
LeadProof
Verify what happens after webhook delivery.
Hi Indie Hackers,
I’m Talha, founder of Tynovate Studio, where I led the build of LeadProof.
The product started with one question:
If a webhook returns 200 OK, how do we know the actual business workflow finished?
A form can submit successfully and an automation platform can report a successful run. But the final CRM record can still be missing, late, duplicated or incomplete. The technical delivery succeeded. The intended business outcome did not.
LeadProof adds two verification checkpoints to an existing workflow:
1. A source event when the lead enters.
2. A destination confirmation when the intended system processes it.
LeadProof correlates both events and classifies the outcome as verified, missing, late, duplicate or invalid. Failed outcomes remain visible as incidents instead of disappearing inside execution logs.
The product is now live with a 14-day free trial, but customer learning is only beginning.
The question I am trying to answer now is whether automation agencies, SaaS teams and operations teams see enough value in final-outcome verification to add these two checkpoints.
If you manage form, automation and CRM workflows, do you verify the final destination independently, or mainly rely on the automation platform’s execution logs?
I would genuinely value honest feedback, including reasons why you would not use something like this.
About
LeadProof exists because webhook delivery does not prove the intended outcome happened. It verifies that leads arrive on time, once, and with the required data.

13 Comments
The gap between receiving an HTTP 200 at the ingress level and downstream execution finishing is a classic issue. Building deployment infrastructure forced us to handle this early—an execution queue or web worker might return a 200 after successfully queuing a workload, but downstream worker crashes, silent timeouts, or state mismatches mean the deployment never actually completed. Decoupling ingestion status from actual execution state and introducing reconciliation loops made a huge difference in catching those silent drops. How are you handling state reconciliation when a downstream system accepts the payload but silently stalls or partial-fails during processing?
That’s a really interesting way to frame it.
“Recovered revenue” is much closer to the business outcome than “better monitoring.” One thing we’re being careful about is not overclaiming what LeadProof can prove today. The current product is focused on forward looking verification through source and destination checkpoints rather than reconstructing historical failures.
But the reconciliation idea is interesting if a prospect has reliable historical source and CRM data. It could make the problem tangible before asking them to add another verification layer.
Which source-to-destination workflow would you test first for that reconciliation?
Agreed — that distinction is important.
Delivery, workflow completion and business outcome are not necessarily the same thing.
That’s why LeadProof’s destination checkpoint is intended to verify a meaningful expected outcome not simply whether another request returned successfully. The interesting part for us now is learning which destination event teams actually consider proof that the business workflow completed.
For the workflows you’ve seen, what would you consider the strongest final confirmation?
The distinction between “workflow succeeded” and “business outcome happened” is interesting.
Curious whether teams see enough real failures here to justify adding another verification layer to workflows they already consider reliable.
That’s exactly the question we’re testing now...LeadProof is not meant for every automation. A simple, low-impact workflow probably doesn’t justify another verification layer.
The likely fit is a revenue critical, multi-step handoff where one missing, late, duplicate, or invalid outcome can cost more than the effort of adding verification.
Existing logs can show that an automation ran but not always that the expected destination record actually arrived, arrived on time and was complete. We’ve built the verification layer. Now we’re working with real teams to understand how frequently these failures happen and when that added visibility becomes valuable.
What type of workflow would cross that threshold for you?