Planning & tool calling
Agents that break a goal into steps, call the right tools, and know when a step failed — not a single prompt pretending to be autonomous.
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·AI agents · reference example
Support agents that actually resolve tickets — like Yuma
Yuma is AI support agents that resolve ecommerce tickets. It's a recognisable benchmark for a system class I build — here's what it does, and how I'd build yours.
Reference example — not my client. Yuma is an independent product I'm not affiliated with, shown as a benchmark for this kind of build.
Live preview of www.yuma.ai — their site, shown as reference.
01What a Yuma-class system does
The shape of the build
At its core, Yuma is AI support agents that resolve ecommerce tickets — the kind of system you reach for when you have Shopify, ecommerce support and order-aware agents. Here is how I'd build one for you.
Memory & state
Short and long-term memory so an agent carries context across a task, instead of starting cold every turn.
Human handoff
Clear escalation to a person when confidence drops or the task leaves the agent's remit — designed in, not bolted on.
Safe termination
Budget ceilings, loop detection and stop conditions, so an agent can't quietly run up cost or spin forever.
02More AI agents examples
Other benchmarks in this class
Same system class, different products. Each opens a page like this one.
Want something like Yuma?
Tell me what it needs to do and where it's getting stuck. I'll tell you honestly whether I'm the right person and what it would take — no pitch deck, no discovery call to book a discovery call.