AI & RAG

Customer MSA Self-Service Answers via Front

When a customer emails asking about a term in their own signed agreement, it identifies their account, retrieves clauses only from their contract in Dropbox, and drafts a scoped.

CategoryAI & RAG
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCustomer email in FrontFront
  • LogicResolve account and scope to their contracts
  • ActionAccount-scoped vector search in PostgresPostgreSQLPostgres
  • ActionDraft scoped, cited answer with OpenAIOpenAI
  • OutputStage draft reply in FrontFront

What it does

Handles inbound customer questions about their specific agreement — 'what's our payment term?' or 'does our contract cover SSO?' — by answering strictly from that customer's own signed documents, never another account's, with the clause quoted for confidence.

When to use it

Use it when customers email support or account managers about their own MSA terms and you want fast, accurate, account-scoped answers without exposing other customers' contracts.

How it works

  1. 1A customer email arrives in the Front inbox and triggers the flow.
  2. 2A logic step matches the sender's domain to an account and resolves which Dropbox contracts belong to them, enforcing strict tenant scoping.
  3. 3The workflow runs a vector search in Postgres filtered to only that customer's clause chunks.
  4. 4OpenAI drafts an answer grounded solely in the retrieved, account-scoped clauses, declining anything outside them.
  5. 5The reply is staged in Front as a draft for an agent to review and send, with the source clause cited inline.

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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