Autonomous BMS for AI Data Centers

AIMI replaces legacy, rule-based building management with autonomous control of cooling and facility systems—improving efficiency, reliability, and grid responsiveness without new hardware.

Schedule a Demo

Autonomous BMS in Practice

Legacy building management systems rely on static rules and manual tuning, making it difficult to maintain efficiency and reliability as data center conditions change.

AIMI replaces rule-based control with autonomous decision-making. It continuously coordinates cooling, airflow, and facility systems as a unified control layer—optimizing energy efficiency, maintaining SLA constraints, and adapting in real time without operator intervention.

Legacy building management systems rely on static rules and manual tuning, making it difficult to maintain efficiency and reliability as data center conditions change.

AIMI replaces rule-based control with autonomous decision-making. It continuously coordinates cooling, airflow, and facility systems as a unified control layer—optimizing energy efficiency, maintaining SLA constraints, and adapting in real time without operator intervention.

Legacy building management systems rely on static rules and manual tuning, making it difficult to maintain efficiency and reliability as data center conditions change.

AIMI replaces rule-based control with autonomous decision-making. It continuously coordinates cooling, airflow, and facility systems as a unified control layer—optimizing energy efficiency, maintaining SLA constraints, and adapting in real time without operator intervention.

Watch How The Autonomous BMS Works

How Autonomous BMS Works
Three AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

Reducing power usage effectiveness (PUE) in data centers

Autonomous Control

Autonomous control of cooling and facility systems

AIMI continuously optimizes cooling and facility operations in real time, adapting to changing load, thermal conditions, and operational constraints without manual intervention or additional hardware.

30–40% autonomous energy efficiency improvement
No extra hardware required
Autonomous Demand Response to curtail load per utility requirements
Stay online during grid events while reducing facility load
Save energy to unlock stranded capacity and increase revenue per site

AI Heat Map

AI-driven thermal visibility and recommendations

AIMI generates real-time AI heat maps that reveal airflow inefficiencies and thermal risk, with clear recommendations for tile flow and equipment placement.

AI-recommended tile airflow and equipment setup
30-40 hours per month saved in manual analysis and tuning
50% reduction in SLA excursion risk
Continuous optimization as conditions change

On-Premise & Air-Gapped

Security-first by design
AIMI is built for security-critical data center environments, operating fully on-premise and air-gapped with no dependency on external cloud connectivity.

On-premise, air-gapped deployment
SOC 2 compliant
Failsafe-tested in live environments
Zero operational excursions across active deployments

Relevant Case studies

U.S. AI Factory reduced cooling load by ~10% during a grid event

AIMI autonomously curtailed HVAC load in response to grid stress while maintaining operational constraints and uptime. Cooling demand was reduced in real time without manual intervention, demonstrating safe autonomous control during live grid events.

LATAM colo operator unlocked ~15% stranded capacity

By autonomously optimizing cooling and facility operations, AIMI reduced baseline energy consumption and recovered unused headroom. The resulting efficiency gains translated directly into increased usable capacity without physical expansion.

AIMI BMS, Explained

This demo shows AIMI autonomously controlling a live lab environment. Watch how the system optimizes cooling and facility operations in real time—maintaining operational constraints while delivering measurable energy savings without manual intervention.

Talk to the AIMI BMS Team

Get a quick response from our team on deployment fit, requirements, and next steps.

Talk to the AIMI BMS Team

Get a quick response from our team on deployment fit, requirements, and next steps.

Schedule a Demo

Autonomous BMS in Practice

Autonomous BMS in Practice

Autonomous BMS in Practice

Legacy building management systems rely on static rules and manual tuning, making it difficult to maintain efficiency and reliability as data center conditions change.

AIMI replaces rule-based control with autonomous decision-making. It continuously coordinates cooling, airflow, and facility systems as a unified control layer—optimizing energy efficiency, maintaining SLA constraints, and adapting in real time without operator intervention.

Legacy building management systems rely on static rules and manual tuning, making it difficult to maintain efficiency and reliability as data center conditions change.

AIMI replaces rule-based control with autonomous decision-making. It continuously coordinates cooling, airflow, and facility systems as a unified control layer—optimizing energy efficiency, maintaining SLA constraints, and adapting in real time without operator intervention.

Legacy building management systems rely on static rules and manual tuning, making it difficult to maintain efficiency and reliability as data center conditions change.

AIMI replaces rule-based control with autonomous decision-making. It continuously coordinates cooling, airflow, and facility systems as a unified control layer—optimizing energy efficiency, maintaining SLA constraints, and adapting in real time without operator intervention.

How Autonomous BMS WorksThree AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

How Autonomous BMS WorksThree AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

How Autonomous BMS WorksThree AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

Autonomous Control

Autonomous control of cooling and facility systems

AIMI continuously optimizes cooling and facility operations in real time, adapting to changing load, thermal conditions, and operational constraints without manual intervention or additional hardware.

30–40% autonomous energy efficiency improvement

No extra hardware required

Autonomous Demand Response to curtail load per utility requirements

Stay online during grid events while reducing facility load

Save energy to unlock stranded capacity and increase revenue per site

AI Heat Map

AI-driven thermal visibility and recommendations

AIMI generates real-time AI heat maps that reveal airflow inefficiencies and thermal risk, with clear recommendations for tile flow and equipment placement.

AI-recommended tile airflow and equipment setup

30-40 hours per month saved in manual analysis and tuning

50% reduction in SLA excursion risk

Continuous optimization as conditions change

On-Premise & Air-Gapped

Security-first by designAIMI is built for security-critical data center environments, operating fully on-premise and air-gapped with no dependency on external cloud connectivity.

On-premise, air-gapped deployment

SOC 2 compliant

Failsafe-tested in live environments

Zero operational excursions across active deployments

Relevant Case studies

Relevant Case studies

Relevant Case studies

U.S. AI Factory reduced cooling load by ~10% during a grid event

U.S. AI Factory reduced cooling load by ~10% during a grid event

LATAM colo operator unlocked ~15% stranded capacity

AIMI BMS, Explained

AIMI BMS, Explained

This demo shows AIMI autonomously controlling a live lab environment. Watch how the system optimizes cooling and facility operations in real time—maintaining operational constraints while delivering measurable energy savings without manual intervention.

This demo shows AIMI autonomously controlling a live lab environment. Watch how the system optimizes cooling and facility operations in real time—maintaining operational constraints while delivering measurable energy savings without manual intervention.

Get a quick response from our team on deployment fit, requirements, and next steps.

Get a quick response from our team on deployment fit, requirements, and next steps.

Talk to the AIMI BMS Team

Get a quick response from our team on deployment fit, requirements, and next steps.

How Autonomous BMS Works
Three AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

How Autonomous BMS Works
Three AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

How Autonomous BMS Works
Three AI-driven control capabilities operate continuously to optimize efficiency, reliability, and grid responsiveness.

Security-first by design
AIMI is built for security-critical data center environments, operating fully on-premise and air-gapped with no dependency on external cloud connectivity.