PLAYBOOK · IT OPERATIONS

Turn Confluence, Jira, and GitHub into an IT helpdesk knowledge assistant.

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.

ConfluenceJiraGitHub VectorsSEEMR
Private RAG
VDF Data Overview
The problem

Knowledge exists — discovery doesn't

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.

The VDF AI approach

Federated semantic search across all three

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.

REFERENCE ARCHITECTURE

Tickets in, cited answers out

Confluence · Jira · GitHub
VDF Vector Stores
Per-source pgvector indexes
all_vectors_search
Federated tool
Custom HTTP Tool
ITSM ticket actions
Helpdesk Network
triage · resolve · escalate
Agent reply + runbook citation
PLAYBOOK · STEP BY STEP

Wire it up in five afternoons

1

Connect Confluence, Jira, and GitHub

Use the built-in integrations to authorize VDF Data to read each source. Schedule re-indexing.

2

Build vector indexes

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.

3

Wrap ITSM actions as Custom HTTP tools

"Create ticket", "assign", "request more info" become callable tools — VDF AI handles auth and rate limiting.

4

Compose the Helpdesk Agent

System prompt: cite Confluence first, fall back to Jira history, then GitHub READMEs. Output a draft reply and a recommended action.

5

Run, monitor, evolve

Live monitoring shows every retrieval. SEEMR learns which source resolves which intent fastest.

Helpdesk network live execution monitoring
OUTCOMES

L1 talks less, resolves more

tickets resolved per L1 agent shift.

−45%

average handling time on repeat issues.

100%

answers cite the runbook, doc, or past ticket they came from.

SEEMR REFERENCE

Quality compounds with every resolved ticket

SEEMR's knowledge-graph mode wires resolved-ticket signals into the routing fabric, so common issues get cheaper and faster over time.

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GET IN TOUCH

You Have Questions

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.