Sourcing option
Business documents for document AI
Scope authentic business document sourcing for extraction, classification, and layout understanding.
Documents · Tables · Business context
Business data.
With the context intact.
Invoices, reports, operational records, and structured tables become useful when their meaning travels with them. Start with the business question your model needs to answer.
A direct line to Fiund. Source fit and permissions reviewed for your project.
A sourcing conversation
Built around the specification.
Record definitionWhat one document, row, or case represents
CoverageCountries, languages, industries, date ranges, document families, and layout diversity
Data dictionaryField meanings, units, missing-value conventions, stable identifiers, and provenance information
Category map
FIELD NOTES / BUS01 — SOURCING
Define the signal.Then source the data.
Illustrative structure · source requirements vary by project
Your first step
A useful brief, before a file transfer.
Document types or table schemas. Ground truth and sensitive-data requirements.
Outline your project →Task-first scope
Specify the outcome your model needs.
Source context
Keep file meaning and lineage connected.
Reviewable quality
Agree on evidence and acceptance criteria.
Direct conversation
Speak with Jaeden at Fiund.
Dataset solutions
Find the right source for the model task.
Sourcing option
Enterprise retrieval and grounded answers
Plan source documents, business questions, and citation evidence for enterprise search evaluation.
Sourcing option
Structured business records and linked tables
Specify rows, entities, dictionaries, and relationships for tabular business AI workflows.
Sourcing option
Business AI evaluation datasets
Design held-out business examples with expected outputs, source evidence, and meaningful failure slices.
Sourcing option
Procurement and operational document workflows
Plan linked operational artifacts for reconciliation, routing, and business process understanding.
Category context
Different sources. Different review questions.
Business documents
Invoices, purchase orders, shipping records, policies, and reports. Specify authentic versus synthetic requirements, document types, origin, language, and layout variation.
Structured business records
Tables, catalogs, and operational exports. Describe the unit represented by a row, the fields you require, date coverage, and relationships between files.
Enterprise evaluation sets
Examples for classification, extraction, or retrieval testing. Define the expected answer, acceptable evidence, and how sensitive details should be handled.
Why the details matter
Better data starts with a better definition.
Business datasets span more than spreadsheets. A document classification project may need varied layouts and languages; an extraction project may need field-level ground truth; an enterprise benchmark may depend on relationships between records. This Fiund site helps buyers turn those different needs into a specific sourcing inquiry.
Explore quality & provenance →Specification essentials
01Record definition
02Coverage
03Data dictionary
04Sensitive information
Technical scope
Specify the collection before counting the volume.
Record definition
What one document, row, or case represents; how related records are grouped.
Coverage
Countries, languages, industries, date ranges, document families, and layout diversity.
Data dictionary
Field meanings, units, missing-value conventions, stable identifiers, and provenance information.
Sensitive information
Required removal or replacement of personal, confidential, financial, and account-level details.
How sourcing works
From the first brief to a reviewable handoff.
01 / PROJECT STAGE
Define the target
Business datasets span more than spreadsheets. A document classification project may need varied layouts and languages; an extraction project may need field-level ground truth; an enterprise benchmark may depend on relationships between records. This Fiund site helps buyers turn those different needs into a specific sourcing inquiry.
02 / PROJECT STAGE
Write the specification
Document types or table schemas; Languages, regions, and date coverage; Volume by category; Ground truth and sensitive-data requirements; Intended use and licensing scope. These details establish the project’s review criteria and reveal where further clarification is needed.
03 / PROJECT STAGE
Review sourcing fit
Discuss which existing sources or collection approaches could address the brief. Identify access constraints, source documentation, and unanswered permission questions before treating a category as usable inventory.
04 / PROJECT STAGE
Inspect representative material
Where appropriate material can be shared, agree on handling and inspect it against the specification. Record defects, coverage gaps, and annotation questions against exact source identifiers.
05 / PROJECT STAGE
Agree the project scope
Confirm the selected material, intended uses, preparation work, acceptance criteria, commercial terms, and delivery arrangements in a project-specific agreement.
06 / PROJECT STAGE
Review the handoff
Check file references, manifests, documented processing, and accepted exceptions. Keep permission review and technical acceptance explicit, and resolve open issues before the collection is treated as approved for the intended use.
Field notes
Practical reading for a sharper brief.
Resource guide
Building an invoice extraction evaluation set
Specify invoice fields, layout variation, and evidence so extraction results mean something beyond a headline accuracy number.
Resource guide
Purchase orders and invoices: designing linked document datasets
Plan a document set that tests reconciliation across purchase orders, invoices, and receiving records.
Resource guide
What belongs in a business dataset dictionary
A practical field guide to names, meanings, units, permitted values, and missingness in business records.
Resource guide
Checking joins before buying business tables
Assess key uniqueness, unmatched records, and cardinality before treating related tables as a usable dataset.
Resource guide
Measuring layout diversity in business documents
Turn “varied documents” into a measurable sampling plan for document understanding.
Resource guide
Designing enterprise retrieval datasets with answer evidence
Connect business questions to specific source passages and clear answerability decisions.
Common questions
Before you source.
Can I request genuine business documents?
Yes. State that authentic records are required, and identify acceptable origins and document types. Sourcing fit, permissions, confidentiality, and de-identification need review for each collection.
Should I ask for raw files or extracted tables?
That depends on the task. Layout understanding may need original documents; structured analysis may need normalized records. If you need both, specify how each extracted record must link back to its source.
Are all categories available in the same volume?
No volume is promised on this site. Send your required counts by category so Jaeden can discuss availability and sourcing options without treating a broad category label as confirmed inventory.