01
Reduce repetitive service work.
Let agents investigate order questions and prepare resolutions from your store data.
Phrony / AI agents for
Retail & ecommerce.
Make every interaction move the customer forward.
Help customers with orders, returns and product questions. Connect agents to your store and define when they can act—and when your team needs to approve.
Self-host Phrony on your infrastructure.
Orders. Returns. Product discovery.
Estimate your ROIHelp customers move. Keep your team focused.
A shared runtime for the work that matters. Start with one agent and measure what changes.
02
Make buying and returning easier.
Give customers relevant product answers and clear next steps on returns.
03
Keep commercial rules in control.
Define supported action limits and approval points for refunds, offers and purchasing.
Watch an example
Agents for the moments that shape the experience.
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
My order says delivered, but I have not received it.
- Retrieve the order
- Investigate the delivery
- Prepare the resolution
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
150 hours
Today400 h
With an agent250 h
- Net value, year one
- €22,500
- ROI, year one
- 71%
- Simple payback
- 3 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.