI SOC analysts, SIEM and Security data lakes and pipelines. This page sets the two records side by side: what each sells, where it is based, who owns and funds it, the customers it names and its recent news, each fact numbered to its source.

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  • Panther
  • RunReveal
Panther vs RunReveal: Products, Customers and Funding Compared
PantherPanther is an AI SOC platform that ingests and normalizes logs at petabyte scale, lets teams write detection rules in Python, and automatically creates detections using AI and natural language.panther.comRunRevealRunReveal sells a unified platform that handles the security lifecycle from data ingestion through investigation and remediation.runreveal.com
What it sells
  • AI SOC Agent[6]Runs on a schedule, responds to natural language queries, and takes action with complete context.
  • AI Detection Builder[5]Creates detections using AI and natural language.
  • Security Data Lake[1][7]RunReveal integrates natively with 80+ sources and supports Bring-Your-Own-Source functionality to unify logs in one searchable security data lake.
  • Detections[1][4][6][11]RunReveal includes pre-built SQL detections for common threats across AWS, Azure, GCP, GitHub, Okta, and 80+ integrations.
  • Pipelines[1][10]RunReveal's data pipelines let users filter, route, transform, and enrich security logs before they hit storage.
Categories
Headquarters
Not stated on its pagesNot stated on its pages
Founded
Not stated on its pages2024[3]
Ownership and funding
Not stated on its pagesNot stated on its pages
Named customers
Not stated on its pagesNot stated on its pages
Recent news
  • June 16, 2026Databricks reached a deal to buy Panther Labs, the company behind Panther, as part of a push into cybersecurity.[7]
  • June 16, 2026Databricks acquired Panther, a startup that works on cyberattack detection.[8]
Not stated on its pages
G2 and Gartner Peer Insights
  • G2: Not stated on its pages
  • Gartner Peer Insights: Not stated on its pages
  • G2: Not stated on its pages
  • Gartner Peer Insights: Not stated on its pages
Who it fits
Teams with detection engineers can use Detection-as-Code with Python rules, version control, and CI/CD workflows. Teams without detection engineers can start with the built-in detection library and AI Detection Builder. Panther can run inside the customer's own AWS account, or Panther can operate a managed cloud with the customer's data ingested into a dedicated, isolated environment.From its own pages, RunReveal sells mainly to security teams that want data management, detection, and response in a single platform. Its use cases include cloud security monitoring for misconfigurations, unauthorized access, and policy violations. Identity and access use cases cover detection of credential abuse, impossible travel, privilege escalation, and unauthorized access. RunReveal states that bring-your-own-cloud lets customers deploy in their own VPC for control over data residency, security, and compliance. RunReveal states that bring-your-own-database runs the platform on a database the customer's team controls.
Last verified
September 27, 2026October 30, 2026

Where they overlap

  • Panther and RunReveal are both filed under AI SOC analysts, SIEM and Security data lakes and pipelines.

Where they differ, field by field

  • Panther's primary category is AI SOC analysts; RunReveal's is SIEM.
  • Panther lists AI SOC Agent and AI Detection Builder. RunReveal lists Security Data Lake, Detections and Pipelines.
  • RunReveal was founded in 2024.

What it sells: Panther

What AI SOC Agent does[6]
Panther's AI SOC Agent runs on a schedule, responds to natural language queries, and takes action with complete context. Each investigation pulls from the data lake, detection logic, and connected tools via MCP. Panther runs scheduled threat hunts across the full data lake on a cadence the customer configures. Panther generates new detection rules from natural language, identifies recurring false positives, and submits tuning changes as reviewable Python code through the existing GitHub workflow.

What it sells: RunReveal

What Security Data Lake does[1][7]
RunReveal integrates natively with 80+ sources and supports Bring-Your-Own-Source functionality to unify logs in one searchable security data lake. RunReveal can be deployed in its SaaS cloud, in a customer cloud account, on a customer database, or completely on-premise.
What Detections does[1][4][6][11]
RunReveal includes pre-built SQL detections for common threats across AWS, Azure, GCP, GitHub, Okta, and 80+ integrations. Existing rules can be modified, or custom detections written, using standard SQL or Sigma format. RunReveal lets users preview detections against historical logs, validate logic with real events, and iterate on rules. RunReveal can deploy Sigma rules that evaluate events during ingestion rather than on a schedule.
What Pipelines does[1][10]
RunReveal's data pipelines let users filter, route, transform, and enrich security logs before they hit storage. RunReveal provides a visual pipeline builder for filtering, routing, and basic transformations. For advanced uses such as complex data reshaping or custom enrichment logic, transformations can be written in SQL or built-in functions can be used. RunReveal provides real-time pipeline metrics showing volume processed, filtering rates, routing destinations, processing latency, and error rates.

Questions about Panther and RunReveal

What do Panther and RunReveal sell?
Panther sells AI SOC Agent and AI Detection Builder. RunReveal sells Security Data Lake, Detections and Pipelines.
Are Panther and RunReveal in the same category?
They share AI SOC analysts, SIEM and Security data lakes and pipelines. Panther's primary category is AI SOC analysts and RunReveal's is SIEM.
When were Panther and RunReveal founded?
RunReveal was founded in 2024.
Who are Panther and RunReveal sold to?
Teams with detection engineers can use Detection-as-Code with Python rules, version control, and CI/CD workflows. From its own pages, RunReveal sells mainly to security teams that want data management, detection, and response in a single platform.
What have Panther and RunReveal announced recently?
June 16, 2026: Databricks reached a deal to buy Panther Labs, the company behind Panther, as part of a push into cybersecurity.

About Panther

Panther is an AI SOC platform that ingests and normalizes logs at petabyte scale, lets teams write detection rules in Python, and automatically creates detections using AI and natural language. Panther is a cloud-native SIEM featuring detections-as-code and advanced search, with natively supported log sources and alert destinations. Panther ingests terabytes of security events per day into a structured data lake to power real-time detections and investigations. Panther uses a security data lake architecture that provides long-term retention. Customers own their data and can query it at any time, and retention policies in Panther are configurable to meet compliance requirements.[2][3]

Panther says that cloud security logs, EDR portals, and MDR consoles each exist in silos with no central view. Panther states that analysts manually piece context together, often missing critical details. Panther describes an agentic SOC in which agents hunt the full data lake on a regular cadence, surfacing findings that flow into new detections through a governed workflow. In Panther, every alert is investigated with full context, and confirmed benign alerts close automatically. When a finding escalates in Panther, the agent assembles the full investigation across multiple systems, and analysts review and guide agentic runbooks to take action.[6]

Panther's AI SOC Agent runs on a schedule, responds to natural language queries, and takes action with complete context. Every investigation by the AI SOC Agent pulls from the customer's data lake, detection logic, and connected tools via MCP. When an alert fires, Panther automatically gathers evidence across the data lake, detection logic, alert history, and connected tools. Panther AI queries the data lake, reviews detection logic, and pulls enrichment from connected tools, delivering a risk classification with reasoning. Any analyst can investigate through a natural language interface in Panther without writing SQL, PantherFlow, or any other query syntax. Panther exposes its own MCP server, so external agents can query alerts, detections, and log data directly. When the risk classification of the AI SOC Agent falls below a threshold the customer configures, the alert closes automatically.[6]

Panther generates new detection rules from natural language, identifies recurring false positives, and submits tuning changes as reviewable Python code through the customer's existing GitHub workflow. The Panther agent traces an issue back to the specific Python rule responsible and proposes an edit as reviewable code through the existing GitHub workflow, with a diff, explanation, and unit tests. In Panther, nothing deploys without human review. Teams with detection engineers use Detection-as-Code in Panther, with Python rules, version control, and CI/CD workflows. Teams without detection engineers can start with Panther's built-in detection library and AI Detection Builder, then grow into custom rules over time.[6]

Panther connects to cloud platforms (AWS, GCP, Azure), SaaS tools, endpoints, and network devices. Panther routes alerts to Slack, Jira, PagerDuty, and more. For orchestration and response, Panther provides agentic workflows and runbooks or integrates with external SOAR platforms. Panther offers Okta log monitoring for complete visibility into IdP activity. Panther detections can be enriched with real-time IoCs from Google Threat Intelligence. Panther AI can send messages and search a Slack workspace directly, manage incidents and on-call schedules directly, and search and update a Notion workspace directly. Panther-managed rules for Orca Security are in the panther-analysis GitHub repository. Panther includes built-in dashboards and MITRE ATT&CK mapping, from alert trends to program maturity. In Panther, native access to detection logic means every triage outcome feeds back into the rules that fire.[6][9][10]

Panther offers two deployment models on one platform, and the choice is where the customer's data lives. In the first model, Panther runs inside the customer's AWS account, against Snowflake or Databricks, and the security data stays in the customer's warehouse. The detection engine, workflows, and agents in Panther operate against that data in place. In the managed model, Panther manages the service and ingests customer data into a dedicated, isolated environment.

Databricks has acquired Panther to accelerate the security lakehouse vision. Panther's AI SOC workflows, 100+ integrations, and detection-as-code capabilities are being integrated into Databricks Lakewatch. Panther requires human approval for every write, and every AI action is logged and reviewable.[1][6][9]

Panther on the record

Sources

Panther full record

  1. [1]ProductPanther · panther.com · undated page, accessed September 27, 2026 · Tier A
  2. [2]panther.comPanther · panther.com · undated page, accessed September 27, 2026 · Tier A
  3. [3]Overview | Panther DocsPanther · undated page, accessed October 27, 2026 · Tier A
  4. [4]Security Integrations for Modern SOC Operations | PantherPanther · undated page, accessed October 27, 2026 · Tier A
  5. [5]Panther | The Complete AI SOC PlatformPanther · undated page, accessed October 27, 2026 · Tier A
  6. [6]AI SOC Agent for Alert Triage & Investigation | PantherPanther · undated page, accessed October 27, 2026 · Tier A
  7. [7]Databricks strikes deal to buy Panther Labs in cybersecurity pushReuters · published June 16, 2026 · Tier B
  8. [8]Databricks acquires cyberattack detection startup PantherSiliconANGLE · published June 16, 2026 · Tier B
  9. [9]Security Integrations for Modern SOC Operations | PantherPanther · undated page, accessed November 10, 2026 · Tier A
  10. [10]Orca Security Logs | Panther DocsPanther · undated page, accessed November 10, 2026 · Tier A

RunReveal full record

  1. [1]runreveal.comRunReveal · runreveal.com · undated page, accessed October 30, 2026 · Tier A
  2. [2]runreveal.comRunReveal · runreveal.com · undated page, accessed October 30, 2026 · Tier A
  3. [3]AboutRunReveal · runreveal.com · undated page, accessed October 30, 2026 · Tier A
  4. [4]RunReveal | Fast, Scalable Security Log ManagementRunReveal · undated page, accessed November 10, 2026 · Tier A
  5. [5]RunReveal Platform | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  6. [6]Modern SIEM Alternative | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  7. [7]Modern Security Data Lake | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  8. [8]Security Data Readiness | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  9. [9]Security Data Readiness | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  10. [10]Security Data Pipelines | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  11. [11]Detections | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  12. [12]AI-Powered Security Analysis | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  13. [13]AI SOC Platform | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A
  14. [14]Security Dashboards & Analytics with AI | RunRevealRunReveal · undated page, accessed November 10, 2026 · Tier A

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