Copenhagen AI builds the Algorithmic Foundations, Agentic Frameworks, and Data Intelligence that...
...provide true substrate independence.
Through GitOps-native workflows and open-source foundations, we treat Hyperscalers, IaaS, and Private Clouds as interchangeable compute targets—ensuring your Machine Learning models and AI remain portable, permanent assets.
CPH.AI operates on two distinct logical frequencies. We architect for systematic performance or absolute resilience, depending on the mission profile.
Leveraging Hyperscalers and SaaS inference endpoints for maximum throughput. We engineer Agentic Workflows that operate with kinetic speed, utilizing the full scale of public cloud infrastructure.
View Transformation Journey
Continuous velocity loop.
We map the mathematical trajectory of value. Defining the architecture, selecting the models, and establishing the sovereignty protocols.
The build phase. Infrastructure provisioning, model fine-tuning, and the coding of agentic logic layers.
Deployment to the edge. Establishing MLOps pipelines, continuous evaluation loops, and autonomous scaling.
Latest output from the CPH.AI Research Institute.
The internet is becoming a dark forest of synthetic actors. To preserve trust in digital commerce and discourse, we must move beyond CAPTCHA. We introduce "Know Your Agent" (KYA)—a cryptographic standard for declaring the non-human nature of autonomous systems. HUV.AI is our contribution to this necessary future.
As nations tighten borders on data, the ability to move model weights across jurisdictions becomes a primary survival metric. We explore the rise of "National Clouds" and the strategic necessity of dual-stack architecture.
Moving from "Question & Answer" to "Goal & Execution". How multi-agent swarms and OODA loops are replacing traditional RPA in high-frequency environments. A deep dive into our swarm topology.