DOCUMENT OPS

On-Demand Redline Clause Matrix via Webhook to Coda

Accepts a webhook carrying a Dropbox file path, extracts and compares the redlined clauses against your standard, and returns plus stores a full clause matrix in Coda.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook received with Dropbox file pathHTTP webhook
  • ActionDownload referenced file and extract textDropboxDropbox
  • ActionBuild clause comparison with risk flagsOpenAI
  • ActionWrite matrix rows to CodaCodaCoda
  • OutputReturn summary payload to callerHTTP webhook

What it does

Exposes an HTTP endpoint your CLM, intake form, or internal tool can call with a Dropbox path to a redlined contract. The flow fetches that specific file, builds the complete clause-comparison matrix, writes it to Coda, and returns a summary payload to the caller so the requesting system can show status immediately.

When to use it

Use it when analysis should be pulled by another system at a precise moment — a reviewer clicking "Analyze," a CLM stage transition — rather than fired automatically on every file drop. The webhook gives you explicit, traceable control over when each contract is processed.

How it works

  1. 1An inbound webhook arrives with the Dropbox file path and a request id.
  2. 2The flow downloads that exact file from Dropbox and extracts its text.
  3. 3OpenAI produces the clause-by-clause comparison: standard language, counterparty language, the delta, and a risk flag per clause.
  4. 4The matrix rows are written to a Coda table tagged with the request id for traceability.
  5. 5An output step returns a JSON summary (clause count, highest risk, Coda row link) to the webhook caller.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect DropboxFiles and folders.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect CodaDocs, packs, automations.
  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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