invoice_processing · workflow
TMNZ saves 400 hours per month and runs 150,000 monthly workflow executions with n8n agentic AI
TMNZ needed a self-hostable, secure workflow automation platform that non-technical staff could use without heavy training while giving engineers fine-grained control — requirements that Zapier, Make, MuleSoft, and the Microsoft suite could not meet simultaneously.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Staff submits automation request
More than a third of TMNZ staff initiate n8n workflows spanning market research, HR, finance, and operations.
Tools used
n8nOpenAI · partnerAzure · partnerPostgreSQL · partnervector storesOpen WebUI
Outcome
n8n is now used by more than a third of TMNZ staff, running around 150,000 executions per month and saving 400 hours per month, with AI POCs saving up to an hour per execution; TMNZ is scaling toward one million executions per month.
What failed first
Zapier and Make could only automate isolated workflows and were heavily limited in scope; MuleSoft and the Microsoft suite were either not self-hostable or cost-prohibitive for a 60-person Fintech.
Results
Time savedaround 150,000
Volumeup to an hour
Grounding & classification
Source type: vendor customer story
35 fields verified against source quotes.
agentic workflowai agentdata extractionmulti agent workflowinvoicefailure mode describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedfinancial servicesemployee productivitythroughput increasetime savedvendor customer storyback office opsfinance opshr opsinvoice processingmarketing opsagentic task executiondata sync enrichment