CoreBridge AI
Targeted AI Model Evaluation

Multilingual Model Training Data:
14-Day Pilot

AI Speed + Human Accuracy — Credentialed, multilingual, audit-grade annotation built for teams training and evaluating frontier language models.

The Problem

Model pipelines are bottlenecked at the edges.

Model training and evaluation pipelines are bottlenecked by one unglamorous constraint: labeled data quality at the edges—low-resource languages, domain-specific terminology, and the judgment calls that separate a usable label from a confidently wrong one.

Generic Crowd Platforms:Optimize purely for throughput, struggle with multilingual nuance, and hide their disagreement methodology.
Inherited Pipeline Risk:You inherit vendor errors without the raw logs or disagreement data needed to diagnose and defend them to stakeholders.
What CoreBridge Does Differently

Documented, Auditable Accuracy

01

3+ Languages Validated

Credentialed, language-matched annotators—not generalist crowdworkers. Annotators are assessed for target-language fluency and domain knowledge before pilot start.

✓ Bench composition shared in advance
02

≥ 98% Target IAA Accuracy

Inter-Annotator Agreement (IAA) is managed as a rigorous process. Disagreements are logged, adjudicated, and routed back into annotator calibration.

✓ Full disagreement logs delivered
03

20% Faster TAT vs Baseline

Output formats map directly to common RLHF/SFT and eval pipeline structures (preference pairs, span labels, rubric-scored rationales).

✓ Zero integration overhead
Multi-Modal Capability

Need Spatial & Autonomous Perception Labeling?

We also run high-precision 3D LiDAR point cloud annotation, semantic segmentation, and multi-frame tracking alongside our NLP workflows.

Explore 3D LiDAR →
Start the 14-Day Pilot

Scope Your Dataset Pilot

🔒 All sample datasets and project details submitted through this form are fully protected and subject to automatic, strict non-disclosure terms.