Zignal Labs today announced the launch of Zignal AI, a new platform architecture designed to deliver structured intelligence derived from publicly available information (PAI) directly into mission systems, operational workflows, and agent-driven environments. Built on more than 15 years of experience with high volume, multimodal publicly available information, Zignal AI transforms fragmented public data into mission-ready outputs.
Zignal AI delivers structured intelligence from PAI into mission systems, partner platforms, and agent-driven workflows.
ZEN platform updates include AI Chat, Inbox, agentic reporting, and multi-agent workflow capabilities.
Zignal AI integrated into Peraton's IRIS platform for cognitive and operational workflows.
Deployed with Everforth ECS for geolocated image and video detections into Maven Smart Systems.
New capabilities include inauthentic messaging detection (preview) and expanded deep/dark web data.
Zignal has been a GSOF Corporate Partner since 2024.
“The challenge isn't access to public data. The challenge is transforming fragmented, multimodal information into structured intelligence,” said Adam Beaugh, CEO of Zignal Labs. “Agents don't need more raw data. They need trusted, mission-aligned outputs on which they can act with confidence. Zignal has been solving this problem for over a decade – conditioning, enriching, validating, and structuring publicly available information into operationally relevant intelligence. Zignal AI now makes that possible across analysts, platforms, and agent-driven workflows, at scale.”
Zignal AI is designed for organizations building, integrating, or modernizing mission systems that require publicly available information as part of operational workflows. Rather than forcing customers into a single interface, Zignal AI can be accessed through ZEN, delivered via APIs, embedded into partner platforms, or integrated directly into customer-owned systems.
“Zignal AI enables IRIS to incorporate structured intelligence – from narrative detections and alerting to visual and geospatial signals – directly into our agent-driven workflows. That precision matters,” said Cliff Bean, Senior Director, Cognitive Warfare, Cyber & Intelligence Sector at Peraton. “Instead of requiring agents to process large volumes of raw, inconsistent data, we're able to operate on curated, mission-aligned intelligence artifacts.”
“Our work with Zignal since 2021 has focused on delivering highly curated, geolocated detections directly into Maven to support specific missions within the global combatant commands,” said Heather Maderia, Associate Director – OSINT Solutions at Everforth ECS. “The ability to inject externally derived, mission-relevant context strengthens the overall intelligence picture without adding noise or processing burden.”
New ZEN capabilities include:
AI Chat for querying and exploring existing datasets, maintaining analysis history, and generating visual outputs
Inbox as a centralized hub for alerts, summaries, notifications, and follow-on action across multiple signal types
Agentic Reporting to synthesize multi-source intelligence into structured, presentation-ready outputs
Multi-agent workflows that enable more efficient analysis across datasets and mission contexts
Expanded deep and dark web data to surface harder-to-reach conversations and emerging risks
Inauthentic messaging detection (preview) to identify coordinated activity, amplification networks, geographic spread, and campaign effects
Zignal Labs delivers AI and agentic intelligence for national security, transforming raw, publicly available information into structured, mission-aligned intelligence that analysts, AI systems, and mission platforms can reliably consume and operationalize. Built on more than 15 years of operational experience, Zignal ingests, filters, enriches, validates, and structures high volume, multimodal data across text, imagery, and video to support earlier warning, sustained situational awareness, force protection, maritime awareness, influence detection, and other mission-critical operations.