NEXOD is an AI consultancy and product studio. We build AI systems, advise on vendor selection, engineer context pipelines, and train teams to work with frontier models. Strategy through deployment.
Independent technical due diligence and AI roadmap architecture. We evaluate vendors, map data readiness, and design adoption paths. For teams new to AI, we run hands-on enablement workshops.
Production AI systems from architecture to deployment. Custom agent pipelines, context engineering, computer vision integration, and the bridge layer between AI vendors and internal teams.
Internal product incubation and proprietary research. Every system NEXOD advises on, NEXOD can build. We ship venture grade software and publish open research.
Every engagement follows the same three phase structure. The protocol is designed to reduce risk at each stage and produce auditable artifacts that survive procurement review.
Technical feasibility assessment, data sovereignty mapping, and risk quantification. Vendor evaluation against structured scorecards. High impact deployment targets ranked by ROI and regulatory exposure. Deliverable: decision ready recommendation memo.
Context topology design, routing schemas, and system specification. Integration architecture between AI vendors and your internal infrastructure. Edge first when latency demands it. Deliverable: technical specification and integration blueprint.
Deployment, clinical observation, and operational transfer. Controlled trials validate system adherence before production handoff. Documentation, training, and monitoring frameworks included as standard. Deliverable: production system with operational runbook.
NEXOD validates every system through controlled clinical trials before deployment. These numbers represent our internal research methodology applied across the Lingot context engineering standard.
NEXOD systems run on Lingot, our proprietary context engineering standard for composable intelligence. Structured domain knowledge compiled into machine-readable blocks that force frontier LLMs to adhere to strict constraints.
Most of the AI industry is busy predicting the future. We are busy building in the present. What can you ship today, with the models that exist today, that makes your team measurably better tomorrow.