AI Data Services / GenAI Data For Model Training & Fine-Tuning
GenAI Data For Model Training & Fine-Tuning
Purpose-Built AI Training Data.
From Collection to Control.
The foundation of every powerful AI model is high-quality data. We specialize in Data Collection and Enhancement, delivering curated datasets tailored to your unique AI needs. From conversational AI to domain-specific applications, our global network captures authentic, representative data across languages and use cases.
Whether you need diverse text or structured datasets, our advanced collection methods and rigorous quality controls deliver data that’s ethically sourced, well-documented, and built for performance.
Frequently Asked Questions
What is Supervised Fine-Tuning (SFT)?
Supervised Fine-Tuning is the process of improving a base language model by training it on carefully curated datasets with known outputs. We provide high-quality, domain-specific data that enables SFT to align your models more closely with your desired behavior—boosting accuracy, task performance, and contextual relevance.
What is Prompt Engineering?
Prompt Engineering involves designing and refining prompts to guide large language models toward producing optimal responses. We help create and test diverse prompt datasets to ensure your model performs consistently across use cases—maximizing relevance, minimizing ambiguity, and reducing token waste.
What is Reinforcement Learning with Human Feedback (RLHF)?
RLHF is a training method where human feedback is used to guide a model’s learning process after initial fine-tuning. We build and manage RLHF pipelines that incorporate structured evaluations by real annotators—helping your models learn preferred behaviors and reduce harmful or biased outputs.
What are Risk Mitigation Services for GenAI?
Risk Mitigation Services help identify and reduce potential issues in your AI models before deployment. We provide data-driven insights and human evaluations to catch hallucinations, toxicity, bias, and factual errors—ensuring your GenAI system is reliable, safe, and aligned with ethical standards.