Process Intelligence Audit · Free Download

Your operations start in Outlook. Your ERP sees half the story. We see all of it.

Everything that happens between your customer's email and your ERP entry is finally visible.

Most breaches do not start in the ERP. They start in the inbox. These audits show exactly where, how long each delay costs, and what fixing the highest-impact bottleneck saves.

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Real enterprise data audit No demo required Sent instantly
Claims Process and Order-to-Cash audit reports
Inside the report

This is what we found in a real operation.

Not a benchmark. Real audits on real claims and order data, sanitized but not simplified, with specific recommendations and expected savings per fix.

Process fragmentation invisible in SAP

How 3,314 claims and 4,514 orders each produced over 1,300 unique process paths, and why traditional reporting makes this invisible until it becomes a customer complaint.

1,314 process paths across one operation

Bottleneck analysis with time costs per loop

Every bottleneck mapped with median duration, case volume, and downstream impact. The highest-cost loops add over 14 hours per return cycle across both processes.

14h 9m added per rework cycle

AI model predictions on your classification data

How Tekst classifies every order topic, language, and business unit automatically, and what that means for routing accuracy before any automation runs.

+90% classification accuracy on live data

Five prioritized recommendations with savings per fix

What to fix first, what each fix saves, and the configuration change required. Including 300 hours recovered annually from automating a single process in each operation.

300h recovered from one automation
Free download

Download the audit report

  • What a week-one process audit reveals that months of ERP reporting missed
  • Why the manual work lives in the inbox, not the system
  • What recoverable hours look like before a single tool is deployed
  • How to sequence automation by impact, not by gut feel
  • What to show your leadership team when the case for change needs data behind it

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