Technical Support Data is the New Oil

After deploying RunLLM’s AI Support Engineer across 50+ user bases, we’ve consistently seen user interaction increase — sometimes by as much as 10X. When users realize they can get instant, high-quality answers from trusted AI that actually works — and won’t judge them for asking even simple questions — engagement jumps.

That engagement generates a wealth of insights, revealing how users interact with your product — what they’re trying to do, where they succeed, and where they get stuck. It also highlights the other technologies they use alongside your product, where you fit in the ecosystem, and even new opportunities for your roadmap.

But like crude oil, raw data isn’t immediately useful — it needs refining. Imagine getting 5,000 support questions a week like some of our customers do. Without structure, that data would be overwhelming. At best, your support team might scan a handful of tickets and extract anecdotal insights — but that’s not enough to drive real decisions.

Technical support data is the new oil.

Data That Drives Customer Insights

With the volume of data that RunLLM gathers, the natural starting point is for us to help you understand what’s happening across all those conversations.

We believe that every technical support question is more than just a request for help. It highlights user needs, product friction, and areas for improvement. Until now, those signals were hard to capture. Customers avoid asking “silly” questions, forcing companies to rely on indirect product metrics, or wait until issues become serious enough to trigger complaints.

RunLLM changes that.

By tracking every customer conversation and applying advanced topic modeling, we uncover recurring themes, emerging trends, and real-world use cases hidden in technical support interactions.

These topics provide the foundation from which to ask even more valuable questions about your customers. Once you know what users are focused on, you can start learning which parts of your product your customers are happy and unhappy with. You can ask if customers are asking for features that you haven’t yet built or offered. Moreover, this framework is the foundation for gathering even more useful feedback. For example, once you know users are frustrated with a particular feature, you can guide RunLLM to ask those users for specific feedback that will help you improve that feature.

Data That Improves Documentation

Maintaining accurate documentation is one of the hardest challenges for any technical product company. Without extremely careful management, it inevitably becomes outdated and unwieldy. Traditionally, teams had to rely on direct user feedback or manual audits to find issues in their knowledge bases — an inefficient and reactive process that never ends.

Because RunLLM answers so many user questions, it constantly references your documentation — giving it a unique ability to detect and flag gaps, inconsistencies, and outdated content.

With RunLLM, documentation issues are automatically identified for you.

• If users repeatedly struggle to find certain answers, or if AI responses lack confidence, RunLLM flags these issues automatically.
• If documentation is inconsistent, RunLLM detects and surfaces conflicts for review. If a feature is described differently in two places, it asks: “Which is correct?”
• As your product changes, RunLLM can proactively suggest documentation updates to make sure your customers have the latest information.

RunLLM thrives on accurate information — so it’s in our best interest to keep your documentation up to date. The result? A virtuous cycle where AI-powered support improves both user experience and documentation quality.

Advanced Insights Video Walk Through

Want to see these features in action? Our CEO, Vikram, walks through how RunLLM:

• Surfaces product insights from customer interactions.
• Automatically detects documentation gaps and suggests updates.
• Transforms raw support conversations into structured, actionable data.

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Data That Builds Businesses

An AI Support Engineer does more than just answer questions — it turns every interaction into an opportunity to improve your product, refine documentation, and enhance customer experience. Customers get instant, high-quality answers, while you gain continuous insights that help reduce friction, prioritize improvements, and build a stronger business.

And this is just the beginning. We’re working on automating bug detection, identifying onboarding challenges, and even predicting customer issues before they arise.

By making support data visible and actionable, we’re helping teams move from reactive troubleshooting to proactive problem-solving.

RunLLM transforms technical support data into business intelligence. Start unlocking insights today. Try it for free at runllm.com.