The Agentic Lab

The institutional engine for converting decades of infrastructure expertise into autonomous, scalable AI agents. From experimentation to production autonomy in 8–12 weeks.

Bridge the Gap Between Vision and Deployed Autonomy

Most organizations understand the potential. The challenge is getting from experiments to production-grade autonomy.

  • Tools and infrastructure for designing agent systems
  • Domain expertise in buildings + AI engineering
  • Structured path from experimentation to transformation
Agentic Lab — digital twin design, simulation, and deployment workstation

How Expertise Becomes Autonomous Intelligence

Knowledge Acquisition

Parse textbooks, manufacturer docs, ASHRAE/IEEE/ISO standards, and decades of field data into structured ontologies.

Agent Training

Supervised learning, reinforcement learning, and transfer learning using real building data and simulated environments.

Certification

Rigorous testing against safety, performance, and compliance benchmarks before any agent goes live.

Deployment

Progressive activation from single-system to multi-agent orchestration across entire portfolios.

Continuous Learning

Agents improve from every decision. Experience data refines models across the entire fleet.

How the Lab Gets You There

1

Design

Define objectives. Connect to building data. Auto-generate digital twin. Configure agent goals, policies, and guardrails.

2

Simulate

Test disruption scenarios. Refine agent behaviors. Validate metrics against your success criteria in a safe digital twin environment.

3

Deploy

Go live with supervised autonomy. Monitor via Agent Observatory. Tune, expand, and define the path to full autonomy.

Built for Enterprise Complexity

Building Owners & Operators

Managing portfolios of commercial, institutional, or industrial properties.

System Integrators

Designing next-generation solutions for clients.

Energy Utilities & Cities

Building-to-grid coordination and cross-system management.

Three Categories of Transformation

1

Re-designing Processes

Map workflows across strategy, execution, and operations. Identify where agents create the most impact.

2

Re-thinking Governance

Define agent archetypes, capabilities, and escalation paths — similar to workforce roles.

3

Scalable AI Infrastructure

Complex agent ecosystems that scale safely with shared context and centralized governance.

What You Walk Away With

Deployed System

Governed agents running on GAOS

Validated Data

Energy, efficiency, cost metrics

Autonomy Roadmap

Clear milestones at every stage

Trained Team

Equipped to expand deployments

“We entered the Lab with 200 buildings and a vague sense that AI could help. Eight weeks later, energy agents were deployed across all sites. First-quarter savings covered the entire engagement cost.”

Lab Engagement — Commercial Portfolio
200 buildings · 8-week deployment · Full ROI in Q1

*Illustrative deployment based on validated simulation results.

Expert Engineering at a Fraction of the Cost

Adjust the inputs below to see projected annual savings with autonomous agents across your portfolio.

125500
$20K$120,000$500K
Annual savings, broken down
Energy (30%)
$900,000
Autonomous HVAC + load balancing
Downtime avoided
$300,000
Predictive maintenance catching failures
Maintenance (10%)
$300,000
Workforce + parts optimization
Agent cost
−$37,500
Subscription + licensing
Net annual savings
$1.46M
39x return on agent spend
5-year projection
$7.31M
Cumulative across portfolio
Estimates based on industry benchmarks (DOE, ASHRAE) for commercial buildings. Actual savings depend on building type, climate, and operational baseline. Talk to us for a tailored projection.

Sign up for early access

Infrastructure AI's Galaxy Agentic Operating System (GAOS) will soon be available for Public Beta.

Galaxy Agent
Online

Want to see autonomous agents run a building in real time?

Launch our interactive demo — no signup required.

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