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The AI Technical Support Experience Customers Deserve
Yesterday, we announced the public beta of our AI Support Engineer — specifically for advanced technical support. Designed from a decade of academic research and real-world deployment, RunLLM delivers high-quality, fast, and scalable support for technical teams.
Great support isn’t just about responding. It’s about making sure users solve their problems. The best support engineers don’t just react — they anticipate, guide, and adapt.Scaling that level of expertise is tough, even for the best human teams. RunLLM gives every technical team a seasoned support engineer, working at AI speed.
Unlike generic AI tools that treat support as simple Q&A, RunLLM reasons through problems, explores multiple solutions, and improves with every interaction. Over the past six months, we’ve studied how top support engineers operate and embedded their expertise into RunLLM — so it doesn’t just provide answers, it actively solves problems.
This week, we’re rolling out a revamped experience that takes AI-powered support further than ever before. Stay tuned as we highlight the key features that make RunLLM the most capable AI support solution today.
AI That's Smarter
We’ve redesigned RunLLM’s support experience, making it feel more like a real Support Engineer — one that doesn’t just provide answers but actively solves problems and learns from every interaction.
Key features include:
Instant Learning: If RunLLM gets an answer wrong, you can correct it on the spot. When new information contradicts what it previously learned, it flags the discrepancy — allowing you to update its knowledge while seeing why it responded the way it did. Once RunLLM learns something new, it automatically updates its responses and won’t need to be taught again.
Adaptive Confidence & Guidance: Not all answers are black and white. When confident, RunLLM responds directly. When uncertain, it adjusts its tone, flags gaps, and cites sources to ensure transparency. If it can’t find an answer, RunLLM automatically escalates the question to human support — creating a Slack thread where agents can review, refine, and approve a response. With a single click, the answer is sent back to the user, and RunLLM learns from the interaction, so it won’t need to ask again.
Rich Inputs: Upload screenshots, logs, or error messages — RunLLM extracts relevant details and provides troubleshooting insights. No need to copy-paste every stack trace or error message. Just drop in a screenshot from Stack Overflow (or anywhere else) and ask, “What is this?” — RunLLM automatically analyzes the content and generates a response.
RunLLM Feature - Rich Inputs
AI That Cares
Great support isn’t just about responding — it’s about making sure users actually solve their problems. RunLLM doesn’t just react — it anticipates. During a support engagement, it takes additional steps between user questions, refining its search for the most relevant information.
Alternative Solutions: Technical issues rarely have just one fix. After providing an initial answer, RunLLM proactively searches its knowledge base for alternative solutions — whether it's a workaround, best practice, or edge-case fix. Instead of waiting for users to request more options, RunLLM volunteers additional insights automatically, ensuring users have multiple approaches at their fingertips to increase the likelihood of a faster resolution.
Smart Web Searches: When RunLLM can’t find an answer in your knowledge base, it expands its search. Instead of leaving users stuck, RunLLM intelligently looks beyond internal sources — surfacing insights from trusted technical documentation, developer communities, and reliable web sources to find the best possible solution.
Check Ins: RunLLM doesn’t just answer and move on — it follows up. If an issue remains unresolved, RunLLM proactively checks back, asking if the solution worked. If not, it offers further guidance, alternative approaches, or escalates the issue to ensure users get the help they need.
RunLLM Feature - Alternative Solutions
AI That Verifies
Code snippets are valuable to technical users but often need adjusting to fit their needs. That’s why RunLLM now includes live code execution and validation — ensuring accuracy before an answer is even delivered.
Run & Verify Code: RunLLM doesn’t just generate code — it ensures it runs correctly. When a response includes a code snippet, RunLLM automatically executes it, validating accuracy before presenting the answer. If execution fails, RunLLM refines the code and tries again — ensuring users receive functional, validated solutions.
Iterative Debugging: If an initial solution doesn’t work, RunLLM troubleshoots dynamically — identifying errors, refining logic, and providing an improved fix, just like an engineer would.
RunLLM Feature - Code Execution
RunLLM wasn’t built to just answer questions — it was built to solve problems.
User Experience Video Walk Through
Want to see how RunLLM adds value to technical support conversations, learns from interactions, and improves response accuracy? In this demo, our CEO, Vikram, walks through:
How RunLLM handles complex technical questions—allowing users to upload code, logs, or error messages for richer responses.
Why RunLLM generates alternative solutions proactively instead of waiting for users to ask.
How RunLLM validates code execution—refining and correcting answers dynamically.
How RunLLM escalates unanswered questions to human support while learning from every resolution.
AI That Solves Problems
Every feature we’ve introduced serves one goal: helping users solve problems faster. RunLLM is redefining technical support, delivering the expertise of a top support engineer with the speed and scale of AI.
And this is just the beginning. As we refine AI support engineering, expand integrations, and deepen RunLLM’s capabilities, we want your input. What would take your advanced technical support experience to the next level?
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