DOCUMENT OPS

NDA Risk-Flag Triage to Postgres Ledger

Scores each incoming NDA against your risk policy, routes high-risk agreements to a Slack escalation channel, and records every decision and flag in a Postgres audit ledger.

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew NDA email in intake mailboxGmailGmail
  • ActionClassify clause risk with Hugging FaceHugging FaceHugging Face
  • LogicBranch low-risk vs high-risk by tier
  • ActionInsert NDA, flags, and tier into Postgres ledgerPostgreSQLPostgres
  • OutputEscalate high-risk NDAs to SlackSlack

What it does

Takes NDAs as they arrive, classifies each clause for risk (unlimited term, broad non-compete, one-sided indemnity, missing mutual-confidentiality), assigns an overall risk tier, and writes the full result to a Postgres ledger. High-risk agreements are pushed to a Slack channel so counsel sees them immediately instead of waiting in a queue.

When to use it

Use it when not every NDA needs the same scrutiny and you want low-risk standard forms to auto-clear while only genuinely risky terms reach a lawyer. The Postgres ledger gives you an auditable record of what was flagged and why.

How it works

  1. 1A new NDA email lands in the intake mailbox.
  2. 2A Hugging Face classifier scores each clause and produces a risk tier.
  3. 3A logic branch splits low-risk from high-risk based on the tier and flagged clauses.
  4. 4Every NDA, its flags, and the tier are inserted into the Postgres review ledger.
  5. 5High-risk agreements are posted to the legal escalation Slack channel with the offending clauses called out.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GmailRead, draft, send, label.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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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