Half of every L1 ticket is "where is the runbook for this?". VDF AI's federated semantic search across Confluence, Jira, and GitHub gives your helpdesk agents an assistant that already read the docs.
Runbooks rot in Confluence, root-cause notes live in old Jira tickets, configuration lives in GitHub. L1 agents context-switch through six tools to answer one question.
VDF AI ships dedicated MCP tools for Confluence, Jira, and GitHub vector search — plus an all_vectors_search federated tool. A helpdesk agent uses them like any other capability.
Use the built-in integrations to authorize VDF Data to read each source. Schedule re-indexing.
Vectorize Confluence spaces, Jira issues by project, and GitHub repos. Each becomes a queryable MCP tool: confluence_vector_search, jira_vector_search, github_vector_search.
"Create ticket", "assign", "request more info" become callable tools — VDF AI handles auth and rate limiting.
System prompt: cite Confluence first, fall back to Jira history, then GitHub READMEs. Output a draft reply and a recommended action.
Live monitoring shows every retrieval. SEEMR learns which source resolves which intent fastest.

tickets resolved per L1 agent shift.
average handling time on repeat issues.
answers cite the runbook, doc, or past ticket they came from.
SEEMR's knowledge-graph mode wires resolved-ticket signals into the routing fabric, so common issues get cheaper and faster over time.
Tell us what you’re trying to achieve—governed AI Networks, enterprise RAG, deep integrations, or on‑premise deployment. We’ll help you map the right architecture, security posture, and rollout path. If you’re moving beyond AI pilots and need scalable, auditable execution, reach out—our team is ready to help.