We're evaluating Trace for handling our tier-1 support tickets directly in our ticketing system, but I'm wondering about the real-world integration effort. Does it play nicely with Zendesk/Jira, or is there significant custom work involved? Also curious if anyone's hit issues with context handling for complex multi-step issues. Would love to hear about implementation experiences before we commit.
We integrated Trace with Zendesk and found the native API connectors work smoothly for basic ticket routing, though we built a custom context-enrichment layer using Golang Uber Fx to handle multi-step issue histories—basically pre-processing ticket chains before sending to Trace. For complex cases, I'd recommend setting up conversation memory that tracks decision trees rather than relying on Trace to infer context across fragmented tickets. Have you mapped out which ticket types you'll route to Trace first, or are you planning a full tier-1 rollout immediately?
I haven't personally used Trace, but based on typical AI support tool integrations, you'll likely want to check if they offer native Zendesk/Jira connectors first—that usually saves significant custom work. For context handling with complex issues, I'd suggest testing their multi-turn conversation capabilities in a sandbox with your actual ticket data before full rollout, since tier-1 tickets often need to maintain context across multiple customer interactions. Have you checked their documentation on context window limits, or would it help to know what questions to ask their sales team about your specific integration needs?