AI Training Data Built for Production-Grade Models
The performance ceiling of your AI model is set by the quality of its training data. Centric Labs delivers curated, domain-specific AI training datasets that accelerate model development from proof-of-concept to production deployment. We combine human expertise with intelligent tooling to create datasets that are accurate, diverse, and aligned to your model objectives. From supervised learning datasets to RLHF preference data for LLM alignment, we supply the fuel that powers high-performing AI systems.
Training Data for Every AI Paradigm
We deliver training data across the full spectrum of AI methodologies: supervised learning datasets with human-verified labels for classification, detection, and segmentation tasks; RLHF and preference data for LLM alignment including human rankings, comparisons, and reward model inputs; LLM fine-tuning data including instruction-response pairs, prompt engineering datasets, and domain-specific corpora; synthetic data generation for augmenting real-world datasets, handling edge cases, and privacy-preserving AI development; and multilingual datasets spanning 30 plus languages including Arabic, Urdu, and other low-resource languages.
What you get
- Dedicated managed teams, no anonymous crowd
- Multi-stage QA with measurable SLAs
- Secure workflows designed for enterprise data
- Fast pilots with clear success criteria
Domain Experts, Not Just Data Workers
Training data quality depends on who creates it. Our annotation teams include medical professionals for healthcare AI, financial analysts for fintech and banking models, automotive engineers for autonomous driving datasets, legal experts for document understanding and compliance AI, and native speakers across 30 plus languages for NLP and conversational AI. Every annotator is trained on your specific taxonomy, guidelines, and quality standards before a single label is created.
What you get
- Dedicated managed teams, no anonymous crowd
- Multi-stage QA with measurable SLAs
- Secure workflows designed for enterprise data
- Fast pilots with clear success criteria
End-to-End Data Pipeline Management
We do not just label data — we manage your entire training data lifecycle. Our pipeline includes data collection and acquisition from diverse sources, data cleaning, deduplication, and preprocessing, annotation and labeling with multi-tier QA, dataset versioning and change management, continuous model feedback integration, and delivery in your preferred format with full documentation. This end-to-end approach eliminates the fragmentation that slows down enterprise AI programs.
What you get
- Dedicated managed teams, no anonymous crowd
- Multi-stage QA with measurable SLAs
- Secure workflows designed for enterprise data
- Fast pilots with clear success criteria
Enterprise Security at Every Stage
Your training data often contains sensitive or proprietary information. We protect it with SOC 2 Type II aligned security controls, ISO 27001 aligned information security management, HIPAA-ready workflows for healthcare data, air-gapped annotation environments for classified or restricted data, data residency controls with in-region processing options, and encrypted data transfer and storage with full audit trails.
What you get
- Dedicated managed teams, no anonymous crowd
- Multi-stage QA with measurable SLAs
- Secure workflows designed for enterprise data
- Fast pilots with clear success criteria
Start Building Better Training Data Today
Request a free pilot to see the difference that expert-curated training data makes in your model performance. Our team will scope your requirements, configure the pipeline, and deliver a sample dataset within one week — no commitment required.
What you get
- Dedicated managed teams, no anonymous crowd
- Multi-stage QA with measurable SLAs
- Secure workflows designed for enterprise data
- Fast pilots with clear success criteria
Ready to validate quality and security in a pilot?
We will scope a small, measurable dataset, define acceptance criteria, and stand up a managed team fast.