Questions, Answered

Brick AI is an AI operating platform for energy and physical infrastructure. It connects to existing building, industrial and data center systems, creates a live operational model, and uses AI to reduce energy consumption, unlock capacity and improve reliability.

HVAC, VRF and VRV systems, RTUs, central plant, data center cooling, power infrastructure and other controllable loads, through scheduling, setpoint optimization, load shifting, equipment sequencing and fault correction.

Brick AI targets a 15–30%+ energy reduction opportunity in strong-fit facilities. The achievable figure depends on your baseline, equipment, controllable load and operating constraints, which is why every deployment starts with a scoping review and an agreed baseline rather than a promise.

No. Brick AI is designed to sit above the infrastructure you already run. Most sites need some additional hardware, such as gateways, sensors or submeters, to collect the data the platform needs, but Brick AI does not generally require major equipment replacement to begin creating value.

Brick AI is built for heterogeneous infrastructure and integrates using standard protocols including BACnet/IP, BACnet MSTP, Modbus RTU and TCP, KNX, MQTT and OPC UA, plus vendor-specific pathways where technically feasible. Final scope depends on site equipment, network access and your approvals.

Brick AI can begin in monitoring or advisory mode and move to human-in-the-loop or closed-loop optimization only after your review. Control changes stay inside operating constraints you approve, and fail-safe logic reverts to your existing BMS or BAS on any connectivity, data quality or control risk.

Pricing typically combines an upfront deployment cost, covering gateways, sensors, meters, commissioning and installation support, with a recurring software subscription. For energy optimization the subscription can be aligned to projected or verified savings. For data centers and infrastructure, pricing may be module- or site-based. Utility-sponsored deployments are available in some programs.

Against an agreed baseline, using utility bills, interval meter data, equipment trends and operational data, with normalization for weather, occupancy and production where needed. Independent measurement and verification can be used for grant or utility-backed projects.

Measurement, optimization and reporting are structured to show exactly where outcomes differ from expectations. Remedies depend on contract terms, but the operating model is built on transparency, iterative improvement and keeping your ROI and our subscription aligned.

Brick AI uses an enterprise-minded architecture: controlled connectivity, access management, least-privilege permissions, logging and secure update practices, with specific controls confirmed during your security review. The platform focuses on equipment and facility data and avoids unnecessary personal data collection.

Large energy users and infrastructure operators: data centers, manufacturers, hotels, healthcare facilities, commercial real estate owners, utilities and public-sector facility portfolios.

Yes. Once a facility type is mapped and the controls and measurement approach are validated, the deployment package can be reused across similar buildings, portfolios, utility programs and partner channels.

PermitOS is Brick AI’s permitting automation platform. It maps required permits, agencies, sequencing and dependencies, automates the supporting document workflow, and identifies lawful ways to shorten the path, reducing time-to-power and execution risk on large infrastructure and energy projects.

With one site. A focused scoping review confirms technical fit, then a paid assessment or pilot sets the baseline and defines success metrics before anything is installed. Once savings are quantified, the pilot converts to a recurring subscription and the deployment expands across the portfolio.