Overview
Harnessing real-time data, Ai-driven analytics and data-led maintenance insights
In a world where buildings are no longer static structures but dynamic ecosystems, Acutro is committed to how it can optimise building performance through a smart buildings lens.
The Acutro Core product harnesses real-time data, AI-driven analytics, and data-led maintenance insights to deliver unparalleled efficiency, sustainability, and savings. From commercial portfolios to critical infrastructure, we enable clients to shift from reactive, time-based maintenance to intelligent, data-led operating systems that streamline operations, reduce costs, minimise downtime, and enhance asset longevity.
Key features
Asset health scoring (AHS) service
Event-driven system scores key connected assets on a 10-100% scale, using its Dynamic Logic (DyLo) engine, machine-learning, and tiered data integration (Levels 1-6). Includes time auditing, interactive visualisations, and real-time measurement for early issue detection.
Data-led maintenance automations
Integrates with industry-standard maintenance guidance for color-coded task prioritisation of planned maintenance (Statutory, Mandatory, Function Critical, Discretionary). Facilitates automations to optimise maintenance scheduling through suppression of jobs/tasks via 24/7 monitoring and dynamically adjust schedules based on logic underpinned real-time asset health scores, with two-way CAFM/FSD integration for work order generation, calendar syncs and efficiency reporting.
Dynamic logic engine
Provides a robust, fault detection and diagnostics (FDD) foundation, designed to identify common performance issues across building services. This baseline logic is then progressively enhanced with building-specific logic statements that reflect the unique systems, design intent, control strategies, and operational challenges of each site.
By contextualising data at a building and system level, DyLo moves beyond static rules, enabling adaptive logic that evolves over time to deliver more accurate diagnostics and outcomes that align with real-world operation.
HNTAS compliance and reporting
Captures 12+ KPIs for the new Heat Network Technical Assurance Scheme (HNTAS) published in 2026 for energy centres, ensuring reliability (≤3 unplanned interruptions/year), efficiency, and uptime (≥98%). Supports feasibility, design, construction, and operation phases with live data validation.
Scalability and AI
Designed to scale seamlessly from individual buildings to large, multi-asset portfolios, Acutro applies AI assisted analytics to identify patterns, anomalies, and performance trends across thousands of data points.
Machine-learning models enhance the Dynamic Logic Engine by refining thresholds, improving diagnostics, and reducing noise as data volumes and operational maturity increase. This enables consistent performance management at scale, portfolio benchmarking, and continuous improvement, while ensuring that insights remain grounded in building-specific context rather than generic models.
Benefits
Acutro helps organisations move from reactive building management to proactive, data-driven operations. By connecting asset performance, maintenance activity, and operational data, the platform delivers actionable insights that improve reliability, strengthen compliance, reduce risk, and optimise costs across single buildings or entire portfolios.
How it works
Acutro transforms building data into intelligent operational insight through a structured, data-led workflow. By ingesting information from multiple systems, applying AI-driven monitoring, and enabling automated optimisation and reporting, the platform helps organisations continuously improve building performance and maintenance outcomes.
FM Service Delivery Monitoring
Compliance
Energy Optimisation
Maintenance Suppression
Predictive Maintenance
Fault Detection
Asset Lifecycle Scoring
Automation
Data ingestion
Ingest, normalise and tag a combination real-time data and static data from multiple sources into a centralised environment.
Monitoring & scoring
Apply logic and AI across the dataset to enable asset health scoring, data-led maintenance automation and fault detection.
Optimisation
Dynamically suppress or accelerate maintenance tasks; prescribing interventions for review and authorisation.
Action & reporting
Integrate with downstream tools like CAFM/FSD for work orders and calendar syncs; providing dashboards, digital twin, intervention logs, and compliance reporting.
Continuous improvement
Underpinned by feedback loops and iterative changes to logic to refine building performance over time to deliver more innovative, sustainable building operations.
Maintenance strategies
It is important we understand the evolution in maintenance strategies and the journey we support in taking customer on towards a more progressive, tech-led operation.
A structured, compliance-focused regime based on schedules from the SFG20 standard, covering legal and best practice tasks across asset types.
Aligns maintenance efforts with business priorities – focusing on high-impact assets and outcomes rather than uniform servicing.
Uses live and historical data from systems (e.g. BMS, IoT sensors) to inform decision-making on when and where to maintain.
Leverages machine learning, AI and historical patterns to predict failures before they happen, enabling interventions.
Testimonials
