Cignal AI™ Platform

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Cignal AI is an Industrial GenAI platform that generates physically accurate, multi-modal training environments from natural language prompts. With Cignal AI, you can deploy specialized agents that can construct, build, or arrange complex multi-modal/multi-spectral scenes in seconds.

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Built for the Physical World

Powered by Cignal Engine, our patented Voxel-Tensor Rendering Engine, Cignal AI produces fully labeled X-ray, CT, Millimeter Wave, and multi-spectral outputs — eliminating the data bottleneck that slows AI deployment across industrial, medical, and defense applications.

Prompt to Reality
Describe a physical scenario in natural language and Cignal Engine generates a fully labeled, physically accurate multi-modal environment in seconds.
Multi-Modal
X-ray, CT, MMW, and multi-spectral outputs paired with natural language annotations. Purpose built for training the next generation of Vision Language Models.
Accelerate MLOps
Compress months of data collection into hours of generation, closing the gap between AI development and real world performance.

The next wave of AI is physical AI.

-Nvidia’s co-founder and CEO Jensen Huang

Resources

Tutorial

Agentic AI in the Cignal Sandbox

In this video, Cignal introduces the Cignal Toolbox Node, providing in-browser language models the ability to execute JavaScript functionality to build agentic testing and workflow processes.

Tutorial

Building an AI Testing Workflow in Cignal Nodegraph

In this demonstration, Justin Tornetta shows how to use the Cignal Sandbox to build a simple testing workflow to find problems in AI systems.

Tutorial

Drag and Drop RAG: Instantly Improve any LLM

In this demonstration, Cignal demonstrates how to use drag-and-drop RAG to improve LLM stability and performance.

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Protected by U.S. Patent Nos. 11,893,088, 12,361,099. Additional patents pending.
Cignal® is a registered trademark of Cignal LLC.
Cignal LLC is a portfolio company of the DHS Silicon Valley Innovation Program (SVIP).
References to DHS, SVIP, or any specific government project do not constitute or imply an official endorsement,
recommendation, or favoring by the United States Government.