Product
The Only AI Support Engineer
Purpose-Built for Your Product
RunLLM handles basic and advanced questions—with code validation, multimodal responses, and alternative solutions. Cut ticket volume, speed up resolutions, and free your team to focus on what matters most.
RunLLM saves users time by delivering answers in seconds—not minutes or hours. With grounded AI responses, complete with documentation citations and follow-ups, users stay unblocked and engaged.
RunLLM analyzes user inquiries and feedback to pinpoint gaps in your docs and product. Get automated suggestions to enhance your knowledge base and create a continuous cycle of improvement.
RunLLM's grounded AI is based on the data you provide. Every RunLLM assistant is powered by a fine-tuned LLM that's an expert on your product and a knowledge base that's continuously updated with best-in-class data engineering. This combination allows RunLLM to generate the highest quality answers for your technical questions.
Our AI Support Engineer is built to deeply understand your product, assist your customers wherever they need help, fit into your team’s workflows, and help improve your product and documentation.
Answer Quality
Advanced Data Pipelines
Ingests and annotates your docs, APIs, guides, and more
Custom Model Fine-Tuning
Trains a model on your product and terminology
Multi-Agent Precision
Orchestrates agents for guardrails and precision
Continuous Learning
Learns instantly from feedback to continuously improve
Actionable Insights
Topic Modeling
Organizes conversations into clear, actionable themes
Proactive Docs Updates
Suggests and auto-generates documentation improvements
User Sentiment
Tracks satisfaction and friction across your product and docs
Trend Detection
Surfaces features request and common challenges
Agent Capabilities
Multimodal Support
Handles text, code, and images for complete context
Code Execution and Validation
Validates generated code for usefulness and trust
Proactive Alternate Solutions
Suggests best practices and fallback paths
Seamless Human Escalations
Escalates complex issues to human support when needed
Workflow Integration
Seamless Integration
Connects to Docs, Slack, Github, Zendesk, and more
Flexible Deployment
Embeds in chat, docs, Slack, Discord and Zendesk
Instant Data Sync
Ingests docs, tickets, and code on a schedule or on demand
Unified Dashboard
Configures integrations and manages deployments centrally
Behind every interaction, we employ sophisticated multi-step reasoning and dynamic decision making, including Supervised Fine-Tuning, GraphRAG, Policy-Driven Re-ranking, and adaptive refinement. These techniques deliver consistently precise, relevant, and actionable answers that transform technical support interactions.
Model Specialization
Fine-Tuned LLMs
Trains a dedicated LLM on your product’s documentation and vocabulary for the best possible answer precision
Synthetic QA Generation
Transforms your docs into thousands of realistic Q&A pairs to bridge the gap between how users ask and how your docs explain
GraphRAG
Builds a structured knowledge graph to support deep, hierarchical retrieval and alternative path exploration
Decision Intelligence
Multi-Agent Reasoning
Dynamic planner routes queries through retrieval, re-ranking, refinement, and validation until confident
Contextual Re-Ranking
Scores docs by authority, freshness, authorship, and clarity, with tunable weights for your use case
Secure Code Execution
Executes code in ephemeral, sandboxed environments. Retries on failure, repairing until correctness is confirmed
RunLLM ensures enterprise-grade security through SOC 2 audits, sandboxed code execution, and data governance.
Soc 2 Type II Compliant
Validates security, availability, and access controls through independent audits for enterprise-grade compliance
Isolated Runtime Sandbox
Executes code in isolated containers without data or network access. Logs activity and discards sessions post-run
Granular Data Governance
Controls ingestion, visibility, and retrieval by source, enabling precise and enforceable access rules