Workflow automation and ERP integration
A pipeline from inbox to ERP includes the validation layer and the handling for everything that does not parse cleanly, which is where most of the real work is. We scope it against your actual documents rather than a template.
- Scope
- One pipeline end to end, or an integration layer
- Typical
- Four to seven weeks end to end
- Runs on
- Self-hosted, so records never reach a SaaS vendor
- Start
- Free scope and a fixed price in three business days
FAST Workflows absorb the repeat work that used to need a person.
GOOD A strict schema decides what passes. The model never gets the last word.
REACHABLE It pays for itself in the hours it stops costing you.
What we build
Extraction that is allowed to be wrong
A language model reads the order email, the attached spreadsheet, or the scanned document and proposes a structured record. It is treated as a proposal throughout. Nothing it produces reaches your ERP without passing a schema that was written independently of the model.
A schema with the final say
Types, required fields, value ranges, and cross-field rules are checked before anything is written. A record that fails is not repaired by asking the model again; it goes to a person with the original document attached. This is the difference between automation you can audit and automation you have to supervise.
Failure handling as a first-class path
Transient errors retry with backoff. Ambiguous records queue for review. Every run leaves a trace linking the final record back to the input it came from, so a disputed line item can be traced to the email that produced it months later.
How we approach it
The interesting part of this work is not the extraction. Getting a model to read an invoice is close to solved. The part that decides whether the system is trustworthy is what happens to the twelve percent it reads wrong.
So the design starts from the failure path. What must never be auto-written, what routes to a person, what a reviewer sees when it does, and how a wrong record is traced back and corrected. Build that first and the happy path is straightforward.
Questions on this work
n8n, Zapier, or Make for ERP integration?
n8n, if the integration touches data you care about. It self-hosts, so your records never reach a SaaS vendor, and it handles branching, retries, and custom code without hitting a task ceiling. Zapier is better for simple software-to-software triggers where speed of setup beats control. Make sits between the two and is a reasonable middle choice for teams that want a visual builder without self-hosting.
How do you stop a language model from writing bad data into our ERP?
By never letting the model write. It proposes a structured record, and a schema written independently of it decides what is allowed through: types, required fields, value ranges, and cross-field rules. Anything that fails validation goes to a person with the source document attached rather than being retried until it passes. The model is a reader, not an authority.
What happens when the automation gets something wrong?
It gets caught at the schema and queued for review, and the record is traceable back to the document that produced it. The failure worth designing against is not the obviously wrong record, it is the plausible one, which is why validation checks business rules rather than only shape. Expect a review queue permanently; a pipeline claiming to need none is either simple or unaudited.