Start with origin and coverage.
Describe what exists, how it was captured and which source relationships the task requires.
Data foundations for enterprise AI
Better business AI
starts with
connected data.
Bring documents, structured records and workflow evidence into one clear project specification. Find the source material your model needs to move forward.
Explore business datasetsIN FOCUS
SOURCE & FORMATFrom isolated records
Explore an illustrative procurement example →
SOURCE & FORMAT
From isolated records
to a connected workflow.
Explore an illustrative procurement example →A focused path from brief to pilot.
Define the task. Review source fit. Agree the scope, permissions and acceptance criteria for your project.
How it works →Built around your model
Different tasks.
The right starting point.
Choose a use case to explore its source, reference and delivery requirements. Availability is confirmed for the selected project.
Project blueprintCustom project
Enterprise retrieval & evidence
- Source material
- Coherent document collections with source relationships
- Reference & annotations
- Answer evidence, document IDs and access/revision context
- Delivery scope
- Document manifest, retrieval questions and review records
A closer look
Explore the format.
Keep the context.
A purchase order, receipt and invoice can be read together to expose an exception. The authored example distinguishes a quantity mismatch from a payment decision.
Illustrative procurement records · no company data
Open the walkthrough ↗Business Datasets / INSPECT
Three records. One connected question.business
poPurchase order
DEMO-PO1 · 10 units × $12.00 per unit.
receiptReceipt
DEMO-R1 · 6 units received against the same order line.
invoiceInvoice
DEMO-I1 · 10 units billed; two exports represent the same invoice.
po
Purchase order
DEMO-PO1 · 10 units × $12.00 per unit.
receipt
Receipt
DEMO-R1 · 6 units received against the same order line.
invoice
Invoice
DEMO-I1 · 10 units billed; two exports represent the same invoice.
exception
Evidence-backed exception
Billed quantity exceeds received quantity by 4. Payment authorization is not established by the example.
- Ordered / received
- 10 / 6 units
- Billed before tax
- $120 illustrative
- Quantity difference
- 4 units
A purchase order, receipt and invoice can be read together to expose an exception. The authored example distinguishes a quantity mismatch from a payment decision.
Illustrative procurement records · no company data
More than a folder of files
The details make
the data useful.
Keep the reference meaningful.
Agree what the model sees, what the target means and how a reviewer will inspect the evidence.
Make the handoff interpretable.
Connect the selected material, preparation, accepted units and correction process.
From question to project
A clear path.
A focused next step.
Begin with the decision your model needs to make. Agree the source and its supporting evidence before scaling.
Define the brief
Share the task, target conditions, source needs and essential reference fields.
Review a pilot
Assess representative material and make gaps, preparation and acceptance criteria explicit.
Agree the project
Confirm source scope, permitted use, delivery and commercial terms for the selected material.
The research behind the brief
Go deeper.
Choose with context.
FIELD GUIDE / 01Authentic and synthetic business records: preserve origin and test the intended use
Compare observed records, redacted derivatives, simulations and generated tables with a task-specific source and evaluation ledger.
FIELD GUIDE / 02Business AI evaluation data: build an evidence contract for the decision
Scope business AI tests around decision-time inputs, supported references, source independence and task-specific acceptance.
FIELD GUIDE / 03Business data dictionaries: define grain, units, field meaning and review evidence
Write a business data dictionary with a worked order-line example, explicit monetary and quantity units, nullable fields, constraints and release-level validation.
What is Business Datasets?
Business Datasets is a specialist Fiund website for enterprise documents and linked business workflow records. Its official website is https://businessdatasets.com/. Buyers can discuss a project-specific source, sample and preparation scope with Fiund. The public previews demonstrate material or formats; commercial inventory, permitted use, pricing and delivery are confirmed for the proposed project.
What makes business data usable for AI?
Define the document or row unit, field meanings, source relationships and information available at the decision time. Those requirements determine what a useful pilot must establish.
Can I request a sample?
Yes. Share the model task and the conditions a useful sample should show. The team reviews source fit and sample availability for the project before agreeing any next step.
What does the preview represent?
The preview shows an editorial source or a clearly illustrative record format, with its evidence notes. It does not establish commercial inventory or grant a training-data license.
How is a project priced?
Scope depends on the selected source, intended use, preparation, annotations, accepted units and delivery work. Start with a brief so a project-specific proposal can compare the same requirements.