End-to-end delivery framework
From discovery through continuous optimization, our engineering team gives operators a clear path to measurable savings.
- 1
Discovery & Data Intake
Capture system schematics, equipment inventory, load profiles, and point lists to define AI integration boundaries.
- Standardized HVAC assessment checklist
- Point map, network topology, and protocol alignment
- Target KPI definition and measurement methodology
- 2
Edge Deployment & Integration
Install the ClimaMind edge appliance, integrate with the existing BMS, and configure layered safety guardrails.
- Edge server and resilient power setup
- Communication testing and point binding
- Safety limits and operator approval workflows
- 3
Reinforcement Learning Activation
Launch adaptive policies across chillers, cooling towers, pumps, and air handlers for whole-plant optimization.
- Live control across the chiller plant
- Policy iteration logs and performance metrics
- Real-time anomaly detection and alerting
- 4
Measurement & Continuous Value
Quantify savings via alternating-day comparisons or historical baselines and deliver ongoing optimization insights.
- Savings verification package
- Operations playbook and tuning cadence
- CapEx or shared savings contract scorecard
Technology capability matrix
Reinforcement learning, plant-wide orchestration, and safety engineering designed for critical environments.
Plant-Wide Reinforcement Learning
Aggregates live telemetry, historical performance, and weather feeds to continuously seek the global efficiency optimum.
Layered Safety Architecture
Multi-tier limits and rate controls ensure every command stays within OEM specifications, with instant fallback to the existing BMS.
Low-Impact Implementation
Leverages existing instrumentation with minimal retrofit work, reaching production readiness in just a few weeks.
Flexible Commercial Engagements
Supports traditional capital projects or shared savings structures with contractual performance guarantees.
Technical FAQs
A closer look at the engineering questions we hear most often during enterprise evaluations.
Technical
Does the AI layer compromise the stability of the existing BMS or plant control?
ClimaMind runs in parallel with your BMS. Every command is constrained by multi-level safety limits and rate-of-change policies. If telemetry is out of bounds, the system reverts to the native sequence, and operators retain manual override at all times.
Technical
Do we need new sensors or significant hardware retrofits?
Most deployments reuse existing plant instrumentation—supply/return temperatures, flow, and power meters. We add a hardened edge server with UPS backup and networking gear but avoid intrusive sensor retrofits whenever possible.
Technical
How long before energy savings are measurable?
We enable reinforcement learning immediately after commissioning. Within 1–2 weeks we stabilize policy updates, and a 30-day alternating-day test or historical baseline comparison produces auditable savings results.
Technical
Can the platform run in the cloud?
Yes. ClimaMind can operate fully on-premises via the edge appliance or integrate with a secure cloud environment. Commissioning typically uses an isolated network segment with firewall rules that align to your cybersecurity policies.