Babel Street Announces Agentic Risk Intelligence, Enabling Analyst-Led, AI-Executed Investigations

Washington, D.C. – May 18, 2026 – Babel Street, the world's leading provider of mission-grade risk intelligence (Headquarters: Reston, Virginia, USA; Japan Subsidiary: Babel Street Rosette Co., Ltd. (Minato-ku, Tokyo); CEO: Benji Hutchinson), today announced "Insights Investigator," a new agentic capability. Designed to have an AI agent trained on intelligence domain expertise take the core role in investigative tasks, Insights Investigator processes large volumes of investigative work at high speed while ensuring analysts maintain full control over the mission scope, query logic, reasoning, and outcomes. Delivered as part of the Babel Street Insights platform, Investigator enables a shift from traditional analytical methods centered on search and AI-assisted queries to an "analyst-led, AI-executed" investigation style.

Threat actors are no longer bound by the constraints of human processing capacity. State-sponsored attackers, organized crime networks, and hostile foreign intelligence agencies are leveraging AI to accelerate disinformation campaigns, fabricate synthetic identities, probe supply chains, and conduct influence operations on an industrial scale. If defenders continue to rely on manual investigations, they will fall behind before executing their first query.

Benji Hutchinson, CEO of Babel Street, stated the following:

"Adversaries are already deploying AI-driven campaigns at a scale that manual workflows simply cannot match. For the organizations we support to combat this speed and scale, they cannot afford to have their world-class analysts spending their capabilities on mere data tracking. Insights Investigator brings defenders an agent trained on a decade of mission data and practical intelligence expertise. This allows analysts to focus on delivering actionable intelligence that directly informs decision-making."

Designed for environments where the success or failure of a judgment leads to critical consequences, Insights Investigator allows analysts to express their intent in natural language, and the AI agent then rapidly executes the approved investigation. Investigator is built upon Babel Street's proprietary Data Dominance™. With a trusted multilingual data foundation curated and prepared according to the mission, and a unique data processing infrastructure designed for agent utilization, it embeds reliable data, transparent reasoning, and traceable evidence into all investigative workflows. Consequently, it achieves faster investigations without compromising auditability, source governance, or human control.

Early adopters have reported a reduction in investigation times by over 50%. This translates to saving several hours per analyst each week, and instances have been reported where entire teams have reduced the time required for data collection in ongoing investigations by several days.

Brian Fuller, Executive Director of the Office of Strategic Initiatives and the Center for Intelligence Research Analysis and Training (CIRAT) at Mercyhurst University in the US, commented:

"Insights Investigator has significantly changed how our analysts operate. Information gathering that previously required days of manual work is now completed in hours while maintaining the source governance essential for our clients. The time savings enable defenders to act more swiftly in areas such as tracking illicit financial networks and monitoring rapidly changing threat indicators."

Insights Investigator is designed based on advanced intelligence insights, workflows, and experiences cultivated by frontline practitioners. The key features included in this release are as follows:

Trusted Data Dominance: Investigator utilizes data assets curated and prepared by Babel Street according to the mission, enabling cross-format investigations into diverse formats actively used by threat actors, across more than 200 languages. With newly added entity extraction capabilities, data is structured upon ingestion, improving search accuracy and supporting more consistent, evidence-based analysis.

Analyst-Led AI Agent: Analysts define the objectives, and the plan