Solution architecture
Three layers. One operating memory.
AiBE is structured around the three jobs facilities teams repeat every day: retrieving knowledge, operating across systems, and serving occupants without losing context.
Each module maps to a real operating job.
AiBE is not three random product names. The stack is arranged around how facilities teams actually retrieve knowledge, operate the estate, and support occupants.
Scholar turns building knowledge into a working memory layer.
Use Scholar when the job starts with manuals, SOPs, prior incidents, or technical know-how that is currently trapped in folders and people.
- Retrieve manuals, SOPs, and service history in plain English.
- Preserve troubleshooting memory when senior engineers leave or change shifts.
- Shorten onboarding time for technicians and FM teams.
Source base
Manuals, O&M files, certificates, service notes, and prior incident records.
Good fit
Troubleshooting, knowledge retention, and technical onboarding.
Output
Faster answers with source-backed context instead of guesswork.
Operator helps teams work across the live estate faster.
Use Operator when the question depends on live systems, telemetry, work orders, shift context, or the next operational action.
- Pull BMS, CMMS, telemetry, and asset history into one operating thread.
- Brief engineers faster with the right site, fault, and service context.
- Support alert handling, escalation, and handover continuity.
Connects above
BMS, CMMS, EMS, IoT telemetry, work orders, and service history.
Good fit
Fault triage, shift briefings, and cross-system retrieval.
Output
A clearer shared operating view instead of five partial ones.
Dweller handles occupant and front-line service without losing site context.
Use Dweller when requests like air-con extension, bookings, or common facility asks need a cleaner front-line path.
- Guide occupant and tenant requests through a cleaner intake flow.
- Keep rules, approvals, and service routing tied to the same operating context.
- Reduce friction between front-line service and engineering teams.
Front line
Air-con extension, tenant requests, bookings, and guided service asks.
Good fit
Hospitality, mixed-use estates, managing agents, and service desks.
Output
Cleaner occupant service without fragmenting the workflow underneath.
How the modules work together in a real building flow.
Most buyers do not want a generic AI box. They want a faster route from question to answer to action.
A question starts the flow
The trigger could be a fault, a certificate risk, a tenant request, or a technical question.
AiBE retrieves context
Scholar and Operator pull the relevant manuals, telemetry, site history, and service notes.
The right team is briefed
The engineer, operator, or front-line user gets the next useful step with less manual chasing.
Action is recorded and inherited
The next shift or next request starts warmer because the operating memory is preserved.
Why this structure lands with buyers.
Each module answers a different buyer concern without forcing them to understand the whole stack on day one.
Procurement teams
They get a clearer story around deployment posture, systems fit, and where the first use case should start.
Operations leaders
They see how knowledge, telemetry, and workflow coordination fit together without interface sprawl.
Head technicians
They get faster access to manuals, incident history, and the operational context behind the next decision.
Occupant-facing teams
They get a cleaner service layer for common requests without breaking the engineering operating loop.
See which layer fits your estate first.
The first conversation does not need to cover everything. It just needs to start with the highest-friction workflow in your building stack.
Frequently asked questions
What makes AiBE different from a generic AI chatbot?
AiBE is framed around facilities workflows and operational memory, not a generic prompt box. It is meant to sit on top of real FM systems and knowledge sources.
Do buyers need all three modules from day one?
No. We recommend starting with one clear use case, one team, or one building workflow first. The three-layer structure is there so expansion stays coherent later.
