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Material safety data sheet indexing

For Safety data sheet document administrators

Prepare product, manufacturer, revision and stated hazard classifications from an sds with fields you can edit. Safety interpretation external.

25 free credits/month · No card needed

See the workflow and review checks

Inspect a document example.

Synthetic documents · Expected output
Standard documentPDF
material safety data sheet indexingFictional sample · For demonstration
product name
Example demonstration product
manufacturer name
Example Manufacturer - synthetic
revision date
2026-09-30
document reference
DEMO-DOCUMENT-0042
hazard text
Hazard text explicitly printed in the original synthetic source for reviewer context.
precaution text
Precaution text explicitly printed in the original synthetic source for reviewer context.
emergency contact text
Example emergency contact details are omitted from this public fixture.
{
  "product_name": "Example demonstration product",
  "manufacturer_name": "Example Manufacturer - synthetic",
  "revision_date": "2026-09-30",
  "document_reference": "DEMO-DOCUMENT-0042",
  "hazard_text": "Hazard text explicitly printed in the original synthetic source for reviewer context.",
  "precaution_text": "Precaution text explicitly printed in the original synthetic source for reviewer context.",
  "emergency_contact_text": "Example emergency contact details are omitted from this public fixture."
}

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

An sds arrives for safety data sheet document administrators. The next step needs product, manufacturer, revision and stated hazard classifications, recorded under the correct document reference before the information enters your quality or production document register.

An SDS has a revision date and a separate print date. Capture the revision and the stated hazard text for qualified 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

  • SDS PDFs
  • Scanned or photographed sds pages

PDF, JPEG, PNG, TIFF, or WEBP. Send one file per extraction call; create separate schemas when the document types need different fields.

  1. Define the fields

    Open the starter schema. Edit field descriptions, mark the values your process requires, and save it in your account.

  2. Extract at intake

    Send the document and saved schema slug to POST /api/v1/extract, or collect the file through a branded upload site.

  3. Hand off reviewed data

    After checking product name, manufacturer name, revision date, your application maps the reviewed record into your quality or production document register. Keep the original document reference with the result. Safety interpretation 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 schema

Choose required fields for your process. The starter schema preserves any defined nested fields; refine line-item structures and test them on representative files.

FieldTypeWhat to capture
product_namestringProduct name exactly as printed in this sds. Preserve identifiers and qualifiers; do not look up or infer missing information.
manufacturer_namestringManufacturer name exactly as printed in this sds. Preserve identifiers and qualifiers; do not look up or infer missing information.
revision_datedateRevision date explicitly printed in this sds. Keep it distinct from other dates; leave it empty if no calendar date is stated.
document_referencestringDocument reference exactly as printed in this sds. Preserve identifiers and qualifiers; do not look up or infer missing information.
hazard_textstringHazard text exactly as printed in this sds. Preserve identifiers and qualifiers; do not look up or infer missing information.
precaution_textstringPrecaution text exactly as printed in this sds. Preserve identifiers and qualifiers; do not look up or infer missing information.
emergency_contact_textstringEmergency contact text exactly as printed in this sds. 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 contract

Run a synthetic response through a review gate

Checks for this process

  • An SDS has a revision date and a separate print date. Capture the revision and the stated hazard text for qualified review.
  • Check revision date against their own printed labels; leave an unstated date empty instead of deriving it.
  • Resolve missing product name, manufacturer name, revision date against the source before using the record.

Prove the fit on a representative batch.

Test sds examples from the layouts your team actually receives. Include the exception described here: An SDS has a revision date and a separate print date. Capture the revision and the stated hazard text for qualified review. Compare the extracted product name, manufacturer name, revision 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 sds 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 safety data sheet document administrators. Bring difficult sds samples and the review requirements your implementation must preserve.

Talk through document mix and volume

Start 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.

Free

$0/month

  • 25 credits/month
  • 2 schemas
  • 1 branded upload site
Test this workflow

Starter

$99/month

  • 500 credits/month
  • 10 schemas
  • 5 branded upload sites
Explore Starter

Growth

$499/month

  • 3,000 credits/month
  • 50 schemas
  • 25 branded upload sites
Explore Growth

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 material safety data sheet indexing

Which fields can I capture from an sds?

The starter schema contains product name, manufacturer name, revision date, document reference, hazard text, precaution text, emergency contact text. 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 material safety data sheet indexing?

An SDS has a revision date and a separate print date. Capture the revision and the stated hazard text for qualified 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 quality or production 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. Safety interpretation 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.