Headquartered in Chennai with delivery operations serving North American enterprises, DataXWorks provides domain-specific dataset curation, multimodal annotation, and human-in-the-loop validation for regulated industries.
Domain Specialists
High-Precision Annotations
Annotation Accuracy SLA
Global Compliance Standards
We replace fragmented data labeling vendors with an integrated, compliance-first operating layer engineered specifically for production MLOps environments.
We support technical teams and global organizations where model accuracy, governance, and audit readiness are critical to production deployment.
Sourcing domain-specific training sets, RLHF human feedback loops, and automated red-teaming pipelines for foundation models.
Providing continuous, pipeline-integrated data annotation and drift mitigation to accelerate internal production AI rollouts.
Delivering HIPAA-compliant clinical datasets, PHI-safe medical imaging annotation, and expert ICD coding validation.
Powering fraud detection, KYC/AML extraction, and audit-ready document classification for regulated fintech architectures.
Scaling complex product taxonomies, multimodal catalog enrichment, and visual search datasets for omnichannel platforms.
Acting as the white-labeled, high-security AI data delivery engine behind Tier-1 enterprise digital transformation initiatives.
We bridge the gap between raw data ingestion and production inference. Every dataset, annotation pipeline, and human-in-the-loop checkpoint is built with downstream model performance, strict lineage, and regulatory auditability baked in from day one.
Audit-ready across HIPAA, GDPR, ISO 27001, SOC 2, NIST AI RMF, and EU AI Act requirements.
Schema-aligned, domain-specific data sourcing and synthetic augmentation engineered for optimal inference accuracy.
Scalable, multi-tier labeling across computer vision, NLP, and audio with automated pre-checks and consensus QA.
Domain-specialist oversight to eliminate hallucinations, enforce safety boundaries, and fine-tune model alignment.
Post-deployment active-learning loops and benchmark evaluations to prevent model degradation over time.
Accelerate enterprise AI deployment with structured, validated training data infrastructure.
.png)
.png)