Spark + StackGo

Run compliance from inside Spark. Checks start from a record and the result lands back on the client.

Spark publishes 1 trigger event and 1 action on its public Zapier listing. That is what a StackGo connector would be built on.

CRM System of record Not connected yet

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What Spark is

Spark is a modern Medicare brokerage platform to manage the full lifecycle of a client from quoting to post-enrollment support.

Description supplied by Spark.

The trigger

What starts a check

You do not open StackGo. A change in the system starts the work, and the system stays your source of truth.

Event	What StackGo does	What comes back
A deal or opportunity is won	Starts intake and runs identity	Status on the contact
A contact is created	Sends a branded verification request	Verification status
Contact details change	Re-screens against sanctions and PEP lists	Updated status, alert if changed

The write-back

What StackGo puts back on the record

A Spark connector would write named fields onto the record, not a link to a portal. These are the fields StackGo writes on the systems it connects to today.

Verification status
Risk rating
Last checked
Report link
Verified name
Date of birth
Document checked
Screening result
Beneficial owners
Form responses
Verification report (PDF)

Every field is optional. What each one holds, and which carry personal data, is set out once in what “integrates with” actually means.

How it lands in Spark

Create Contact

Spark's own write operations. The result goes onto the record you already work in.

Everything else Spark publishes

Spark’s public integration surface

The rest of what Spark exposes on Zapier, beyond the ones above. This is the raw material a connector would use.

1 event

Referral Source List

Names are Spark’s own, read from its public Zapier listing on 28 August 2026.

Questions

Common questions about Spark

What is Spark and why is it used?

Spark is a modern Medicare brokerage platform to manage the full lifecycle of a client from quoting to post-enrollment support.

How would a check result show up in Spark?

Through Spark’s own write operations: “Create Contact”. You choose which fields are written, and you can also run it one-way, with nothing written back to Spark at all.