White-label backend engineering

The engineering layer behind automation that holds up in production.

For automation agencies whose client work has outgrown the no-code layer.

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Works with n8n, Make.com, and Zapier stacks. Invisible to your client.

The gap

Automation fails quietly. That's the problem.

A vendor API returns a 200 with an empty body. A field arrives as a string where the next step expects a number. A workflow completes six of seven steps and stops. Nothing crashes, nobody is alerted, and the client finds out when something is missing.

No-code platforms are good at connecting steps. They are not built to track state across a run, retry safely, detect a silent mismatch, or hold a failed job for a human to resolve. That reliability layer has to be engineered.

That is the gap I fill, so your workflows keep running and your client relationship stays yours.

How it fits

Your workflow stays. I add the layer underneath.

Same workflow, same failure. Toggle to see what changes when the reliability layer is there.

Your no-code stepsWhere custom code is neededScroll sideways on small screens

What I build

The custom pieces your stack can't cover.

Three areas, delivered as production code your team can run, hand over, and put in front of a client.

Custom integrations

Connections to APIs that have no native connector, or where the connector covers half of what you need. Authentication, pagination, rate limits, and data mapping handled properly.

  • REST, SOAP, and webhook-driven APIs
  • Multi-vendor sourcing with fallback
  • Data normalization across systems

Backend infrastructure

The services underneath the workflow: schemas designed for the real data, authentication, persistent state, and queues, all containerized and deployable on the client's infrastructure.

  • Database and schema design
  • Auth, state, and job queues
  • Docker deployment

Production reliability

The layer that makes failures visible and recoverable. Every run is tracked, every failure is either retried safely or routed to someone who can resolve it.

  • Retries with backoff and idempotency
  • Exception queues and alerting
  • Structured logging and run history

Selected work

Procurement automation for a manufacturer.

Multi-distributor sourcing and purchase orders

Manufacturing client · delivered as backend infrastructure

An automation workflow needed to call multiple external APIs, apply custom decision logic, and produce documents. The no-code layer could orchestrate it, but could not carry it. I built the backend infrastructure underneath.

  • 01Parts sourced across Mouser, DigiKey, and other distributors, with automatic fallback when a vendor fails or has no stock
  • 02Weighted vendor comparison across price, availability, and lead time
  • 03Automated purchase order generation from the selected quotes
  • 04Packaged and deployed with Docker
Stack
PythonFastAPIPostgreSQLDocker
n8n / Make / Zapier FastAPI serviceauth · state · retries Mouser DigiKey Others Weighted comparisonfallback on failure PostgreSQL PO document

How it works

Three steps, no friction.

01

You send the spec

Share what the workflow needs to do, where it's breaking, and the systems involved. A rough brief is fine. We'll tighten scope together before any work starts.

02

I build it

I design and build the backend, test it against real failure cases, and deploy it. You get clear updates and documentation your team can work from.

03

You white-label the delivery

It goes to your client under your name. I stay behind the scenes and remain available for changes and support.

Starting is low-commitment. The first project is priced to prove the work before any ongoing arrangement, and no retainer is required upfront.

Contact

Tell me where your workflow is breaking.

A few lines on what you're trying to solve is enough. I'll reply with questions or a rough approach.

Or reach out directly
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