Hi @Ultra_Fund — I’d approach this as a data-integrity audit before changing the existing Make scenario.
The first thing I’d test is whether the final merchant record stays correct when the same documents arrive in different orders.
For example:
application → bank statements
bank statements → application
repeated application
later document with blank fields
The same rules should hold every time: one merchant record, application-authoritative fields preserved, no blank overwrite, and no broker/funder data leaking into merchant fields.
I can do a bounded first audit for $120 fixed using the Make blueprint, Airtable schema, and redacted or synthetic samples only.
You’d get:
a field/source authority map;
replay results for the duplicate and overwrite cases;
a written PASS/FAIL findings list;
the prioritized repair order.
No live credentials, production writes, real SSNs, or unredacted bank statements are needed for the audit.
My background is API/automation reliability and deterministic workflow testing rather than years of paid Make client work, so I don’t want to overstate that. I do have a controlled reliability case I can share if you want to see how I reproduce and verify incorrect business outcomes.
If the audit shows part of the current workflow is already correct, I’ll say so rather than invent work.
I’m Giambattista from SABIA LABS. Your project is a strong fit for us, especially because the goal is to stabilize and complete the existing system rather than rebuild it unnecessarily.
I’d begin with a paid technical audit covering merchant deduplication, source-priority rules, application vs bank-statement extraction, protection against incorrect overwrites, Airtable/Drive linking, and error handling.
The audit would produce a clear failure map and a fixed implementation proposal. If useful, we can then complete and test the workflow end to end.
Could you share the Make blueprint and 2–3 redacted sample files privately? I’m also available to sign an NDA before reviewing any sensitive material.
@Ultra_Fund — you already asked for the right first product: a short paid audit of what exists, not a rebuild.
The failure mode here is usually source precedence living in module order (application vs bank statement vs broker/ISO), not “the AI extraction is bad.” Blanks then overwrite good merchant fields, and a second document creates a second Airtable row.
I do a 48h written Diagnostic IA (PDF by email, no call, no RPA): field-authority matrix (which source may write which field, and whether a blank can ever clear it), replay test (same merchant, both arrival orders → one record, no blank-overwrite), and the 3 fixes to do first vs what to leave alone.
60 USDC (~60 EUR), paid on-chain. I send a USDC invoice after you confirm. Reply here or DM “audit” and I’ll send the 10-line intake (redacted samples only — no live SSNs / unredacted statements).
Hi, this is very close to the type of Make.com workflow I’ve been building recently.
I’ve worked with Gmail/webhook intake, Google Drive, AI data extraction, JSON parsing, validation, duplicate checks, routers and structured output workflows.
I’d be interested in starting with the short paid audit you mentioned rather than rebuilding anything unnecessarily.
I can review the current scenario, identify where the duplicate/source-priority/update logic is breaking, and give you a clear list of fixes.
I’m available today. For the initial audit, I’d suggest $50 fixed, and if the implementation scope is a fit we can agree on the next milestone separately.
Happy to share a redacted screenshot/demo of a multi-step Make workflow I’ve built.
I’d be interested in starting with the paid audit.
My background is in building and maintaining operational systems using Airtable and Make, including multi-step workflows, structured record management, search/update logic, integrations and troubleshooting production processes.
A lot of what you’ve described is less about rebuilding the automation and more about protecting data integrity: establishing which source is authoritative, preventing duplicate records, making updates non-destructive, keeping related records/documents linked correctly and ensuring exceptions don’t silently corrupt the Airtable data.
That’s an area I’m comfortable working through.
I’m currently responsible for an operational Airtable + Make system connecting customer/order data with Shopify. That work has included record matching, linked data, payment/status synchronisation, resolving missing or duplicate records and adjusting live workflows without breaking the underlying operational process.
I want to be transparent that AI document extraction itself is not the strongest part of my background, so I wouldn’t present myself as an AI extraction specialist. My strongest contribution would be auditing the Make scenario and Airtable structure around the extraction layer — particularly mapping, deduplication, source precedence, non-blank updates, record relationships and failure handling.
I’d be comfortable starting with a small paid audit before quoting the implementation.
I’m based in South Africa, available this week, and my standard rate for this type of work is $20/hour. I’m also open to agreeing a fixed scope for the initial audit once I’ve seen the Make blueprint and Airtable structure.
I’d start with one merchant and trace what happens when the application arrives, then a statement, then the same email runs again. I want to separate extraction problems from record matching and update problems before changing anything. I’d also check overlapping runs: two runs might both find no match and create separate records.
For a first audit, I’d propose $200 for one scenario, its Airtable structure and up to three problem cases, with the scope agreed first. You’d get annotated findings, a repair order and a test checklist for duplicates and unwanted overwrites. Implementation would be quoted separately after that review.
We can discuss the scope here, asynchronously. Which issue is costing you the most time right now: duplicates, blank overwrites or the wrong contact being picked up? A made-up example is enough at this stage; please don’t post bank statements, IDs or credentials.
Hey @Ultra_Fund
I read through your requirement and a few things stood out.
The duplicate merchant records suggest the workflow doesn’t have a reliable unique identifier before creating new records. That can usually be solved by introducing a consistent matching layer before any record is written.
The issue of later bank statements overwriting good application data points to missing field-level validation and update rules. Separating trusted application data from document extraction prevents valid information from being replaced by blank or incomplete values.
The merchant vs. broker/funder mix-up is typically caused by entity mapping during AI extraction. Adding validation and classification before writing to Airtable helps keep those records separate.
we help businesses improve existing automation workflows instead of rebuilding them from scratch, so we would be happy to review your current Make scenario, identify the root cause and implement only the changes that are actually needed. Would you be open to sharing how your current merchant matching logic is set up?
@Ultra_Fund — SIL is a new service brand, so I won’t invent client case studies. Our current proof is an owned synthetic reliability canary that reproduces transient failures and duplicate deliveries, then verifies retry/idempotency hardening with deterministic acceptance checks.
For your existing Make + Airtable flow, I’d start with a fixed $249 audit using only the Make blueprint, Airtable schema, and redacted/synthetic fixtures. I’d return:
a source/field-authority map (application vs bank statement vs broker/funder)
replay tests with documents arriving in different orders
PASS/FAIL evidence for duplicate merchants, blank overwrites, merchant/contact contamination, linking, and retry/error paths
the exact repair order, with implementation quoted separately only if the audit finds real work
No live credentials, real SSNs, or unredacted bank statements needed for the audit. If the flow already passes, I’ll say that too.
If this is still open, which is costing you more right now: duplicate merchants or good application fields getting overwritten?
Ultra_Fund — I’d treat this as a data-integrity rescue, not a rebuild. Before changing modules, I’d test whether every merchant field has an explicit authorized source and null-overwrite rule, or whether precedence is only implicit in scenario order.
My relevant proof is API/webhook workflows, typed structured outputs, dedupe/idempotency, and failure-path testing; I won’t claim prior MCA or production Make/Airtable client work that I don’t have.
I can do a $400 fixed, two-business-day audit from the Make blueprint, Airtable schema, and two redacted or synthetic fixture sets—no production writes, live credentials, real SSNs/EINs, or unredacted bank statements. You get a field-authority matrix, both document-arrival-order replay tests, PASS/FAIL for duplicates, blank overwrites, broker/funder contamination and broken links, plus the exact repair order. If the audit shows a viable repair path, implementation is scoped separately.
Hi Ultra_Fund, I saw you’re finishing the MCA CRM automation with Gmail intake, AI extraction, and Airtable.
The duplicate prevention and record structure part is usually where these workflows get tricky.
I help businesses build and fix Make.com systems like this. Happy to take a look at where the current flow is breaking and suggest the cleanest approach.
this is very close to the Make workflows I’ve been building recently — Gmail intake, Google Drive, OpenAI structured extraction, Google Sheets/CRM-style data processing and automated follow-ups.
I’d be interested in starting with the paid audit you mentioned. I can review the existing scenario, identify where the duplicate/overwrite logic is breaking and give you a clear fix plan before changing anything.
I’m available to start immediately and can also share a recent Make workflow example.
@Ultra_Fund the bit I’d look at first is “prevents later documents from overwriting good application data with blanks.”
That’s usually not an extraction problem. The model hands you “”, “N/A” and null for the same situation, and Airtable can’t tell “wasn’t on this document” apart from “actually empty.” Until every field comes back with a found/not-found flag next to it, no update rule you write downstream is going to hold.
The other thing I’d want to know is what you’re using as the merchant key. Business name falls over on LLC vs L.L.C. vs DBA. EIN is blank on a lot of applications. So it ends up falling back to a normalised phone or email, and that’s where broker contact tends to leak into the merchant record.
$250 fixed, three or four hours. We write down what the audit has to cover before I start. I walk you through what I find, live, on your own scenario. If the writeup doesn’t point at a specific place your scenario drops or overwrites data, don’t pay me for it. Escrow is fine if you’d rather.
I worked US Eastern hours from Dhaka for four months this year, so the time difference isn’t a problem.
I can help with this. I’d suggest starting with the paid audit you mentioned rather than rebuilding anything unnecessarily.
I can review the existing Make + Airtable setup, focusing on merchant deduplication, source priority, preventing blank overwrites, AI document extraction, Airtable/Drive linking and error handling.
For the initial audit, I can offer a fixed price of $125. I’ll identify the failure points, provide a prioritized fix plan, and give you a clear fixed quote for completing the implementation.
I can start immediately. Redacted/synthetic data is completely fine for the initial review.
I’m Zay. I develop and maintain business automations, and my background in banking is particularly relevant to the funding workflow you’re finishing. The information your team uses to assess a merchant needs to remain dependable as applications and bank statements arrive.
My experience spans more than eight years working on business systems, with responsibility for organising data, connecting processes and resolving the issues that interrupt operations. I work with Make and Airtable as well as JavaScript, Python and APIs, so I can follow a problem from the document or integration through to the record your team actually uses.
I’ve built a Make workflow that validates incoming requests, creates or updates Airtable records, prepares documents and email drafts, and notifies the team. Repeat submissions update the existing opportunity. In my application work, I’ve also handled recovery after partial failures, where repeating an operation could duplicate an action already accepted by another service.
For your CRM, I’d take responsibility for the short paid audit and the subsequent repairs. The useful outcome would be a merchant record your team can trust, with its supporting documents correctly attached and later uploads preserving valid application data. I would verify that against repeat submissions, incomplete documents and documents arriving in a different order, as well as the normal intake flow.
My banking experience helps me approach this as an operational handover: clear information, a traceable source and a workflow someone else can understand and maintain. You can see my work with connected systems in my portfolio.
I’m based in Spain and available to discuss the audit and implementation. I would agree a fixed audit fee after reviewing the scenario’s scope, then price the repairs against the findings.
I’d be glad to discuss the project and how I could help you finish it. Happy to continue here or by message.
Hi Ultra_Fund, I’m contacting you from CemX about the audit and completion of your Make/Airtable funding CRM. Are you still looking for help? Could you share the current scope or specification, a sanitized Make blueprint and Airtable schema, plus one example of the duplicate or blank-overwrite issue? Please remove credentials and all real applicant/bank data; synthetic examples are enough for an initial review. What deadline and budget have you set for the initial audit?
Hi @Ultra_Fund — I went through the workflow requirements and the existing discussion, and I’d approach the audit slightly differently from a normal Make workflow review.
The first thing I’d want to prove is whether the workflow is convergent: if the same merchant’s application, bank statement and supporting documents arrive in different orders, or one document is processed twice, do we still end up with exactly one merchant record and the same authoritative final values?
I’d test that with a small synthetic replay set covering:
application → bank statement → later correction
bank statement → application
duplicate document/event
incomplete document after a complete one
broker/funder data appearing alongside merchant data
failed/retried Airtable update
Rather than just identifying where the current scenario breaks, I’d turn those cases into explicit pass/fail acceptance tests and use them to make the minimum changes required to the existing scenario.
I’d also map field-level source authority before changing the update logic, so we know exactly which source is allowed to populate or overwrite each field.
If the paid audit is still open, I’m happy to work from a redacted/synthetic dataset and return the failure map + source-authority map + prioritized implementation plan before touching production.
If you send the current Make blueprint/schema, I can start from the existing architecture rather than rebuilding it unnecessarily.
Hi Ultra_Fund — is this audit still open? I’m Velmren at Patchcairn. I can offer a $75 first stage: review the Make blueprint and Airtable schema, then deliver a source-precedence map, a replay-test checklist for duplicate/partial arrivals, and a concrete fix list. The audit would cover one merchant per business, application fields taking precedence, blank-field protection, and correct document links. Inputs can be a blueprint export, schema, and a few redacted or synthetic example payloads.
Delivery would be within 24 hours of receiving the agreed inputs and kickoff payment, with one clarification pass. Would $40 at kickoff and $35 on acceptance fit your budget? If your process requires payment on acceptance, please confirm the acceptance criteria and payment timing before work begins. Which payment method works for you? Implementation can be scoped after the audit.
Hi Ultra_Fund — I think the main problem here is not the AI extraction itself, but controlling what happens to the extracted data afterwards.
I would start with an audit rather than rebuild the scenario.
For the audit I would test four things specifically:
Whether the same merchant always resolves to one record, regardless of document arrival order.
Which source is allowed to populate or change each merchant field.
Whether a later blank/low-authority value can overwrite an existing valid value.
Whether merchant data can ever be contaminated by broker/ISO/funder data.
I would also replay the same redacted document set in different arrival orders. The final merchant record should be deterministic in both cases.
My proposed first step is a fixed $250 audit, delivered within 48 hours.
Deliverables:
• current-flow / failure-point map
• field authority and source-precedence matrix
• duplicate and overwrite replay tests
• PASS/FAIL findings
• prioritized repair plan
• fixed scope and price for implementation
I can work from the Make blueprint, Airtable schema and 2–3 redacted or synthetic document sets. I don’t need production credentials, real SSNs or unredacted bank data for the audit.
My relevant experience is building a production document-processing workflow around Gmail, multiple incoming files, AI/data extraction, deduplication, normalization, source validation, reporting and exception handling. I don’t want to overstate that as MCA-specific experience, but the underlying data-integrity problems are very similar.
If the project is still open, I’d start by answering one question: which problem is currently causing more damage — duplicate merchant records or valid application data being overwritten?
your paid-audit-first approach makes sense for this workflow. The duplicate records, blank overwrites, and source-priority issues are closely related to data-integrity and workflow-reliability problems I have been working on in my own n8n, Airtable, API, and AI automation projects.
I want to be transparent: my current hands-on automation work is primarily in n8n and API-based workflows, not previous client production work in Make. I have, however, built and tested Airtable automation, duplicate prevention, structured data validation, AI extraction workflows, and error handling.
I could start with a $95 fixed paid audit: review the workflow logic and Airtable structure using only redacted or synthetic samples, check the duplicate/source-priority/non-blank update logic, investigate one reproducible failure path, and provide a prioritized fix plan.
No live credentials, raw SSNs, or unredacted bank statements would be needed for the audit.
If that scope works for you, I’d be happy to start there.