DOCUMENT OPS

Triage emailed contract redlines and route by risk

When a counterparty emails a redlined contract, extracts the attachment, diffs clauses against approved templates.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerContract attachment arrives by emailGmailGmail
  • ActionParse attachment and extract clausesOpenAI
  • ActionDiff clauses vs templates and assign risk tierOpenAI
  • LogicBranch high-risk vs low-risk deviations
  • OutputEscalate high-risk to Slack, auto-clear low-riskSlack

What it does

Catches inbound emails carrying contract attachments, diffs the document's clauses against your approved templates, and makes a routing decision: contracts with only low-risk or cosmetic edits get auto-acknowledged, while any high-risk deviation (indemnity, liability cap, termination, payment terms) is escalated to legal with the specific language flagged. It turns the shared contracts inbox into a self-sorting queue.

When to use it

Use it when counterparties send marked-up contracts by email and your team wastes time opening every attachment just to learn most are routine. Best for high-volume sales or procurement pipelines where only a fraction of redlines actually need a lawyer.

How it works

  1. 1A new email with a document attachment in the monitored inbox triggers the run.
  2. 2The attachment is parsed and its clauses extracted.
  3. 3An OpenAI step diffs each clause against the approved template and assigns a risk tier per deviation.
  4. 4A logic branch separates high-risk from low-risk contracts.
  5. 5High-risk contracts post an escalation to the Slack legal channel with flagged clauses; low-risk ones get a logged auto-acknowledgement.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GmailRead, draft, send, label.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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