Verified Data Provenance for AI
In an era of copyright lawsuits and regulatory scrutiny, knowing exactly where your training data came from is not a luxury—it is a compliance necessity. We deliver 100% auditable datasets.
Our Sourcing Methodology
NLP Consultancy avoids unauthorized web scraping. Every dataset we supply is collected, curated, and licensed through governed channels that provide absolute legal clarity to the buyer.
Licensed Acquisition
We partner directly with publishers, archives, and institutional repositories to acquire commercial licensing rights for foundational text and document corpora.
Opt-In Direct Collection
For speech, vision, and human preference (RLHF) data, we utilize a global network of paid contributors who provide explicit, documented opt-in consent for their data to be used in AI training.
PII Sanitization
Before delivery, all datasets pass through a rigorous anonymization pipeline to detect and redact Personally Identifiable Information (PII) according to GDPR and CCPA standards.
The Data Card Guarantee
We advocate for complete transparency. Following the industry-standard "Data Card" frameworks (such as those proposed by Google and Hugging Face), NLP Consultancy provides a detailed manifest with every dataset delivery.
- ✓ Demographics of data contributors
- ✓ Collection methodology and environment conditions
- ✓ Hardware specifications (for speech/vision data)
- ✓ Explicit commercial licensing terms and constraints
{
"dataset_id": "nlpc_audio_en_uk_01",
"domain": "Conversational Speech",
"provenance": {
"collection_method": "Opt-in direct recording",
"consent_verified": true,
"pii_scrubbed": true
},
"licensing": {
"commercial_use": "Permitted",
"distribution": "Internal training only",
"attribution_required": false
},
"demographics": {
"locale": "en-GB",
"accents": ["RP", "Northern", "Scottish", "Welsh"],
"gender_split": "49% F, 50% M, 1% Non-binary"
}
} Require Custom Sourcing?
Speak to our data engineering team about your specific compliance requirements, geographic targeting, or domain specificity.
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