7AI Launches Federated SIEM and Workflow Builder
7AI launched Federated SIEM and 7AI Build on July 27, adding federated security-data access and a workflow-building capability to its security operations platform. According to the company's announcement and Help Net Security, Federated SIEM can query, investigate, and act on data where it resides, while 7AI Build lets enterprises and partners define agentic workflows, skills, and security services.
7AI launched 7AI Federated SIEM and 7AI Build on July 27, adding federated data access and workflow customization to its AI security operations platform. According to 7AI's announcement, the products will be demonstrated at Black Hat USA 2026.
Federated SIEM lets security teams query, investigate, and act on data wherever it is stored, including data held within 7AI, according to the company and reporting by Help Net Security. The company describes the approach as separating detection from storage and supporting data access across its own data lake, customer systems, or a combination of the two.
7AI Build enables enterprises and partners to define agentic workflows, skills, and AI-native security services on the platform. In a statement published by Help Net Security, 7AI CEO Lior Div said customers were requesting a federated approach rather than sending all data into a SIEM. He also said 7AI Build is intended to let customers and partners extend the context used by agents for investigation, detection optimization, response, and threat hunting.
Context graph and agent workflows
According to Div's statement, 7AI builds a context graph for each customer environment that connects federated data access, enterprise insights, and customer-defined skills. That is a product claim, rather than an independently verified account of operational performance.
The announcement follows 7AI's June release of Threat Hunt, Threat Intel Hunt, and Skills. Help Net Security reports that those features were presented as tools for directing proactive agent activity, turning threat intelligence into autonomous hunts, and teaching agents environment-specific skills.
7AI also reported that its agents had run more than nine million investigations and returned more than one million analyst hours to customer security teams after one year at enterprise scale. Those figures are company-reported and were not independently substantiated in the available coverage.
What federated access changes
For security engineering teams, federated SIEM designs can reduce the need to centralize every telemetry source before an investigation begins. In comparable architectures, however, useful results depend on durable connectors, consistent identity and asset context, access controls, audit logging, and clear handling of latency or unavailable source systems.
The workflow-builder component also puts emphasis on governance. Organizations evaluating agentic investigation systems commonly need to distinguish read-only investigative actions from containment or remediation actions, then define approval gates and evidence trails for higher-impact operations. The available reporting does not specify 7AI's connector coverage, authorization model, pricing, or the evaluation methods behind its operational claims.
Key Points
- 17AI added federated querying and action capabilities, potentially reducing dependence on centralizing all security telemetry inside a single SIEM.
- 27AI Build exposes agentic workflows and skills to enterprises and partners, making governance and authorization design central implementation concerns.
- 3The company reports nine million investigations and one million analyst hours returned, but available coverage does not independently validate those metrics.
Scoring Rationale
The release is a notable product expansion for teams evaluating agentic SOC platforms and federated security-data architectures. Its practitioner importance depends on unreported implementation details such as source integrations, authorization controls, and operational evaluation results.
Sources
Primary source and supporting public references used for this report.
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