Unaffiliated concept. Prepared by Cognitum to illustrate a possible Nutanix partnership. Not affiliated with, endorsed by, or produced by Nutanix; no Nutanix trademarks or logos are used.
Hybrid multicloud infrastructure

Edge AI workloads with a fleet story attached.

Running inference at the edge is easy once. Running it across thousands of sites — signed, versioned, resource-budgeted, and rollback-safe — is the actual problem. This platform is built as fleet-managed workloads first and sensing capabilities second.

65Capability demos
116In the catalog
11Categories
On-deviceInference and storage

Why this fits Nutanix

Nutanix keeps the hardware, the channel and the customer relationship. Cognitum supplies the intelligence layer as bounded, signed, replaceable objects behind a surface that stays yours.

Fleet management is the product

Signing, digest pinning, resource budgets, staged promotion and rollback are properties of the platform, not scripts around it.

Bounded resource consumption

Every capability declares its budget, so edge nodes stay predictable under load instead of degrading unpredictably.

Reproducible and auditable

Images build reproducibly with an SBOM and a component lock, which is what regulated edge deployments actually get asked for.

Runs where the data is

Inference stays on the edge node. Nothing about the workload requires shipping raw sensor data to a core.

The operator console

Static snapshots of a real running build. Same navigation, same data model — shown here in its reference theme; a Nutanix build would carry Nutanix branding throughout. Controls are not wired to a live device.

Capability catalog

65 capability demonstrations, grouped by what they do, with the categories most relevant to Nutanix first. Search or filter, then open any demonstration.

Fleet & mesh10 featured

Coordination across many devices — consensus, replication, load balancing and orchestration between nodes rather than inside one.

On-device intelligence7 featured

Inference, attention and continual-learning primitives that execute on the device instead of round-tripping to a cloud.

Developer tooling5 featured

Surfaces for building, deploying and debugging capabilities against a real device.

Health & wellbeing8

Contactless physiological sensing from ambient radio: no camera, and nothing worn by the subject.

Research methods7

Advanced and experimental techniques — sparse recovery, temporal logic, hyperbolic embeddings and other frontier work.

HomeCore surfaces5

Role-scoped household and installer surfaces over HomeCore state (ADR 018). Each renders a bounded view; HomeCore owns the domain state.

Security & safety5

Intrusion, tailgating, weapon and anomaly detection for premises protection.

Industrial & workplace5

Plant-floor and site safety: proximity, confined space, structural and equipment monitoring.

Building & energy5

Occupancy-driven HVAC, lighting and energy behaviour for commercial and residential space.

Signal processing4

The RF layer the rest of the catalog builds on — compression, coherence and interference handling.

Retail & spaces4

Footfall, dwell, engagement and turnover analytics for physical retail and hospitality.

No capabilities match that search.

About these pages. Each is the demonstration interface for that capability, served exactly as it ships on the device. They render representative data — nothing here is sensing, inferring, or reading live device state.