Customer Support

AI-assisted troubleshooting for support engineers

AI-supported troubleshooting toolkits help support engineers resolve issues faster and more independently by surfacing relevant data and guidance without needing to wait on engineering for every case.

Why the human is still essential here

Human agents interpret the issue context, validate AI outputs, watch for hallucinations, and communicate with customers during high-pressure incidents. AI accelerates investigation, but people own the resolution and relationship.

How people use this

Incident root-cause summaries

AI reviews alerts, logs, and telemetry during active incidents to produce a likely root-cause summary that support engineers can validate before taking action.

Datadog Bits AI / Splunk AI Assistant

Natural-language log investigation

Support engineers ask plain-English questions over observability data to quickly isolate failing services, error spikes, or customer-specific issues without deep query expertise.

Splunk AI Assistant / Datadog Bits AI

Guided troubleshooting playbooks

AI recommends the next diagnostic steps and relevant runbooks inside the service workflow so support can work through common incident patterns without waiting on engineering.

Jira Service Management Rovo / Zendesk Copilot

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Personal Story
LinkedIn

Your customers don't want to talk to AI.

Your customers don't want to talk to AI.

When systems are down and the pressure is on, they want to know there's a real person on the other side. Someone who gets it, who can pull in the right people, and who won't tell them to "try asking the chatbot."


I've heard this over and over. And I agree with them.


But here's the thing. The best support teams I've built aren't choosing between humans and AI. They're using AI to make the humans better.


I started in support as one of two people covering 24/7 for a global client base. Every ticket was manual. Every escalation was a phone call. Every piece of tribal knowledge lived in someone's head.


Seven years later, I've led that same function through multiple mergers and acquisitions, platform integrations, and a full operational transformation. I didn't do any of this alone. I had a team that was willing to try new things and push through the growing pains.


We replaced manual NOC monitoring with automated alerting. We used AI-assisted tooling to break down knowledge silos and actually capture what people knew. We gave support engineers their own troubleshooting toolkits so they could resolve issues without waiting on engineering every time.


And we saw it in the results. Resolution times improved quarter over quarter. Support self-solved rates increased, which relieved load on backend engineering resources.


The result wasn't just better metrics. It was a team that could take on harder, more complex work because they weren't buried in the repetitive stuff.


I know the future of support feels scary right now. But the unlock isn't replacing people with AI. It's AI-assisted human agents. People who are hungry to grow, supported by tools that surface the right data at the right time. People who learn to use AI responsibly, who watch for hallucinations, who make sure the output is actually correct.


And the humans? They level up. They build a real foundation for a growing career in our industry.


Let's make it better for future us's.

JA
Jenny AnthonyDirector of Global Support
Apr 23, 2026