Six integrated disciplines, delivered by engineers who have shipped on active DoD and IC programs.
Data pipelines, ML productization, and GenAI applied where the mission actually needs it — agents driving decisions inside workflows, RAG architectures over mission data, and embedding models trained to a specific domain. Not chatbots or research demos; systems that run in production.
We build full-stack production systems in Java, Python, Node.js, and React — secure by default, STIG-aware, and engineered for the decade-long lifecycles federal programs demand. Proven in classified and air-gapped environments.
We modernize legacy applications onto Kubernetes, Docker, and AWS — with the judgment to lift-and-shift when it fits and rebuild when it doesn't. Infrastructure-as-code from day one, with the operational discipline FedRAMP, IL-tier, and disconnected deployments require.
Analytics that scale to billions of records across streaming and batch — from raw collection through enrichment to the analyst's dashboard. Built on Elastic, Kafka, Kibana, and Spark, tuned to the volume and latency real production data actually runs at.
Native-code engineering above and below the surface. We write C, C++, and Rust on embedded and firmware targets — building where standard application stacks can't reach — and we reverse real binaries, protocols, and firmware images, working in IDA, Ghidra, and gdb on artifacts that don't ship with documentation.
We engineer parallel and GPU-accelerated workloads for cluster and supercomputing environments — decomposing problems across thousands of cores, tuning for interconnect and memory bandwidth, and scheduling against real allocation limits. From simulation and signal processing to large-scale model training, we make mission-scale compute deliver on schedule.
