Capabilities
AI/ML, proven.
Applied R&D across the full lifecycle. Feasibility, rapid prototyping, language systems, and rigorous evaluation, all of it engineered to be production-ready.
Feasibility → Prototype → Evaluate → Hand off
The array
Five disciplines.
One system.
Applied R&D, language and retrieval, modeling, vision, and independent evaluation, engineered to reinforce each other.
The disciplines
Five areas, one practice.
Applied R&D & Rapid Prototyping
Research pointed at the real world. Feasibility studies and fast, working prototypes that answer whether and how AI solves the problem, engineered to be carried into production.
NLP, LLMs & RAG
Language, retrieval, and knowledge systems that turn large, sensitive document sets into grounded, auditable answers, with evaluation baked in, not bolted on.
Evaluation & Assurance
Independent, rigorous evaluation for AI systems, the discipline some communities call TEVV. The assurance work that determines whether a prototype is trusted enough to carry forward, and that stands up to review.
Machine & Deep Learning
Purpose-built models for detection, classification, forecasting, and anomaly detection, designed for real operational data and edge constraints.
Applied Computer Vision
Vision work grounded in the practice's deep learning core. An active medical imaging collaboration with a practicing neurosurgeon (FAANS), and a training-data discipline shaped inside a Navy maritime autonomy program.
Under every area
The data engineering every AI project stands on, included in every engagement.