CHATBOTS

Outlook Concierge: Negotiate a Meeting Time by Reply

A chat concierge reads inbound meeting requests, proposes open slots from everyone's Outlook calendars, and books the meeting once attendees agree in plain-language replies.

CategoryChatbots
Enginepaperclip
Difficultyintermediate
Triggerchat
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerChat message requests a meeting
  • ActionPull free/busy for each attendeeOutlook
  • ActionDraft candidate slots from constraintsOpenAI
  • ActionPost options and classify repliesOpenAI
  • LogicCheck for unanimous acceptance
  • OutputBook the agreed Outlook eventOutlook

What it does

Turns a back-and-forth scheduling thread into a single conversation. The bot ingests a natural-language meeting request, checks free/busy across every named attendee in Outlook, proposes two or three workable slots, interprets each attendee's reply ("Tuesday works", "after lunch is better"), and books the event when a slot wins consensus.

When to use it

Use it when an assistant or team lead keeps brokering times across busy calendars and wants the loop handled without a scheduling-link round trip. Best for internal or trusted-external meetings where attendees already reply by chat or email.

How it works

  1. 1A chat message kicks off the request with attendees, duration, and constraints.
  2. 2The bot calls Outlook free/busy for each attendee to gather availability.
  3. 3OpenAI reasons over the constraints and drafts two to three candidate slots in natural language.
  4. 4The bot posts the options and waits for replies, classifying each as accept, reject, or counter.
  5. 5A logic step checks whether a single slot has unanimous acceptance.
  6. 6On consensus it creates the Outlook event with all attendees; otherwise it loops with revised options.

Set it up

What you configure once, before turning it on.

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

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