CRM

Merge Audit Warehouse Sync with Rollback-Ready Reporting

On each completed reconciliation run, ships the full before/after merge audit log from Postgres into Snowflake, generates a reversible change manifest.

CategoryCRM
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerReconciliation-completed webhookHTTP webhook
  • ActionRead new audit rows from PostgresPostgreSQLPostgres
  • LogicBuild warehouse rows + rollback manifest
  • ActionLoad audit + manifest into SnowflakeSnowflakeSnowflake
  • LogicCheck anomaly thresholds
  • OutputPost data-quality report to SlackSlack

What it does

Turns your dedup activity into an analyzable, reversible record. After a reconciliation run, it loads every merge — old values, new values, source decisions — from the operational Postgres audit table into Snowflake, builds a rollback manifest mapping each changed field to its prior value, and summarizes run health for the data team.

When to use it

When compliance or data governance needs a queryable history of every automated contact merge, and engineering wants a guaranteed path to reverse a merge that turns out wrong.

How it works

  1. 1A reconciliation-completed webhook triggers the sync.
  2. 2Read the run's new audit rows from Postgres.
  3. 3Transform them into a warehouse schema and a rollback manifest (field-level prior values).
  4. 4Load both into Snowflake tables.
  5. 5Compute run-level data-quality metrics (merges, conflicts, auto vs reviewed).
  6. 6Branch: if anomaly thresholds are exceeded, escalate; otherwise send a normal report.
  7. 7Post the report and a link to the rollback manifest to Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SnowflakeWarehouses, queries, shares.
  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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