Healthcare AI Services by Digital Divide Data (DDD)

Build Safer, Smarter Healthcare AI with Human-in-the-Loop Precision

Healthcare AI succeeds (or fails) on data quality, clinical context, and rigorous validation. Digital Divide Data (DDD) delivers human-in-the-loop data operations and evaluation services that help healthtech teams move from prototypes to production faster, more safely, and at scale.

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What we do

DDD supports healthcare and healthtech organizations across the AI lifecycle from dataset creation and annotation to model evaluation and iterative improvement spanning computer vision, NLP, multimodal models, and generative AI.

Our focus areas

Healthcare training data pipelines for CV, NLP, and multimodal models
Generative AI data + evaluation (LLM tuning support, RLHF-style feedback, safety testing)
Model validation workflows with consistent QA and clinician-in-the-loop options (as needed)

Why DDD

Proven scale (millions of labeled data points; large, trained labeling workforce)
Human-in-the-loop accuracy for high-stakes healthcare use cases
Coverage across CV + NLP + GenAI including evaluation and testing workflows
Secure, enterprise-ready delivery with published security standards

Healthcare AI capabilities

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Use Cases

Digital Pathology

DDD’s pathology-trained teams annotate cells and tissues in Whole Slide Images (WSI) to support digital pathology models, disease detection, and pharmaceutical research.

Digital Radiology

DDD annotates X-rays, CTs, MRIs, and ultrasounds at scale, delivering high-quality ground-truth data for clinical diagnostics and radiology AI applications.

Medical Texts

DDD structures clinical notes, medical records, and audio transcripts to power NLP automation, decision-support tools, and intelligent healthcare assistants.

Robotic Surgery

DDD supports surgical AI with precise instrument tracking, lesion detection, and phase identification for robotics, endoscopy, and real-time procedure analytics.

Sports Medicine

DDD provides point tracking and movement annotation for rehabilitation, athlete monitoring, and behavioral health applications to improve safety and performance insights.

What Our Clients Say

DDD team understood subtle anatomical differences and pathology indicators, helping our diagnostic model reach higher accuracy thresholds than we expected.

– Chief Medical Officer, Diagnostic AI Startup

DDD handled large volumes of CT and MRI segmentation work with remarkable consistency. Their QA process gave us the confidence we needed for regulatory submission.

– Head of Imaging AI, Radiology Company

Our model improved significantly after integrating DDD’s multimodal annotation sets. They delivered exactly what we needed, fast, accurate, and clinically aligned data.

– CTO, Health Tech Company

DDD helped us build a high-quality dataset for fall detection and activity monitoring. Their understanding made a real difference in our model performance.

– Product Manager, Health Tech Company

Customer Success Stories

See how DDD accelerates ADAS innovation through data-driven success stories.

LiDAR Segmentation for ADAS with 97%+ Quality

Our client needed a highly skilled and rapidly scalable annotation team capable of segmenting and labeling massive LiDAR datasets with exceptional precision to ensure safe and reliable ADAS performance.

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