FINANCE
Validate incoming amendment payloads before recomputing recognition
Accepts contract-amendment payloads over a webhook, validates them against the existing schedule for completeness and sane effective dates.
How it runs
The automated pipeline, trigger to output.
- TriggerWebhook receives amendment payload from upstreamHTTP webhook
- ActionLoad referenced contract + current schedule from SnowflakeSnowflake
- LogicValidate existence, effective-date bounds, amount consistency
- ActionQuarantine invalid payloads to Snowflake error queueSnowflake
- ActionRecompute and persist waterfall for valid payloadsSnowflake
- OutputPost accepted/rejected confirmation to ops SlackSlack
What it does
Acts as a validation firewall in front of the recognition engine. Upstream CPQ or billing systems POST amendment payloads to a webhook; this flow checks that the contract exists, the effective date falls within the active term, and the new amounts are internally consistent before anything touches the schedule. Clean payloads proceed to a recompute; malformed ones are quarantined with a reason.
When to use it
Use it when amendment data arrives from a system you don't fully trust and a bad payload would silently corrupt a recognition schedule. The guardrail keeps garbage out of close.
How it works
- 1An HTTP webhook receives the amendment payload from the upstream system.
- 2The flow loads the referenced contract and current schedule from Snowflake.
- 3A validation branch checks contract existence, effective-date bounds, and amount consistency.
- 4Invalid payloads are written to a Snowflake error queue with a rejection reason and the flow stops.
- 5Valid payloads drive a recompute of the remaining waterfall, persisted to Snowflake.
- 6A confirmation (accepted or rejected, with reason) is returned and posted to the ops Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect SnowflakeWarehouses, queries, shares.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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