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Licensed text foundation
All content is fully licensed, linked to rightsholders, and governed by explicit usage terms.
No scraped or unverifiable data enters the system.
Text Partnerships
Transparent influence tracing for trustworthy text generation
Bria’s text attribution brings traceability, provenance, and revenue sharing to text AI.
It identifies which licensed works meaningfully shaped an output, without exposing or reproducing those works.
The result: a rights-clean, auditable alternative to scraped-data LLMs.
Why Text Attribution Matters
Attribution is trust
Most text AI today is built on scraped web data. That creates:
No provenance: You cannot see which sources shaped an output.
No accountability: Rightsholders do not participate in the value their work creates.
No legal clarity: Enterprises face copyright, compliance, and IP risk.
Lower reliability: Unvetted sources introduce errors, bias, and factual instability
Text attribution is not about optics. It is how you build safer, more reliable, more trusted text models.
What Bria delivers
Most text AI today is built on scraped web data. That creates:
Rights-clean
Traceable
Auditable
Monetizable
Aligned with enterprise and regulatory expectations
Across training, retrieval, and tool-based generation.
How it works
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Concept-level attribution
Text is analyzed at the level of meaning, structure, style, and factual contribution, not verbatim copying.
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Real-time influence analysis
As text is generated, Bria measures which sources contributed meaningfully to the result and records a stable attribution vector.
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Impact-based compensation
Rightsholders earn based on measured influence, not catalog size or volume.
Works across modern AI architectures
Bria applies attribution wherever text influences outputs:
• Foundation and domain-specific model training
• Retrieval-Augmented Generation (RAG)
• Tool-based workflows, including MCP
• Fine-tuning and supervised adaptation
Attribution persists as models evolve.
Why Bria’s text attribution Is different
Fair - Compensation tied to real influence
Transparent - Reproducible attribution for every output
Rights-clean - Licensed data only
Publisher-controlled - Terms can be updated or revoked
Enterprise-safe - Built for audit, compliance, and scale
Who It’s For
Publishers & News Organizations - New recurring revenue. Protection of editorial investment.
Authors & Book Rightsholders - Compensation for conceptual and stylistic influence without exposing manuscripts.
Enterprises - Clear provenance, licensing boundaries, and reduced legal risk.
Built for a licensed-data future
The industry is moving from scraped, opaque datasets to licensed, attributed systems.
Text attribution is the infrastructure that makes this shift sustainable:
economically, legally, and technically.
Become a Text Data Partner
If you operate a catalog of journalism, books, educational content, transcripts, or expert domain text, Bria can unlock new recurring revenue.
Receive a free assessment of your catalog’s influence potential and projected earnings.