At Black Hat USA 2026, DataBahn introduced Federated Search and Orchestration, a new capability designed to help security teams and AI agents search enterprise telemetry without moving or duplicating data. The release expands the company’s agentic data control plane, enabling organizations to query information across multiple repositories, enrich results with business context, and automate investigations from a single platform.

The announcement reflects a growing challenge facing enterprise security teams. As organizations move telemetry into lower-cost storage to control SIEM expenses, security data has become fragmented across data lakes, cloud object storage, archives, and analytics platforms. While this approach reduces infrastructure costs, it also makes investigations slower and more complex.

Searching Data Where It Lives

For years, security operations have relied on centralizing telemetry into a single platform before analysts could search or correlate events. That model is becoming increasingly expensive as organizations generate larger volumes of security data and expand AI-driven workloads.

DataBahn’s latest release takes a different approach by allowing analysts—and AI agents—to search information where it already resides instead of copying it into another repository.

Rather than requiring users to know which storage platform contains a particular dataset or to write queries in multiple search languages, the platform presents a unified search interface powered by natural language. Behind the scenes, DataBahn executes searches across connected data sources without requiring a centralized index or duplicate copy of the underlying data.

The approach is designed to reduce storage costs while preserving access to historical telemetry that organizations increasingly keep in lower-cost cloud storage tiers.

Combining Search, Context, and AI

Federated Search and Orchestration extends beyond search by integrating several capabilities into a single workflow.

A live knowledge graph, called Reef, enriches raw security data with enterprise context, linking technical indicators such as IP addresses to assets, owners, and potential business impact. Instead of presenting analysts with isolated events, the platform attempts to provide immediate operational context for investigations.

The release also expands Lumen, DataBahn’s AI-powered threat hunting and digital forensics assistant. Analysts can describe an investigation using natural language, allowing the agent to correlate evidence across multiple data sources before returning a cited investigation timeline rather than a collection of individual search results.

For organizations adopting AI agents in security operations centers (SOCs), DataBahn has also introduced MCP Hub, a governed gateway that provides AI systems with controlled access to enterprise data and security tools while maintaining permissions and audit trails.

Together, these capabilities are intended to reduce manual correlation work while allowing AI agents to participate more directly in incident investigations.

Addressing the Next Phase of Security Operations

The launch comes shortly after DataBahn announced a $40 million Series B funding round, capital that the company said would accelerate development of its broader agentic data control platform.

Industry analysts have increasingly argued that security data pipelines are evolving beyond simple data movement into governance and orchestration layers for AI-driven security operations. At the same time, enterprises continue searching for ways to balance growing telemetry volumes with rising cloud storage and SIEM costs.

Rather than encouraging organizations to consolidate all security data into a single platform, DataBahn is betting that the future lies in federated architectures where data remains distributed but can still be searched, governed, and orchestrated as a unified resource.

The company says the platform supports more than 600 integrations and can significantly reduce telemetry volumes before they reach downstream security tools, helping organizations lower storage and processing costs while preserving the data needed for investigations.

As AI agents become increasingly embedded within enterprise security workflows, platforms that combine search, governance, contextual enrichment, and automation may become a foundational layer for modern security operations. DataBahn’s latest release reflects that broader shift—from treating data pipelines as infrastructure for moving information to using them as control planes that deliver intelligence wherever enterprise data resides.