Cyber and sensor analytics for U.S. defense and intelligence agencies
Global InfoTek builds RF sensor analytics, ML operationalization, and cyber tools for DoD, DHS, and Intelligence Community customers. The stack—C++, Rust, Go, Python, plus TensorFlow, PyTorch, and Hugging Face—reflects heavy ML and signal processing workloads; active Rust adoption signals a shift toward memory-safe systems for performance-critical pipelines. A senior-heavy hiring profile (11 of 23 open roles) and distributed project focus on edge ML, stream processing, and sensor data quality suggest scaling mature capabilities across multiple contract vehicles rather than building greenfield platforms.
Global InfoTek is a 51–200-person defense and intelligence contractor headquartered in Reston, Virginia with offices in San Antonio, Colorado Springs, Annapolis Junction, and Rome. Founded in 1996, the company holds Top-Secret facility clearance and deploys solutions across enterprise cyber, DevSecOps, zero-trust architecture, AI/ML, and large-scale data analytics. Prime contracts include AFRL's ACT³, GSA MAS, AFRL ESCAPE, OASIS SB (Pool 4), Level up BOA, AFLCMC ABMS, and SeaPort NxG. Core work centers on RF sensor data quality, passive emitter identification, ML model operationalization on edge hardware, and real-time stream analytics.
C++, Rust, Go, Python, TensorFlow, PyTorch, Hugging Face Transformers, AWS, Azure, GCP, Docker, GitLab, SonarQube, Fortify, IDA Pro, Ghidra, and MySQL. Actively adopting Rust for performance-critical components.
RF sensor data quality and emitter identification, ML pipeline operationalization for edge hardware, stream ingestion and rollup infrastructure, browser-based visualization tools, and AI-generated imagery detection. Projects span signal processing, machine learning, and real-time analytics.
Global InfoTek, Inc.'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.