Supplier onboarding questionnaire capture
For Supplier diligence intake coordinators
Prepare ownership declarations, operations and stated risks from a due-diligence questionnaire with fields you can edit. Assessment external.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- supplier name
- Example Supply Company - synthetic
- response date
- 2026-11-30
- ownership rows
- [ { "owner_name": "Example Owner - synthetic", "ownership_percentage": 100, "ownership_type": "Example ownership type - synthetic" } ]
- operations text
- Operations text explicitly printed in the original synthetic source for reviewer context.
- declared risks
- [ { "question_reference": "DEMO-QUESTION-0042", "question_text": "Please confirm the referenced supporting document.", "response_text": "Submitted response refers to the named attachment.", "attachment_reference": "DEMO-ATTACHMENT-0042" } ]
- attachment references
- Attachment references explicitly printed in the original synthetic source for reviewer context.
{
"supplier_name": "Example Supply Company - synthetic",
"response_date": "2026-11-30",
"ownership_rows": [
{
"owner_name": "Example Owner - synthetic",
"ownership_percentage": 100,
"ownership_type": "Example ownership type - synthetic"
}
],
"operations_text": "Operations text explicitly printed in the original synthetic source for reviewer context.",
"declared_risks": [
{
"question_reference": "DEMO-QUESTION-0042",
"question_text": "Please confirm the referenced supporting document.",
"response_text": "Submitted response refers to the named attachment.",
"attachment_reference": "DEMO-ATTACHMENT-0042"
}
],
"attachment_references": "Attachment references explicitly printed in the original synthetic source for reviewer context."
}A complete synthetic document with the visible values shown below. Real responses also include model-reported confidence, validation and result status. Test your own file with this schema.
When this work lands on your desk
A due-diligence questionnaire arrives for supplier diligence intake coordinators. The next step needs ownership declarations, operations and stated risks, recorded under the correct document reference before the information enters your supplier or purchasing review queue.
A supplier declares a related-party relationship in an attachment. Retain the source reference for a human diligence review. This schema keeps the source labels and values explicit so the reviewer can resolve the issue before downstream use.
Start with the documents you already collect
- Due-diligence questionnaire PDFs
- Scanned or photographed due-diligence questionnaire pages
PDF, JPEG, PNG, TIFF, or WEBP. Send one file per extraction call; create separate schemas when the document types need different fields.
Define the fields
Open the starter schema. Edit field descriptions, mark the values your process requires, and save it in your account.
Extract at intake
Send the document and saved schema slug to
POST /api/v1/extract, or collect the file through a branded upload site.Hand off reviewed data
After checking supplier name, response date, ownership rows, your application maps the reviewed record into your supplier or purchasing review queue. Keep the original document reference with the result. Assessment external. Dokyumi processes one file with a saved schema; your application owns record matching, business rules and updates to other systems.
A schema shaped around the next step.
Start with these fields, then adjust them to match your documents and destination system. The example above shows the data object you are asking Dokyumi to extract.
Download editable starter schemaChoose required fields for your process. The starter schema preserves any defined nested fields; refine line-item structures and test them on representative files.
| Field | Type | What to capture |
|---|---|---|
supplier_name | string | Supplier name exactly as printed in this due-diligence questionnaire. Preserve identifiers and qualifiers; do not look up or infer missing information. |
response_date | date | Response date explicitly printed in the source. Do not calculate a deadline from a relative period; preserve that wording for review. |
ownership_rows | array | Every visible ownership rows row in this due-diligence questionnaire. Preserve separate rows, labels and qualifiers; do not merge entries or reconstruct missing ones. |
operations_text | string | Operations text exactly as printed in this due-diligence questionnaire. Preserve identifiers and qualifiers; do not look up or infer missing information. |
declared_risks | array | Every visible declared risks row in this due-diligence questionnaire. Preserve separate rows, labels and qualifiers; do not merge entries or reconstruct missing ones. |
attachment_references | string | Attachment references exactly as printed in this due-diligence questionnaire. Preserve identifiers and qualifiers; do not look up or infer missing information. |
Give exceptions a clear path to review.
Dokyumi returns a model-reported confidence map, validation details, and a completed or review status for produced results. Check required fields and your business rules before passing data onward.
A completed extraction describes the extraction result. Your application and reviewers own matching, approvals, routing, and updates to other systems.
Read the response contractChecks for this process
- A supplier declares a related-party relationship in an attachment. Retain the source reference for a human diligence review.
- Check response date against their own printed labels; leave an unstated date empty instead of deriving it.
- Compare every ownership rows, declared risks row with the source, including continuation pages, separate categories and repeated table headings.
Prove the fit on a representative batch.
Test due-diligence questionnaire examples from the layouts your team actually receives. Include the exception described here: A supplier declares a related-party relationship in an attachment. Retain the source reference for a human diligence review. Compare the extracted supplier name, response date, ownership rows and any line rows with a reviewer's checked reference before enabling downstream actions.
Compare extracted values with a reviewer’s reference set. Record corrections, unresolved fields, review time, and credits used before connecting downstream actions.
The free plan’s credit limits apply. Assisted pilots are scoped with Dokyumi before work begins.
Expand when the next process is ready
Add recurring extraction capacity when due-diligence questionnaire intake becomes routine. Reuse this field contract for layouts that express the same information; create a separate schema when the next document has different fields or review requirements.
For a tailored implementation
Discuss document volume, page lengths and schema setup for supplier diligence intake coordinators. Bring difficult due-diligence questionnaire samples and the review requirements your implementation must preserve.
Talk through document mix and volumeStart small. Add capacity as intake grows.
All self-service plans include the REST API, upload-site webhooks, custom confidence thresholds, and schema inference. Choose by volume, schema count, and upload sites.
Each document uses one credit per 5 pages, rounded up. An 8-page file uses 2 credits. Self-service files can be up to 50 pages; larger files, custom-built schemas, and additional volume are quoted through Enterprise. Full pricing details
Questions about supplier onboarding questionnaire capture
Which fields can I capture from a due-diligence questionnaire?
The starter schema contains supplier name, response date, ownership rows, operations text, declared risks, attachment references. Edit those definitions and choose your required fields before saving. Array fields include defined sub-fields so row values have a validation structure.
What needs review in supplier onboarding questionnaire capture?
A supplier declares a related-party relationship in an attachment. Retain the source reference for a human diligence review. Check the original source alongside model-reported confidence and validation output; completion status describes the extraction result, not the business decision.
How does this data reach your supplier or purchasing review queue?
Save the schema, then send one supported PDF or image to POST /api/v1/extract with its slug. The response contains the data, model-reported confidence, validation and result status. Your application maps reviewed values to the destination; upload-site submissions can use a configured webhook. Assessment external.
How do I test this workflow on my own documents?
Start free with 25 credits per month, 2 schemas, and 1 branded upload site. The starter schema opens in the schema builder after sign-up. Edit the fields, save it, and upload a representative file through your account or the extraction API. Account documents are stored according to Dokyumi’s privacy policy; contact hello@dokyumi.com for deletion requests and retention requirements.