CHATBOTS

Benefits Q&A Assistant in Teams from Plan Documents

Answers employee benefits questions in Microsoft Teams by retrieving authoritative passages from your plan documents in Confluence.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEmployee @mentions assistant in TeamsMicrosoft Teams
  • ActionSearch benefits plan docs in ConfluenceConfluenceConfluence
  • ActionDraft grounded answer with OpenAIOpenAI
  • LogicCheck answer confidence and scope
  • OutputReply in Teams thread with citationMicrosoft Teams

What it does

Gives employees a self-serve benefits assistant inside Microsoft Teams. When someone asks about deductibles, dependent eligibility, FSA limits, or open-enrollment dates, the assistant searches your benefits plan documentation in Confluence, grounds its answer in the actual policy text, and replies in the same Teams thread with a citation to the source page.

When to use it

During open enrollment or year-round, when HR spends hours answering the same plan-detail questions. Best when your summary plan descriptions, benefit guides, and FAQs already live in Confluence and you want answers tied to that source of truth rather than guesses.

How it works

  1. 1An employee posts a benefits question by @mentioning the assistant in a Teams channel or chat.
  2. 2The question is converted to a search query and run against the benefits space in Confluence to pull the most relevant plan-document passages.
  3. 3OpenAI composes an answer constrained to the retrieved text, refusing to speculate when coverage isn't documented.
  4. 4A guard checks confidence; low-confidence or out-of-scope questions are flagged for human HR follow-up.
  5. 5The assistant replies in the original Teams thread with the answer and a link to the Confluence source page.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Microsoft TeamsChannels, chats, files.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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