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Last update time : 2026-01-06 13:09:30

Devgraph transforms fragmented engineering data into a live knowledge graph, enabling AI agents to navigate code, infrastructure, and workflows with precision.

In an era where engineering ecosystems are becoming increasingly complex, Devgraph is introducing a sophisticated AI-powered ontology engine designed to unify the disparate threads of modern development. By automatically discovering and mapping intricate relationships across source code, infrastructure, support tickets, and team communications, Devgraph constructs a dynamic, real-time knowledge graph. This centralized intelligence layer allows Large Language Models (LLMs) and autonomous AI agents to interact with technical systems with an unprecedented level of contextual awareness.

Beyond simple visualization, Devgraph empowers teams to execute complex natural-language queries and perform deep-dive dependency and impact analyses that were previously manual and error-prone. The platform is particularly effective at surfacing 'tribal knowledge'—the undocumented insights often lost in silos—thereby accelerating developer onboarding and streamlining cross-functional workflows. Whether it is automatically generating tickets or triggering deployments, the engine transforms static documentation into actionable intelligence.

Recognizing the critical importance of data sovereignty, Devgraph offers a flexible deployment model. Engineering teams can integrate any LLM—whether cloud-based, self-hosted, or entirely air-gapped—ensuring that privacy, cost management, and system performance remain firmly under internal control. As AI agents become a staple of the DevOps lifecycle, Devgraph provides the essential map they need to navigate and manage real-world systems safely and efficiently.

Pricing : Paid

Web Address : Devgraph

Tags : Devgraph AI ontology engine knowledge graph AI agents DevOps automation software dependency analysis engineering intelligence private LLM infrastructure mapping