Reinforcement learning that keeps your plant stable while driving double-digit savings
ClimaMind pairs an edge appliance with cloud reinforcement learning so mission-critical campuses can cut energy waste without sacrificing uptime. Operators stay in control with full transparency, audit trails, and safety layers.
- Commissioned by controls engineers with BACnet, Modbus, and MQTT integrations out of the box
- Layered guardrails tie back to your native BMS logic and OEM setpoints
- ESG-ready savings verification with alternating-day or historical baselines
Operating envelope snapshot
G60 Innovation Corridor Energy Center
Mixed-use campus
23-building district cooling
10.12% energy savings
Energy Savings
10%–20%
Validated through alternating-day baselines or historical energy data across chillers, pumps, and air handlers.
Deployment Window
10–15 days
Edge appliance installation and BMS integration completed in roughly two weeks before live optimization.
Commercial Models
CapEx / Shared Savings
One-time license or multi-year shared savings agreements with performance guarantees and ongoing support.
Protocol Coverage
BACnet, Modbus, MQTT
Works alongside existing BMS infrastructure with layered safety boundaries and operator override.
Healthcare Campuses
Data Center Operators
Commercial Portfolios
Hospitality Portfolios
Energy InfrastructureBuilt for operators who manage critical environments
Every engagement follows a repeatable playbook, with our engineering team validating savings and safety at each step.
- 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
Industry playbooks ready for deployment
From data centers to multi-site healthcare networks and hospitality portfolios, our delivery pods wrap strategy, controls, and measurement into a single accountable team.
Hospitality & Resorts
Keep 24/7 guest experiences consistent while extracting efficiency from hotel and resort central plants.
Primary challenges
- Occupancy swings across weekdays, events, and amenities drive constant schedule overrides
- Hot water and chilled water systems operate in silos without shared comfort KPIs
- Corporate sustainability teams need auditable portfolio reporting to justify retrofits
Solution highlights
- Reinforcement learning aligns comfort, indoor air quality, and energy KPIs across guestrooms, ballrooms, and wellness amenities
- Occupancy-aware sequencing automates chillers, boilers, and thermal storage dispatch
- Portfolio dashboards provide verified savings artifacts ready for ESG disclosure
Recommended engagement
CapEx or Shared Savings: select the structure that fits your portfolio
Works for flagship hotels as well as franchise portfolios rolling out shared savings programs.
Commercial & Mixed-Use Towers
Coordinate premium offices, retail podiums, and mixed-use campuses under one repeatable playbook.
Primary challenges
- Multiple asset types share a central plant but require different comfort envelopes and schedules
- Tariff windows and ice storage assets stay underutilized without predictive dispatch
- Operators lack a unified way to retune pumps, towers, and air handlers as tenants change
Solution highlights
- Reinforcement learning co-optimizes chillers, pumps, towers, and airside equipment within comfort guardrails
- Tariff-aware forecasting orchestrates thermal storage and demand response participation
- Lifecycle reporting links verified savings to leasing, ESG, and asset valuation goals
Recommended engagement
CapEx or Shared Savings: select the structure that fits your portfolio
Ideal for mixed-use REITs and asset managers modernizing multiple landmark properties.
Transportation Hubs
Safeguard mission-critical passenger comfort while controlling the energy footprint of airports and rail hubs.
Primary challenges
- Passenger peaks and overnight lows swing loads far beyond manual playbooks
- Large AHU and PAU fleets with parallel chillers lack closed-loop coordination
- Safety teams require explicit guardrails before approving automated adjustments
Solution highlights
- Theory-of-mind reinforcement learning stabilizes plant staging across chillers, pumps, towers, and air-handling fleets
- Digital twins maintain hydraulic and temperature-field visibility for operations and safety audits
- Layered protections preserve manual override paths and real-time compliance evidence
Recommended engagement
CapEx or Shared Savings: select the structure that fits your portfolio
Best for airport or railway authorities seeking verified savings without disrupting live operations.
Healthcare Networks
Maintain clinical reliability while unlocking savings across hospital campuses and medical networks.
Primary challenges
- Critical care spaces demand precise pressurization and humidity limits year-round
- Legacy BMS logic cannot coordinate isolation wards, labs, and public areas simultaneously
- Facilities teams need audit-ready evidence to satisfy compliance and finance stakeholders
Solution highlights
- Reinforcement learning keeps surgical suites, wards, and labs within comfort and infection-control envelopes
- Dynamic zoning recommendations tie central plant settings to downstream air systems
- Alternating-day validation produces documentation accepted by hospital governance
Recommended engagement
CapEx or Shared Savings: select the structure that fits your portfolio
Suitable for flagship hospitals or syndicated healthcare portfolios phasing deployments.
Industrial Manufacturing
Balance process stability and energy efficiency for pharmaceutical, PV, and advanced manufacturing sites.
Primary challenges
- Process cooling loads shift with batch schedules and production changeovers
- High-spec cleanrooms and dry rooms require coordination between process and comfort systems
- Limited predictive insight into energy cost drivers constrains continuous improvement programs
Solution highlights
- Reinforcement learning harmonizes process and comfort cooling while preserving strict temperature tolerances
- Energy diagnostics highlight deviations by line, shift, and utility tariff
- Edge deployment keeps control autonomy even when corporate networks segment traffic
Recommended engagement
Shared Savings: multi-year partnership funded by realized savings
Ideal for manufacturers pursuing low-carbon KPIs without risking throughput.
Public & Exhibition Venues
Keep year-round visitor experiences consistent across museums, expo centers, and civic facilities.
Primary challenges
- Seasonal events and uneven occupancy cause over-conditioning and manual overrides
- Temporary installations disrupt airflow balance and central plant scheduling
- Budget owners require transparent payback narratives for public funding approvals
Solution highlights
- Reinforcement learning schedules chillers, air handlers, and dehumidification to follow exhibition comfort setpoints
- Scenario planning tools adapt strategies to event calendars and maintenance windows
- Verified reporting supports grant applications and public accountability requirements
Recommended engagement
CapEx or Shared Savings: select the structure that fits your portfolio
Supports government agencies and venue operators seeking visible, auditable sustainability wins.
Infrastructure & Energy Hubs
Orchestrate district energy centers and campus utilities serving multi-building portfolios.
Primary challenges
- Hybrid heating and cooling networks need seasonal playbooks that outpace manual tuning
- No shared KPI links central plant assets, storage, and downstream comfort outcomes
- Tariff and fuel volatility demands optimization across multiple energy streams
Solution highlights
- Single optimization layer covers chillers, heat pumps, boilers, storage, and distribution
- Reinforcement learning targets efficiency, resilience, and energy cost with tariff awareness
- Actionable reporting informs capital planning and daily dispatch decisions
Recommended engagement
Shared Savings: multi-year partnership funded by realized savings
Fits multi-stakeholder campuses or PPP projects where shared savings fund integration.
Data Centers
Optimize mission-critical cooling infrastructure to drive lower PUE while respecting strict reliability requirements.
Primary challenges
- Tight thermal tolerances require traceable safeguards on every control action
- Tower, pump, and CRAH coordination is complex and often reactive to weather swings
- Operators lack automated runbook recommendations for staging and frequency control
Solution highlights
- Closed-loop optimization of CRAH discharge temperatures and chilled water flow
- Operator-selectable auto-execute or approval workflows for equipment staging
- UPS-backed edge platform maintains control continuity during power events
Recommended engagement
CapEx: upfront investment with contractual performance guarantees
Ideal for capital projects seeking measurable PUE improvements backed by performance guarantees.
Technology engineered for safety and scale
Our architecture combines reinforcement learning, deterministic guardrails, and observable operations to keep staff in control while the system optimizes.
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.
Three pillars we bring to every project
Strategic reinforcement learning, operator-focused safety, and rapid delivery are the foundation of every ClimaMind deployment.
Full-plant reinforcement learning
Orchestrates chillers, pumps, cooling towers, and air handlers as one adaptive system tuned to your comfort and reliability envelope.
- Learns live plant behavior with built-in guardrails
- Balances comfort, load, and energy KPIs in real time
- Transfers learnings across sites without re-coding
Operations-grade safety
Layered controls respect OEM limits, ASHRAE/NFPA guidelines, and your existing BMS hand-off procedures.
- Transparent policy approvals and audit trail
- Automatic fallback to native sequences on anomaly
- Site-resident edge appliance with UPS coverage
Accelerated deployment
Dedicated delivery team lands production-grade results in weeks—not quarters—without extensive sensor retrofits.
- Standardized intake, data cleansing, and commissioning
- Integrations for BACnet, Modbus, MQTT, and enterprise APIs
- CapEx or shared-savings commercial structures spanning campuses and hospitality portfolios
From pilot to portfolio in under a quarter
ClimaMind scales from a single plant to entire portfolios with templated integrations, shared safety libraries, and operator-first tooling.
Healthcare Network Energy Program
Cooling plants across three hospitals modernized without disrupting patient care operations.
- Verified savings
- 14%
- Deployment time
- 12 days
- Strategy updates
- Auto every 15 min
Alternating-day testing keeps savings auditable for ESG disclosure, while the clinical engineering team maintained full override control—playbooks now extend to hospitality portfolios with similar comfort-critical constraints.
Mission outcomes
- RL policies operate within OEM limits and linked safety guardrails.
- Operators approve policy updates and maintain full transparency over decisions and setpoints.
- Alternating-day measurement provides auditable results for executive sponsors and ESG teams.
Technical and commercial FAQs answered
Bring your controls, operations, and finance teams together—these responses cover the conversations that matter most.
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.
Commercial
How do the CapEx and shared savings models differ?
CapEx projects include a perpetual license for the edge platform with optional service agreements. Shared savings engagements are 5–8 year partnerships where ClimaMind funds the deployment and is paid from verified energy reductions.
Commercial
How are savings calculated and validated?
We prioritize alternating-day comparisons—AI control one day, native control the next—using utility metering or plant power data. Where historical data is reliable, we also offer multi-year baseline models to satisfy ESG reporting requirements.
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.