They delivered a reliable AI agent that executed real workflows and measurably reduced ops effort.
We also tracked end-to-end resolution versus escalation and saw steady improvement as workflows were added and refined. On the operations side, action success rate became a reliable metric since every tool call was logged, showing what worked, what failed, and where policies needed adjustment. Even when escalation was required, cases arrived with full context and a clear audit trail, making them faster to resolve.
What was the project name that you have worked with Highpolar Software?
AI Agent Development for a retail and fulfillment business.
What service was provided as part of the project?
Mobile App Development, Cloud Computing Services, Artificial Intelligence
Describe your project in brief
The work covered building an AI Operations Agent that could sit inside our support inbox and internal chat and actually get things done, not just answer questions. Highpolar started by mapping our highest volume workflows and the policies behind them, then designed the agent so it could understand what someone was asking, decide the right next step, and complete the task through approved actions.
They delivered the core agent behavior, the integrations to our order management, returns, and logistics tools, and the backend services needed to make those actions reliable. They also added safeguards like permissions and rule checks so the agent could not take shortcuts, plus logging and traceability so we could always see what it tried to do and what it actually executed. We went live in phases, beginning with a pilot for the most common requests, and then expanding coverage and hardening it for day to day production use.
What is it about the company that you appreciate the most?
That focus on safe execution was a big differentiator for us. You could see they were thinking about permissions, policy rules, and traceability from day one, which is exactly what you need when an AI system is allowed to touch real orders, refunds, and customer accounts. They were very deliberate about making the agent useful in the real world, so it could understand what someone wanted and then complete the task through controlled actions rather than just sounding confident.
What was it about the company that you didn't like which they should do better?
Nothing major. If we had one suggestion, it would be a short enablement session a bit earlier so our team could take ownership faster once the pilot was live.
Rating Breakdown
- Quality
- Schedule & Timing
- Communication
- Overall Rating
Project Detail
- $10001 to $50000
- Completed
- Retail