ARLINGTON, Va., March 19, 2026 /PRNewswire/ — Bricklayer AI today unveiled new platform capabilities for deploying and governing coordinated AI agents in security operations at enterprise scale.
As organizations increasingly experiment with AI assistants, automation tools, and do-it-yourself agent frameworks, many security leaders are encountering a new operational challenge: fragmented AI agents operating without shared investigative context, consistent reasoning, or centralized governance.
Bricklayer addresses this challenge through three integrated pillars: Context, Coordination, and Control, enabling security teams to move beyond isolated AI automation toward a coordinated AI workforce for the Security Operations Center. The Bricklayer platform now provides:
- Context – Multi-Agent Context Engineering (MACE) – a system architecture that governs how investigative context is created, accumulated, and shared across AI agents. Instead of context living inside prompts, Bricklayer treats investigative knowledge as a structured system asset so agents inherit evidence, reasoning, and investigative meaning.
- Coordination – Workbench Collaboration Environment – a dedicated operating environment where human analysts and teams of specialized AI agents collaborate around investigations. The Bricklayer Workbench provides visibility into agent plans, evidence, and reasoning while enabling analysts to guide procedures and interact directly with agents.
- Control – Enterprise Governance – a governance layer ensuring AI agents operate within defined boundaries through multi-organization management, environment segmentation, encryption, and comprehensive audit logging. This enables enterprises to deploy coordinated AI agents while maintaining operational oversight and compliance.
Together, these pillars enable a coordinated AI workforce for security operations, not just isolated automation.
Context: Engineering Investigative Knowledge for AI Agents
With this release, Bricklayer introduces Multi-Agent Context Engineering (MACE), a system that ensures investigative context is preserved, accumulated, and shared across AI agents.
Rather than isolating context within individual prompts, Bricklayer treats investigative knowledge as a structured system asset, enabling agents to inherit prior evidence, reasoning, and investigative outcomes.
As multiple agents participate in an investigation, context is continuously built and maintained, preventing loss of critical insight and eliminating fragmented analysis. Investigations no longer reset with each agent or task. Context carries forward, enabling coordinated agents to build on each other’s work rather than operate in isolation.
MACE is applied across all 50 out-of-the-box AI SOC agents, as well as any custom agents created by customers, ensuring consistent context across every workflow. The result is continuous, consistent, and compounding intelligence across every investigation.
Coordination: A Collaborative Workspace for Human and AI Investigative Teams
Bricklayer introduces a dedicated operating environment for human and AI investigative teams to collaborate on shared investigations.
At the center of this experience is the new Bricklayer Workbench, a purpose-built workspace designed to coordinate investigations between human analysts and teams of specialized AI agents. Rather than interacting with isolated AI assistants, analysts operate within coordinated agent teams executing structured investigative procedures on shared context.
Within Workbench, analysts can design, launch, and manage investigative procedures executed by coordinated agent teams. As investigations unfold, the platform provides full visibility into multi-agent plans, reasoning steps, evidence sources, and investigative outputs, ensuring that automated analysis remains transparent and understandable. Collaboration is further supported through shared discussion threads where analysts and agents can communicate directly around active investigations.
Control: Governance Built for Enterprise Security Operations
With this release, Bricklayer introduces a governance layer that ensures AI agents operate within defined boundaries, with full visibility, control, and auditability across every action.
This governance is embedded directly into the platform, enabling organizations to deploy AI agents in security operations while maintaining the transparency, separation, and operational controls required for enterprise environments.
This governance is enforced through:
- Multi-organization management: enables enterprises to operate multiple environments within a unified system while maintaining strict isolation between entities. This allows enterprise business units, regional SOC teams, subsidiaries, and managed service provider customer environments to operate independently while remaining under centralized oversight with per-organization identity management and access control.
- Operational testing: supports separate development, staging, and production environments for safe deployment. New procedures, agent configurations, and investigative workflows can be tested and validated before introducing into live security operations, enabling controlled rollout and measurable impact of automation.
- Data isolation and encryption: protects investigative data through segmentation at the schema level to ensure separation between organizations and environments, while encryption is enforced by default. Organizations may also leverage per-organization encryption keys and optional AWS KMS key management to maintain external control of sensitive data.
- Comprehensive audit logging: records all platform activity including configuration changes, agent updates, procedure modifications, and user activity. These logs can be exported to customer-managed S3 environments to support security monitoring, compliance programs, and enterprise governance requirements.
These capabilities ensure AI-driven security operations remain governed, auditable, and secure. They enable organizations to deploy coordinated AI agents with the controls required for enterprise and regulated environments.
Enabling the Enterprise AI SOC
Organizations using Bricklayer have reduced alert investigation time by 60-90 percent, enabling security teams to operate at significantly greater scale. The new capabilities support core SOC workflows including alert triage, incident response, vulnerability management, and threat intelligence operations.
“Many organizations are experimenting with tool-specific agents, single-use-case AI solutions, or do-it-yourself builds that address only a narrow slice of the SOC,” said Adam Vincent, CEO and Founder of Bricklayer AI. “Without shared context, structured coordination, and enterprise controls, these efforts often lead to agent sprawl rather than meaningful operational improvement. We built Bricklayer so specialized AI agents work together through defined procedures and transparent governance while keeping humans firmly in charge.”
Security leaders attending RSA Conference are invited to schedule a meeting with Bricklayer AI to see the coordinated AI SOC platform in action. The new capabilities will be generally available on April 1st, 2026.
About Bricklayer AI
Bricklayer AI was created to help security operations teams keep pace with AI-driven threats and an ever-expanding attack surface by introducing a coordinated, agent-based approach to the SOC.
The platform enables organizations to deploy specialized AI agents that share investigative context, collaborate through structured procedures, and operate under defined governance and human oversight. Built around the architectural principles of Context, Coordination, and Control, Bricklayer enables security teams to reduce noise, accelerate investigations, and scale security operations without sacrificing transparency or accountability.
For more information, visit https://www.bricklayer.ai or follow Bricklayer AI on LinkedIn.
SOURCE Bricklayer AI
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