Architect field instruction intake
For Construction field document coordinators
Prepare project, issuer, issue date and instructed scope from a field instruction with fields you can edit. Contract impact external.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- project name
- Example Community Workshop - synthetic
- instruction reference
- DEMO-INSTRUCTION-0042
- issuer name
- Example Issuer - synthetic
- issue date
- 2026-09-30
- instruction text
- Instruction text explicitly printed in the original synthetic source for reviewer context.
- drawing references
- Drawing references explicitly printed in the original synthetic source for reviewer context.
{
"project_name": "Example Community Workshop - synthetic",
"instruction_reference": "DEMO-INSTRUCTION-0042",
"issuer_name": "Example Issuer - synthetic",
"issue_date": "2026-09-30",
"instruction_text": "Instruction text explicitly printed in the original synthetic source for reviewer context.",
"drawing_references": "Drawing 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 field instruction arrives for construction field document coordinators. The next step needs project, issuer, issue date and instructed scope, recorded under the correct document reference before the information enters your project document review register.
A field instruction references a drawing revision and says cost impact is pending. Keep those statements before contract administration 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
- Field instruction PDFs
- Scanned or photographed field instruction 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 project name, instruction reference, issuer name, your application maps the reviewed record into your project document review register. Keep the original document reference with the result. Contract impact 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 |
|---|---|---|
project_name | string | Project name exactly as printed in this field instruction. Preserve identifiers and qualifiers; do not look up or infer missing information. |
instruction_reference | string | Instruction reference exactly as printed in this field instruction. Preserve identifiers and qualifiers; do not look up or infer missing information. |
issuer_name | string | Issuer name exactly as printed in this field instruction. Preserve identifiers and qualifiers; do not look up or infer missing information. |
issue_date | date | Issue date explicitly printed in this field instruction. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
instruction_text | string | Instruction text exactly as printed in this field instruction. Preserve identifiers and qualifiers; do not look up or infer missing information. |
drawing_references | string | Drawing references exactly as printed in this field instruction. 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 field instruction references a drawing revision and says cost impact is pending. Keep those statements before contract administration review.
- Check issue date against their own printed labels; leave an unstated date empty instead of deriving it.
- Resolve missing project name, instruction reference, issuer name against the source before using the record.
Prove the fit on a representative batch.
Test field instruction examples from the layouts your team actually receives. Include the exception described here: A field instruction references a drawing revision and says cost impact is pending. Keep those statements before contract administration review. Compare the extracted project name, instruction reference, issuer name 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 field instruction 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 construction field document coordinators. Bring difficult field instruction 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 architect field instruction intake
Which fields can I capture from a field instruction?
The starter schema contains project name, instruction reference, issuer name, issue date, instruction text, drawing 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 architect field instruction intake?
A field instruction references a drawing revision and says cost impact is pending. Keep those statements before contract administration 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 project document review register?
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. Contract impact 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.