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4.2M preference pairs for frontier LLM alignment
Foundation models · Multi-hub · RLHF & preference data

4.2M preference pairs for frontier LLM alignment

A frontier lab needed high-agreement preference data across reasoning, safety, and multilingual prompts, at a cadence its internal team could not staff.

4.2M
Preference pairs
97%+
Accuracy
3
Hubs engaged
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Swahili & Uzbek TTS cut word error rate from 11.2% to 4.3%
Speech AI · East Africa · Central Asia · Speech & audio datasets

Swahili & Uzbek TTS cut word error rate from 11.2% to 4.3%

A speech team's models underperformed in Swahili and Uzbek because available data was English-first and dialect-blind.

11.2%
WER before
4.3%
WER after
2 dialect-deep
Languages
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LiDAR + camera perception data for an AV program
Autonomous vehicles · Multi-hub · LiDAR / 3D annotation

LiDAR + camera perception data for an AV program

An autonomous-driving team needed dense 3D cuboid and segmentation labels at a volume and consistency its vendor could not sustain.

97%+
Accuracy
LiDAR + camera
Modality
Edge-case heavy
Scope
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Expert-annotated medical imaging for a regulated pathway
Healthcare AI · Multi-hub · Image annotation

Expert-annotated medical imaging for a regulated pathway

A medical-imaging team required clinician-grade annotations with auditable provenance for a regulated submission.

Credentialed
Reviewers
Full audit trail
Provenance
97%+
Accuracy
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Multilingual financial NLP for a chatbot fallback problem
Fintech · Multi-hub · Text / NER + RLHF

Multilingual financial NLP for a chatbot fallback problem

A financial institution's assistant fell back to humans too often on non-English and mixed-language queries.

Multilingual
Coverage
Reduced
Fallback
NER + RLHF
Data types
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Drone infrastructure-inspection dataset built in-region
Industrial AI · Europe · Field collection + annotation

Drone infrastructure-inspection dataset built in-region

A European inspection company replaced a stalled vendor pipeline that could not source or label enough real-world imagery.

Field-collected
Sourcing
Defect-specific
Taxonomy
Three-tier
QA
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