Core Strategy
Digital & Data Infrastructure
PropTech integration, smart home readiness, broadband connectivity, and data-driven asset management powering the next generation of housing.
Technology as a Structural Advantage
Most affordable housing operators manage portfolios using disconnected systems, manual processes, and limited data visibility. Kennis Capital embeds technology into every layer of the operating model. Muebox manages operations, Kubiko AI provides intelligence, and IoT sensors generate the real-time data that makes both platforms effective.
This integrated technology stack reduces operating costs, improves maintenance response times, enables predictive interventions, and generates the data required for ESG reporting and green bond certification. Digital infrastructure is not a cost. It is the foundation of competitive advantage at scale.
The Technology Stack
Muebox — Property Operations
Muebox is our property management platform, handling lease administration, maintenance workflows, compliance tracking, and financial reporting across the portfolio. It replaces fragmented spreadsheets and legacy systems with a single source of truth.
Kubiko AI — Intelligence Layer
Kubiko provides AI-driven insights across the portfolio: predictive maintenance, energy optimisation recommendations, tenant risk scoring, and automated regulatory compliance monitoring. It transforms operational data into actionable decisions.
Smart Home & IoT Readiness
Every retrofitted property is wired for smart home integration: smart meters, connected thermostats, and environmental sensors. This generates the data layer that feeds Kubiko AI and Sanufa while improving tenant experience.
Broadband Connectivity
Pilot programmes with leading UK broadband providers bring full-fibre broadband to our properties. Connectivity is essential infrastructure and a baseline expectation for modern tenants.
Data-Driven Asset Management
Every property in the portfolio generates continuous data: energy consumption, temperature, humidity, occupancy patterns, and maintenance events. This data feeds machine learning models that predict component failure, optimise energy usage, and identify properties that would benefit most from targeted intervention.
Predictive Maintenance
ML models trained on sensor data and maintenance history to predict failures before they cause tenant disruption.
Energy Optimisation
Automated heating schedules and demand response participation reducing energy costs across the portfolio.
Portfolio Analytics
Real-time dashboards for asset performance, compliance status, and ESG metrics at fund and property level.
Edge Compute Infrastructure
As portfolio density increases in target regions, our fibre-connected properties become candidates for distributed edge compute nodes. This creates a future revenue layer from telecoms co-location and content delivery, turning residential property into multi-use digital infrastructure.