01
Prepare a clearer incident picture.
Bring authorised telemetry, asset records and work orders together for human assessment.
Phrony / AI agents for
Energy & utilities.
Clarity for your team. Across every system.
Give teams a clearer view of incidents, field-service needs and customer questions. Agents prepare the context while operational technology stays outside their write access.
Self-host Phrony on your infrastructure.
Outages. Field service. Customer care.
Estimate your ROITurn scattered context into a clearer next step.
A shared runtime for the work that matters. Start with one agent and measure what changes.
02
Support field and service teams.
Prepare dispatch recommendations, billing explanations and reporting materials.
03
Keep a clear IT / OT boundary.
Read-only operational context. IT-side coordination. No grid balancing, switching or SCADA writes.
Watch an example
Agents for the work around your infrastructure.
Choose an agent. Follow the request, each step, then the result. Some examples finish a useful draft. Others pause for a person to review.
Choose an example
The request
Why did my electricity bill increase this month?
- Read billing inputs
- Compare the change
- Prepare the explanation
Run the example to see the agent work through this request.
Illustrative run with sample data. No live systems are connected.
Make the business case
Less manual work. What is it worth?
Use your own workload and costs to explore an agent’s potential value. Start with one responsibility you know well.
Potential capacity freed / month
167 hours
Today400 h
With an agent233 h
- Net value, year one
- €38,500
- ROI, year one
- 122%
- Simple payback
- 2 months
Modelled staff capacity value, not guaranteed cash savings. Validate handling time and quality with your own agent.
How the estimate works
Hours freed per month = cases × (current human minutes − future human minutes) ÷ 60. Annual capacity value = hours freed × hourly cost × 12. Year-one net value subtracts 12 months of running costs and one-time implementation. ROI divides net value by those total costs. Simple payback divides implementation cost by monthly capacity value after running costs. The model assumes a full year at the selected volume after launch and excludes ramp-up, taxes and financing. Negative time savings remain negative; payback is not reached when monthly net value is zero or below.
Governance for production agents
EU AI Act readiness
As agents take more consequential actions, control and evidence become part of the product.
- 01Reviewable definitions
Make an agent’s purpose, tools and boundaries explicit.
- 02Human checkpoints
Require approval for designated tool actions.
- 03Execution records
Keep a record of runs for investigation and review.
These controls support compliance work. EU AI Act compliance depends on the complete system, use case and your role; a runtime alone does not establish it.
And in the US?
Requirements vary by state and sector. Texas’s TRAIGA is one applicable AI law. The NIST AI Risk Management Framework is voluntary guidance, not a law or certification. Map obligations to your own deployment.
These examples are just the start
Your ideas. The sky’s the limit.
Customer-facing or behind the scenes: build an agent around the job your business needs done. Connect your tools, define its boundaries and self-host the runtime.