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Last update time : 2025-12-21 14:26:09

Devgraph.ai launches an AI-powered knowledge graph that integrates GitHub, Jira, and Slack to provide real-time context for engineers and AI agents.

Devgraph.ai has introduced a sophisticated ontology engine designed to fundamentally change how engineering teams interact with their internal data. By continuously mapping source code, infrastructure, support tickets, and team conversations into a live knowledge graph, the platform provides much-needed grounding for Large Language Models (LLMs) and automated workflows. This real-time context is pulled directly from a wide array of developer tools, including GitHub, Jira, Slack, and Kubernetes.

Modern development teams are using Devgraph.ai to streamline complex operations, such as performing deep impact analysis before deployments and executing unified searches across their entire tech stack. Beyond simple data retrieval, the engine is proving vital for surfacing 'tribal knowledge'—the undocumented expertise often lost in fast-moving environments—thereby accelerating the onboarding process for new hires.

Perhaps most significantly, the platform empowers AI agents to perform actions and answer technical questions with a high degree of reliability. Devgraph.ai is built with versatility in mind, supporting any LLM and the Model Context Protocol (MCP). For organizations with strict security requirements, the solution also offers robust support for self-hosted and air-gapped deployments, ensuring that sensitive proprietary data remains within the company's controlled perimeter.

Pricing : Paid

Web Address : Devgraph.ai

Tags : Devgraph.ai ontology engine AI for engineers knowledge graph developer tools integration impact analysis AI agents LLM grounding Model Context Protocol air-gapped AI