Let AI Agents Do The Work

Machine learning finds anomalies that humans miss. Agents optimise energy, explain alarms, route tickets and polish tenant messages so operations run faster with less effort.

Trusted by Industry Leaders

Telia
Kaamos
Infortar
Eften
Everaus
Triple Net Capital
Ladu112
Hektor Design Hostels
Solar Estonia
Kookon Smart Storage

Fewer surprises and less downtime

Faster decisions with clear alarm explanations

First-visit fixes thanks to better context and diagnostics

Professional tenant comms - AI expands short replies into on-brand, empathetic updates with details that matter

Fewer admin calls & emails through AI call & email routing

Benefits illustration

How It Works

1

Listen

Ingest live data from BMS, meters, access, weather and tariffs, plus calls and emails with tenants and vendors.

2

Detect

Machine learning & LLM algorithms compare signals to history and peer assets to flag anomalies, rank risk and find likely root causes.

3

Act

Create and route maintenance requests with procedures, grant time-boxed access, translate cryptic alarms into plain-language root causes with step-by-step actions for technicians or tenant self-fixes, send polished notifications, and keep admins in control.

Why Teams Use Fentrica AI for Maintenance & Energy

Anomaly detection & failure prediction

Leverage the power of big data. Learns the “normal” of each asset, cross-checks OEM guidelines and fleet history, and flags tiny drifts, often as little as 3% efficiency loss, before they become breakdowns. Suggests likely causes and recommended checks.

Prioritises by cost, comfort and risk to cut noise
Predicts time-to-failure windows and proposes parts
Anomaly detection & failure prediction

Smart alarm aggregation, one inbox

Pull alarms from BMS, meters, access and IoT into a single queue. We de-duplicate and correlate signals to uncover leaks, failing sensors and heat vs cool conflicts, then route only the actionable incidents to the right team.

Merge related alerts into one incident, suppress self-clearing spikes with hold-down and quiet hours
Cross-system correlation catches conflicts and hidden faults standard BMS pages miss
Route by site and priority with escalations; convert incidents to tickets with access and procedures
Smart alarm aggregation, one inbox

Energy optimiser

Tunes HVAC and lighting to occupancy, weather and tariffs, and orchestrates solar and BESS to buy low, use or sell high. Cuts energy 10–25% without comfort drift.

Pre-cool or pre-heat before peaks, cap demand and resolve heat vs cool conflicts with guardrails
Optimise BESS charge/discharge and solar usage to shift load off peak rates or sell when profitable
Live kWh/m² and projected energy rating, exportable to finance and ESG
Energy optimiser

Alarm explanation agent

Turns cryptic BMS failure codes into plain-language root causes with step-by-step actions for technicians or simple self-fixes for tenants when appropriate.

Correlates alarms with sensor data and recent changes
Links to procedures, checklists and spare parts
Alarm explanation agent

Voice AI agent (call automation)

Takes tenant calls, captures the issue, creates a maintenance request and routes routine cases straight to the approved vendor. Critical or high-impact cases escalate to an administrator by policy. Admins see every ticket and can step in at any time.

Call transcripts and audio voice recordings attached to the ticket
Optional after-hours coverage with clear escalation rules
Voice AI agent (call automation)

Tenant communication polisher

Expands short admin notes into clear, professional messages using live work order context and asset history.

On-brand tone, multiple languages, no extra typing
Explains what happened, what is next and the timeline
Reduces back-and-forth and lowers call volume
Tenant communication polisher

Capabilities at a Glance

Anomaly detection across energy, occupancy and runtimes

Central alarm inbox across BMS/HVAC/meters/security

Root-cause narratives with confidence scores

Parts and procedure suggestions by model and history

Predictive schedules based on condition and run hours

Human-in-the-loop controls: suggest-only or auto-act

Access granted automatically based on work orders

Portfolio learning that improves with every fix

FAQs

BMS shows points and alarms. Fentrica explains them, predicts failures, creates tickets with context and access, and keeps a single audit trail.

AI models use history and peer assets to reduce noise and provide confidence scores and evidence.

No. It removes guesswork, prioritises the right work and prepares technicians to fix issues on the first visit.

In most cases no. We connect to what you already run and add the AI layer on top.

Let's talk about your buildings

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