AI Agents for your Hardest Technology Problems
The agentic platform that becomes an expert on your technology, reasons transparently, configures seamlessly, and continuously learns.
Platform Leverage
The RunLLM platform ingests massive volumes of technical data through advanced pipelines, structures it into a knowledge graph, fine-tunes dedicated models to master your product’s terminology and edge cases, and orchestrates with agentic planning for deep, transparent reasoning across domains.
Battle-tested over two years in production, RunLLM has answered over 1 million technical questions for customers.
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Core Platform Capabilities
Custom pipelines ingest logs, traces, metrics, tickets, and docs
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Contextual re-ranking surfaces high-signal data over noise
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GraphRAG maps dependencies and historical events for causal context
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Fine-tuned models trained on your runbooks, observability data, APIs, docs, and more
Supervised fine-tuning captures nuanced domain knowledge and boosts retrieval accuracy
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Multi-agent reasoning with validation and refinement loops
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Dozens of coordinated model calls per response, scoped to retrieval, validation, and refinement
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Adaptive tool use with built-in error checking
Dependency-aware planning models service relationships to surface likely cause-and-effect, not just correlations.
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Human feedback instantly applies to future responses
Analytics cluster recurring issues and highlight documentation gaps
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Runbooks and knowledge bases evolve automatically, reducing drift
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Quality guardrails detect contradictions, validate new knowledge, and monitor performance
SOC 2 Type II certified
Human-in-the-loop approvals for risky actions
Every agent is isolated and no data is ever shared
Audit logging and policy enforcement at every step
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Open APIs for custom and homegrown systems
Connectors for Datadog, Grafana, PagerDuty, Jira, Zendesk, and more
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Built to handle enterprise-scale ingestion and query loads
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Real-time sync keeps data and docs fresh
Agent Specialization
On top of the shared RunLLM platform, each agent is specialized to map directly to the workflows, data, and responsibilities of its use case. This architecture adapts with the precision required for reliability engineering and technical support — while also sharing end-to-end context about how customers experience your company’s solutions.
Built for Trust
RunLLM’s platform was created by PhDs and professors from UC Berkeley’s RISELab, with over a decade of research in distributed systems and AI. t is production-proven across technical environments, SOC 2 certified, and designed to show its reasoning and evidence — never a black box.
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