Sainapse turns purchase orders into sales orders in Oracle
Avery Dennison receives purchase orders from more than 10,000 downstream customers. Layouts shift by supplier, languages shift by region, and every one of them has to end up as a sales order in Oracle CPQ. Sainapse reads the incoming PO in whatever format it arrives, extracts the fields, validates them against Oracle master data, and writes the sales order. Agents now review the ~5% Sainapse flags as low confidence.
The challenge
Templates do not work on Avery Dennison's PO inbox. PDFs, Excel files, scanned images, and free-text email bodies all land in the same queue. Field names change from supplier to supplier.
Languages change from region to region. Writing a new template for every format was never going to keep up, so the team did the work by hand: 15+ minutes per PO to read it, check the fields against Oracle master data, and type the sales order.
Downstream, the error rate stayed steady.
What Sainapse delivered
Format-Agnostic Ingestion pulls PDFs, Excel files, scans, and email bodies into one pipeline. Intelligent Field Extraction reads each document in context and returns every field with a confidence score.
Master Data Mapping & Validation fuzzy-matches supplier names, product codes, and ship-to addresses against Oracle LOV tables. End-to-End System Write posts a schema-correct payload directly into Oracle CPQ.
Low-confidence cases route to a human reviewer, and every correction feeds back into the model.
What changed in production.
Manual intervention rate
~5% manual intervention rate in production.
10,000+ downstream customer formats
Read as they arrive, with no templates to build and no data to clean up first.
Inbox to Oracle CPQ
With no person in the middle for 95% of POs.
Accuracy improves with use
As every reviewer correction feeds back into the model.
The pieces behind the order pipeline.
Six shipped capabilities, from ingestion through the Oracle write. Each has its own page.
- Workflow overview
Where ingestion, extraction, and the write fit together.
- Intelligent Field Extraction
Reads each PO in context, with a confidence score per field.
- Format-Agnostic Ingestion
Pulls PDFs, Excel files, scans, and email bodies into one pipeline.
- Master Data Mapping & Validation
Fuzzy-matches supplier names, product codes, and ship-to addresses against Oracle.
- End-to-End System Write
Posts the schema-correct payload directly into Oracle CPQ.
- Human-in-the-Loop Exception Handling
Low-confidence cases route to a person instead of into Oracle.
- All customer stories
Named deployments and what they measured.
Related deployment
Avery Dennison: email to service request
Sainapse also runs the service email channel: 300,000 emails a day, triaged and resolved into Oracle Service Cloud.
Use casePurchase order automation
The use case this deployment proves: reading a PO in any format, validating it against master data, and writing the sales order.