CHATBOTS
Leave Request Bot with Manager Approval in Teams
Lets employees request time off through a Teams chat, checks remaining balance, then routes the request to their manager for an approve/deny tap and logs the decision to a Monday…
How it runs
The automated pipeline, trigger to output.
- TriggerEmployee requests leave in TeamsMicrosoft Teams
- ActionExtract dates and leave type with OpenAIOpenAI
- ActionLook up remaining balance on Monday boardmonday.com
- LogicCheck balance covers the request
- ActionSend approve/deny card to manager in TeamsMicrosoft Teams
- OutputLog decision to Monday and notify employeemonday.com
What it does
Turns a casual Teams message like "I want to take Aug 4-8 off" into a structured leave request. The bot parses the dates, validates them against the employee's remaining balance, and hands the request to the manager for a one-tap decision — then records the outcome on a Monday tracking board.
When to use it
Use this when leave requests bounce around email and spreadsheets and managers approve without seeing balances. It gives employees a conversational front door and gives managers a clean approval card with the context they need.
How it works
- 1An employee describes their desired leave in the Teams leave channel, triggering the flow.
- 2OpenAI extracts structured fields — start date, end date, leave type — from the natural-language message.
- 3The flow looks up the employee's remaining balance on the Monday board.
- 4A logic gate checks whether the balance covers the request; insufficient balance gets an immediate decline message.
- 5The bot sends an approval card to the manager in Teams with the parsed request and current balance.
- 6On the manager's approve or deny tap, the decision and new balance are written back to the Monday board and the employee is notified.
Set it up
What you configure once, before turning it on.
- 1Connect Microsoft TeamsChannels, chats, files.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect monday.comVisual work management for teams.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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