Legal demand letter intake
For Legal correspondence intake teams
Prepare parties, alleged issue, requested remedy and deadline from a demand letter with fields you can edit. Response advice external.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- sender name
- Example Sender - synthetic
- recipient name
- Example Recipient - synthetic
- letter date
- 2026-09-30
- matter reference
- DEMO-MATTER-0042
- requested remedy text
- Review and respond to the stated request.
- demanded amount
- 1250
- stated deadline
- 2026-11-30
{
"sender_name": "Example Sender - synthetic",
"recipient_name": "Example Recipient - synthetic",
"letter_date": "2026-09-30",
"matter_reference": "DEMO-MATTER-0042",
"requested_remedy_text": "Review and respond to the stated request.",
"demanded_amount": 1250,
"stated_deadline": "2026-11-30"
}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 demand letter arrives for legal correspondence intake teams. The next step needs parties, alleged issue, requested remedy and deadline, recorded under the correct document reference before the information enters your contract document register.
A demand sets a response period in words instead of a calendar date. Preserve the exact text rather than calculating a legal deadline. 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
- Demand letter PDFs
- Scanned or photographed demand letter 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 sender name, recipient name, letter date, your application maps the reviewed record into your contract document register. Keep the original document reference with the result. Response advice 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 |
|---|---|---|
sender_name | string | Sender name exactly as printed in this demand letter. Preserve identifiers and qualifiers; do not look up or infer missing information. |
recipient_name | string | Recipient name exactly as printed in this demand letter. Preserve identifiers and qualifiers; do not look up or infer missing information. |
letter_date | date | Letter date explicitly printed in this demand letter. Keep it distinct from other dates; leave it empty if no calendar date is stated. |
matter_reference | string | Matter reference exactly as printed in this demand letter. Preserve identifiers and qualifiers; do not look up or infer missing information. |
requested_remedy_text | string | Requested remedy text exactly as printed in this demand letter. Preserve identifiers and qualifiers; do not look up or infer missing information. |
demanded_amount | currency | Amount requested by the sender, not an agreed debt, liability or settlement. |
stated_deadline | date | Calendar deadline only when explicitly printed. Preserve relative wording in a text field for review. |
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 demand sets a response period in words instead of a calendar date. Preserve the exact text rather than calculating a legal deadline.
- Check letter date, stated deadline against their own printed labels; leave an unstated date empty instead of deriving it.
- Check demanded amount for signs, decimal placement and stated currency before any downstream calculation or posting.
Prove the fit on a representative batch.
Test demand letter examples from the layouts your team actually receives. Include the exception described here: A demand sets a response period in words instead of a calendar date. Preserve the exact text rather than calculating a legal deadline. Compare the extracted sender name, recipient name, letter date 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 demand letter 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 legal correspondence intake teams. Bring difficult demand letter 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 legal demand letter intake
Which fields can I capture from a demand letter?
The starter schema contains sender name, recipient name, letter date, matter reference, requested remedy text, demanded amount, stated deadline. 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 legal demand letter intake?
A demand sets a response period in words instead of a calendar date. Preserve the exact text rather than calculating a legal deadline. 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 contract document 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. Response advice 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.