CHATBOTS

Multi-Warehouse Stock Finder Across Airtable and Postgres

Answers "who has this part" by checking the Airtable floor base for the local site and a Postgres ERP table for sister warehouses.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerchat
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWorker asks for a SKU in TeamsMicrosoft Teams
  • ActionNormalize request into canonical SKUOpenAI
  • ActionCheck local stock in AirtableAirtableAirtable
  • LogicBranch if local stock is short
  • ActionQuery ERP for other sites in PostgresPostgreSQLPostgres
  • OutputReply with local plus nearest site stockMicrosoft Teams

What it does

When a part is out at the local site, this bot doesn't just say "none." It also queries the central Postgres ERP for on-hand quantities at other warehouses and tells the worker which sister site has it and how many, all in one Teams reply.

When to use it

Use it in a multi-site operation where a stockout locally doesn't mean a stockout company-wide. It saves a phone tree of calls between warehouses and helps the floor decide whether to transfer, backorder, or substitute.

How it works

  1. 1A worker asks for a SKU in Teams.
  2. 2An OpenAI step normalizes the request into a canonical SKU.
  3. 3The flow checks the local Airtable inventory base first for bin and quantity.
  4. 4A logic step decides: if local stock covers the need, reply now; if short, continue.
  5. 5The flow queries the Postgres ERP for that SKU's quantity-on-hand at every other site.
  6. 6The bot replies in Teams with local availability plus the nearest sister warehouse holding stock.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Microsoft TeamsChannels, chats, files.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect AirtableBases, tables, views, automations.
  4. 4
    Connect PostgresAny Postgres URL — query, write, migrate.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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