AI & RAG

MSA Clause Answers in Front from Dropbox Agreements

Watches a Front inbox for questions like 'what does our MSA say about indemnification', retrieves the relevant clauses from your Dropbox contract library.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew message in Front inboxFront
  • LogicDetect contract question and extract topic
  • ActionVector search clause chunks in PostgresPostgreSQLPostgres
  • ActionDraft grounded answer with citationsOpenAI
  • OutputPost draft reply as Front commentFront

What it does

When a teammate or customer asks a contract question in a Front conversation, this workflow finds the exact clauses in your stored agreements and drafts a reply that quotes them with source citations — no more digging through PDFs in Dropbox.

When to use it

Use it when your sales, legal, or support team fields recurring 'what does the contract say about X' questions and you keep signed MSAs, SOWs, and amendments in Dropbox. It turns a 20-minute document hunt into a drafted answer waiting for human approval.

How it works

  1. 1A new message lands in the monitored Front inbox and triggers the flow.
  2. 2A logic step checks whether the message is actually a contract question (keyword and intent gate) and extracts the topic.
  3. 3The workflow embeds the question and queries your Postgres vector store of pre-indexed Dropbox clause chunks for the closest matches.
  4. 4OpenAI composes an answer grounded strictly in the retrieved clauses, refusing to speculate beyond them, and appends document name and section citations.
  5. 5The drafted reply is posted as an internal comment in Front for a human to review and send.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect DropboxFiles and folders.
  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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