Platform Innovation
The connected home.
Extending capabilities.
Two platform extensions built on our production agent. A home platform that brings broadband, energy, security and family controls into one operator-led interface. A care extension that adds on-device inference, spatial awareness and life-safety telemetry to enable assisted living.
Intelligent Home Platform
One platform.
Every home service.
A working home platform that runs on the operator's existing gateway, one interface for connectivity, energy, security and family controls. Built on our production agent, ready to evaluate and co-develop.
This is what operator-led home services look like in practice. Real-time telemetry from the smart meter, Wi-Fi 7 mesh and connected appliances feeds performance management, closed-loop control and diagnostics, all orchestrated from the device already installed in the home.
Home Dashboard
Household overview with contextual insights, family presence detection, energy snapshot and quick controls: everything relevant to the home in a single view.
Connectivity Management
Wi-Fi 7 mesh topology, device-by-device bandwidth allocation, speed diagnostics and proactive fault detection, often before the household notices a problem.
Energy Intelligence
Real-time consumption, solar and battery state, tariff optimisation and direct appliance control. Closed-loop demand flexibility response within operator SLA windows.
Home Security
Sensor status, activity timeline, arm and disarm controls and alert management, all integrated directly into the gateway rather than a separate application.
Family & Parental Controls
Per-person device management, usage insights, content controls and scheduling, giving households meaningful oversight of their connectivity without complexity.
Supporting Paper
The convergence of energy and connectivity
Our paper explores how residential gateways become the convergence point for energy, broadband and home services, and why operators are uniquely positioned to lead this transition.
Download the paperInteractive Platform Demo
See the platform
in action.
Load the Home Hub app inside the device frame to explore how the platform brings connectivity, energy, security and family controls together in a single operator-led interface.
The prototype loads on demand. Every screen connects to a real telemetry pipeline, showing what the production interface looks like.
- Home DashboardContextual insights, family presence, energy snapshot and quick controls
- ConnectivityWi-Fi 7 mesh health, per-device bandwidth and proactive fault alerts
- EnergyReal-time consumption, solar/battery flows, tariff optimisation, appliance control
- SecuritySensor status, activity timeline, arm/disarm and alert management
- FamilyPer-person device management, usage insights and content controls
Home Hub Platform
Explore energy, connectivity, security and family controls inside the device frame.
Commercial Value
Why the gateway is the right foundation for home services.
UK broadband providers are positioned on an unrealised opportunity. They already have hardware in every home, relationships with energy suppliers through the smart meter rollout, and the technical capability to integrate security and home automation. We've built the software layer that ties it together and makes that position worth something to every household.
For Operators
Engagement that extends beyond connectivity.
Churn reduction through daily household engagement. ARPU uplift via premium service tiers. Referral revenue from energy switching. A value proposition that extends well beyond broadband.
For Households
One interface. Every home service.
Energy costs, connectivity management, home security and family controls in a single place. Multiple services that are genuinely useful together rather than separately.
For the Wider System
Infrastructure that enables flexibility at scale.
A distributed edge layer that enables demand flexibility, richer household data and a practical route to higher-value services, all built on infrastructure already present in every home.
Technical Architecture
Real-time telemetry. Local inference.
Cloud intelligence at scale.
Edge-First Data Pipeline
Every device is a source of continuous telemetry. Gateway hardware metrics, mesh node quality, smart meter data at 10-second intervals, appliance state in real time, all flowing over MQTT to a local broker with sub-second latency to the application layer or cloud.
Control decisions execute on the gateway, without a cloud round-trip. Solar export peaking against a low tariff? EV charging shifts immediately. Flexibility signal arrives from the supplier? Response within the contracted latency window. Milliseconds, not seconds.
On-Device Inference & Cloud Intelligence
Local inference runs on dedicated NPU silicon from Broadcom, MediaTek, Silicon Labs, Intel and Nvidia. Quantised models (Llama, Mistral, Phi) handle pattern recognition and anomaly detection on-device, deployed through LiteRT or ONNX Runtime.
Frontier model families in the cloud handle deeper reasoning and natural language generation against anonymised fleet data, retrain inference models and push updated weights back to the fleet. On-device for latency-sensitive and privacy-critical work; cloud for scale and reasoning depth.
Security Model
Security designed into every layer.
Input validation and schema enforcement on all MQTT messages prevent malformed or malicious payloads from reaching the inference stack. Model outputs pass through confidence gating and output filtering before triggering any control action. For any cloud-facing model interaction, prompt injection defences and adversarial robustness testing are part of the deployment pipeline. Model weight updates are cryptographically signed and verified before the gateway accepts them. Household data stays on-device by default; only anonymised, aggregated telemetry leaves for the cloud training pipeline.
Assisted Living Care Extension
Care intelligence built into the connected home.
We're extending the operator's existing infrastructure into a care platform. The gateway already provides connectivity and energy intelligence. This layer adds on-device inference, spatial awareness and life-safety telemetry, context, proactive alerts and real-time notification without cameras, without constant cloud dependency, and without compromising privacy.
Most assisted living technology is built as a standalone product. We start from the opposite direction: operators already have the connectivity, the gateway and the household relationship. The question is whether that infrastructure can carry a care layer. It can.
The care extension runs on the same agent as our energy and home services platform, same MQTT pipeline, same security model, same edge-first architecture. Operators don't need new infrastructure. They need the software layer that makes what they already have useful for care.
Supporting Paper
Commercial case for operator-led care
Our commercial paper sets out the full business logic for operator-led smart security, assisted living and healthcare monitoring services, including market sizing, service architecture and deployment models.
Download the paperProof of Concept
Multi-floor home model
Our proof-of-concept demonstrates occupancy context, life-safety telemetry and network awareness operating inside a multi-floor home model, showing how the gateway becomes a care platform without any additional hardware.
On-Device Intelligence
Inference at the edge.
The demonstrator runs a stack of lightweight inference models on the NPU. Not threshold monitors or rule engines, models trained on population-scale behavioural data in the cloud, then deployed as quantised binaries that assess the state of the home continuously against learned patterns of normal activity.
Sensors and devices publish state changes over MQTT to the local broker; the inference stack processes the event stream in real time. It draws on motion sequences, door contact timing, temperature gradients and device state at once, a continuous picture of what is happening, and where.
For natural language work, summarising daily activity for a carer, generating plain-language alerts, frontier cloud models run against anonymised context. On-device for latency-sensitive and privacy-critical work; cloud for reasoning depth.
Spatial Awareness
Room-level understanding.
No cameras.
Spatial awareness is derived from the inference stack interpreting a sparse sensor array: motion detectors, door contacts, temperature sensors and the passive sensing capability of the Wi-Fi mesh itself. Room-level occupancy is not read from any single signal. It is inferred from the pattern across all inputs simultaneously, updated in real time as the household moves through the day.
The gateway builds and maintains a live spatial model of the home: which zones are active, which have been quiet, and for how long. That spatial model is the foundation for everything else. Without it, an extended period of inactivity in a single room might be unremarkable. With it, the platform can assess whether that represents a normal rest pattern or something that warrants attention.
The result is genuine context. The inference engine knows it is mid-morning, that the kitchen has been active for twenty minutes, that movement has recently passed from bedroom to bathroom, and that this pattern is consistent with a normal Tuesday. That contextual model is what distinguishes a care platform that understands a household from one that merely watches it.
From Inference to Action
Advice, alerts and automated response.
Alerts are generated when the inference engine reaches a confidence threshold, not when a sensor crosses a hardcoded value. That distinction matters.
A confidence-based alert is informed by the full contextual picture: time of day, recent activity history, deviation from learned norms and the spatial model of the home. The same sensor event that would trigger a false alarm in a naive threshold-based system is assessed in context before anything fires. False positive rates drop significantly. It is the single most important factor in whether care technology actually gets used day to day.
Advice works the same way. Rather than surfacing every anomaly as an alert, the inference engine generates proactive recommendations grounded in what it has learned about the household: a suggestion to adjust a routine, a note that activity patterns have shifted over the past week, a prompt for a welfare check based on accumulated context rather than a single event.
Automated response is the delivery layer. When inference reaches a defined confidence level, MQTT-driven actions execute on the gateway without waiting for a cloud response: a notification dispatched, a contact called, a door unlocked for a first responder, a connected device adjusted. Latency from trigger to action is measured in milliseconds. The cloud is not in the critical path.
Explainability
Why explainability matters in care.
In assisted living, confidence matters as much as detection. Good care technology should do more than flag that something has happened. It should help a carer, operator or family member understand why an alert was triggered and how confident that assessment is. Explainable confidence scores reduce false reassurance, improve triage and make the platform easier to trust over time. That is the difference between technology that gets adopted and technology that gets switched off.
Data Architecture
Structured for care continuity.
High-frequency sensor telemetry flows into a time-series database, the right structure for windowed, pattern-based queries. Significant events and alert triggers are stored in an event store alongside their full inference context, creating a sequential, auditable record for care continuity and review. The cloud training pipeline ingests anonymised, aggregated event data from the deployed fleet, retrains models and pushes updated weights back to every gateway. Individual household data stays on-device throughout.
Commercial Case
A care layer built on infrastructure operators already own.
For Operators
A route into higher-value care services.
Operators can extend into care and safety services grounded in infrastructure they already manage: connectivity, the gateway and the household relationship, without building new platforms from scratch.
For Families
Peace of mind without intrusive monitoring.
Useful, reliable signal rather than constant surveillance. Families get confidence in the wellbeing of those they care for without the privacy compromises of camera-based approaches.
For Health & Care Systems
Earlier intervention. Longer independence.
Earlier detection of declining activity patterns, better prioritisation of care resources, and meaningful support for individuals living independently for longer, at population scale.
Work With Us
See both platforms running.
Operator, utility, care provider, technology partner, we'll demonstrate the platform live and walk through what deployment looks like for you.