Expedition Technology provides an end‑to‑end sensor‑processing platform that combines traditional digital signal processing with AI/ML inference on FPGA and GPU accelerators to analyze radar, EO/IR, acoustic and communications data in real time at the edge. The solution includes cloud‑native analytics, secure data pipelines, and APIs that deliver actionable threat assessments and visualizations directly into existing command‑and‑control systems for defense and intelligence operations.
Funding
Funding not disclosed
Founders
Product
Problem
Defense and intelligence agencies must analyze massive streams of raw sensor data—radar, EO/IR, acoustic, and communications—in real time to maintain situational awareness and assess emerging threats. Conventional processing pipelines are often siloed, rely on heavyweight hardware, and lack the flexibility to incorporate modern AI/ML techniques, leading to delayed decision making. Additionally, the need for secure, deployable solutions that operate both at the edge and in the cloud remains unmet.
Solution
Expedition Technology delivers end‑to‑end sensor‑processing platforms that fuse traditional signal processing with advanced computer‑vision and deep‑learning models. By embedding AI/ML inference on FPGA and GPU accelerators, the system can ingest gigasamples per second at the edge while maintaining low latency. Cloud‑native components built with Docker, Kubernetes, and automated DevOps pipelines provide scalable analytics, continuous updates, and secure data handling. The resulting product‑oriented solutions generate actionable threat assessments and visualizations that integrate directly into existing command‑and‑control workflows, enabling operators to react swiftly in dynamic environments.
Target Audience
Primary customers are U.S. Department of Defense units, intelligence community agencies, and defense contractors that require real‑time, AI‑enhanced sensor processing for mission‑critical operations. Commercial partners developing security‑focused products also leverage Expedition’s technology stack.
Features
- Edge‑optimized processing chain that combines classic DSP algorithms with neural‑network inference on FPGA/GPU hardware for real‑time analysis of multi‑modal sensor streams
- Multi‑sensor computer‑vision pipeline capable of detecting, tracking, and classifying objects across radar, EO/IR, and acoustic inputs, even with limited training data
- Cloud‑native analytics platform using Docker containers and Kubernetes orchestration for scalable model deployment, continuous integration, and automated security updates
- Secure data pipeline with end‑to‑end encryption, role‑based access controls, and compliance‑ready logging for classified environments
- Customizable web dashboard that visualizes raw sensor feeds, AI‑generated alerts, and threat‑level metrics with drill‑down capabilities
- API layer supporting integration with existing DoD and intelligence command‑and‑control systems, including FHIR‑style data exchange for interoperability
- Agile product development framework that transitions prototypes from research to fully supported fielded hardware with continuous delivery cycles