Connect operational performance with environmental accountability.
AI agents that manage assets, find energy losses, collect emissions data and prepare traceable sustainability evidence.
Agents for assets, energy, emissions and reporting.
Expand an agent to see how it works.
Gives field and operations teams what they need to work across distributed assets.
It retrieves asset history, explains alarms from approved documents, prepares diagnostic and service steps, checks safety, parts and skills, and captures field evidence.
Field and operations teams running geographically distributed assets.
Alarm: winding temp high
ExplainedMatched to O&M manual, section 6.2
Works across operational and environmental data.
- Smart meters & utility systems
- SCADA & energy management
- EAM & maintenance
- ERP & procurement
- Carbon-accounting platforms
- Supplier portals
- Weather & forecast data
- Invoices & spreadsheets
- Data warehouses
- Document repositories
Three ways to begin.
GHG Inventory Data Collection
For sustainability-service providers and multi-site organisations.
Utility Anomaly Detection
For businesses with significant energy, water, steam or compressed-air use.
Field-Service Agent
For organisations operating geographically distributed assets.
A pilot should use one reporting boundary, one utility or one asset group with a measurable baseline.
Start with one asset, utility or reporting workflow.
We will define the required data, controls and measurable outcome before building the solution.
Tell us what the work actually looks like.
Share a process that is high-volume, slow or expensive to review. We'll help you identify a strong first AI workflow and how to build it with the right controls.
- We start from your workflow, systems and terminology, not a generic template.
- High-volume, rule-based, expensive-to-review processes make the strongest first project.
- Sensitive actions stay subject to appropriate human review and control.