AI & Big Data — Information Advantage, Responsibly
We build data pipelines, models, and governance that sharpen situational and operational awareness—aligned to DoD Responsible AI, NIST AI RMF, and test & evaluation practices for AI-enabled capabilities.
What we solve
From noisy data and brittle tooling to decision‑grade intelligence.
Data readiness
Authoritative sources, lineage, and quality checks; schema‑on‑read streaming and batch ETL to feed the COP.
MLOps at the edge/enterprise
Pipelines for training/inference, model registries, drift & performance monitoring, and rollback plans.
Responsible AI & TEVV
Risk‑based governance (RAI), evaluation plans, and evidence to build justified confidence in AI results.
How we do it
Standards‑aligned architecture, workflows, and evidence.
Ingest, curate, and fuse telemetry, logs, geospatial, and intel—edge‑to‑cloud with degraded‑mode options.
Model/data versioning, CI/CD for ML, evaluation gates, and audit trails that survive review.
Threat‑informed tests, performance/robustness, human‑machine trust, and rollback triggers.
RAI toolkit artifacts, risk registers, and approval workflows tied to mission context.
- Reference data model & pipeline specs (edge/enterprise)
- Model cards & evaluation reports (metrics, datasets, limitations)
- MLOps runbooks, monitoring & rollback plans
- RAI/AI RMF alignment package & decision logs
- DoD Responsible AI Strategy & Toolkit
- NIST AI Risk Management Framework 1.0 (+ GenAI profile)
- DoD T&E for AI (DT&E/OT&E) and VV&A for M&S