Kled: Everyday Writing
Collection
Text people wrote for their own reasons, contributed by the author: emails, notes, reviews, recipes, how-to guides, support threads, code. • 13 items • Updated
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Dataset Card for Permissioned Workplace Documents
Memos, reports and plans shared with permission by verified business users in 36 Western countries, tagged by type.
Collected through the Kled app by consenting contributors and licensed for commercial training. The files are delivered by Kled under license, not downloaded from this repository. Use Request a sample set at the top of this page, or write to team@kled.ai. Catalog entry: kled.ai/datasets/workplace-documents.
Dataset Details
Dataset Description
Contributors verify a business email, confirm they may share the document, paste or upload it with structure intact, and tag its type; anything under NDA or of uncertain permission, and blank templates, are rejected. Eligibility is limited to the US, Canada, the UK, Europe, Australia and New Zealand, one or two documents per contributor. Enterprise writing is a register models handle poorly and the one least present in open corpora, because it lives inside companies; the use is enterprise document understanding, professional-register generation and workplace assistants that need to see what a real internal memo or status report looks like, not a model's idea of one. The task is permission-gated by design.
- Curated by: Kled (useKled)
- Collected through: Typed in the Kled app
- Language(s): English, French, German, Spanish, Italian, Dutch
- Regions: US, Canada, UK, Europe, Australia and New Zealand (36 countries)
- Volume: Available on request
- Contributors: Available on request
- Modality: Text
- Format: Plain text
- Resolution: Plain text, UTF-8
- Annotations: Labeled (document type)
- Quality control: QA review on every submission
- License: Non-exclusive commercial training license (terms); exclusivity available on request
- Consent: Each contributor opted in to this use when they uploaded.
Dataset Sources
- Catalog page: kled.ai/datasets/workplace-documents
- Sample set: through the access request at the top of this page, or team@kled.ai
- Publisher: huggingface.co/useKled
Uses
Direct Use
- Enterprise document understanding
- Professional-register generation
- Workplace assistant training
Out-of-Scope Use
Redistribution or resale of the files, use outside the terms of the commercial training license, and any attempt to identify or contact contributors or people who appear in the data. Uses that require labels this set does not carry should be scoped with the data team first.
Dataset Structure
Data Instances
One document per record, delivered as Plain text. Volume: Available on request.
Data Fields
- File: the Plain text file as captured or uploaded by the contributor
- Labels: Labeled (document type), entered by the contributor at capture and checked at review.
- Capture metadata: capture tool, country of capture, submission time
- Review status: QA outcome (QA review on every submission)
Field names and the manifest format are confirmed with the sample set.
Data Splits
Delivered as one set. Subsets by country, language or label, and custom splits, are available on request.
Dataset Creation
Curation Rationale
The dataset exists because the public alternatives named in the description are non-commercial, synthetic, small or collected elsewhere. Kled runs the task as a paid brief in its app so that the data is captured on purpose, under the capture rules above, by people who have opted in to commercial use.
Source Data
Data Collection and Processing
Contributors complete the task in the Kled app. Capture tool: Typed in the Kled app. Each submission is reviewed against the task brief; submissions that break the capture rules are rejected. QA review on every submission. Files are delivered as Plain text, in the resolution noted above.
Who are the source data producers?
Kled contributors, who complete paid data tasks on their own phones. This task was open to contributors in the US, Canada, the UK, Europe, Australia and New Zealand (36 countries). Kled has 625,000+ contributors in 100+ countries, strongest in Southeast Asia, the United States and Europe.
Annotations
Annotation process
Labeled (document type). The label is entered by the contributor as part of the task and checked at review against the task brief; it is a contributor label, not an expert annotation, unless the description above says otherwise.
Who are the annotators?
The contributors themselves, at the moment of capture. Kled reviewers check each submission against the task brief.
Personal and Sensitive Information
Every item was contributed by its owner, who opted in to this use at upload. The task brief states what may and may not appear in a submission, and reviewers reject submissions that break those rules. Kled's data handling practices are documented at trust.kled.ai; questions about handling requirements for your use go to team@kled.ai.
Bias, Risks, and Limitations
Coverage follows the contributor base: strongest in Southeast Asia, the United States and Europe, thinner elsewhere, and limited to the US, Canada, the UK, Europe, Australia and New Zealand (36 countries) for this task. Devices, settings and conditions vary by contributor, which is the point of the collection and also means no two items are captured under identical conditions. Where labels are contributor-entered, they are checked at review but are not expert annotations. Volumes are the current scope of the task and grow as collection continues.
Recommendations
Request a sample set and run it against your task before licensing. Ask for per-country or per-language counts where they matter to your use.
Licensing Information
Non-exclusive commercial training license; exclusivity on request. Each contributor opted in to this use when they uploaded. The license terms are on the catalog page.
Citation
@misc{kled_workplace_documents_2026,
title = {Permissioned Workplace Documents},
author = {Kled},
year = {2026},
url = {https://www.kled.ai/datasets/workplace-documents},
note = {Commercially licensed dataset collected through the Kled app. Sample sets on request.}
}
Dataset Card Contact
Kled data team: team@kled.ai
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