Dataset Generation: Powering AI with High-Quality Training and Evaluation Data

We generate diverse datasets for model training and evaluation, including fine-tuning, RLHF, DPO, and domain-specific benchmarks. Our approach leverages LLM, HITL, or a combination of both to ensure comprehensive data coverage.

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What it is?

Dataset generation is a critical step in the AI development process. At Zangoh, we work with cleaned data to generate a variety of datasets for both model training and evaluation. These datasets ensure that your AI models are trained with the highest quality data and evaluated against relevant, domain-specific benchmarks. Our approach combines automation through LLMs with the precision of human-in-the-loop (HITL) processes, ensuring accuracy and relevance across all datasets.

Our Dataset Generation Services

Training Data Generation

We create datasets specifically tailored for various training purposes, including:

Fine-Tuning Datasets: Data sourced and prepared to fine-tune models for specific tasks and domains.
RLHF Datasets: Carefully curated datasets to help reinforce learning and feedback processes.
DPO Datasets: Data generation for Direct Preference Optimization, enhancing model alignment with user preferences.
Synthetic Data: When needed, we generate synthetic data to broaden the model’s knowledge base, covering gaps in real data and ensuring more robust training.

Evaluation Data Generation

Evaluation datasets are vital to ensure that your models are performing as expected. We generate domain-specific benchmarks that rigorously test the model’s domain knowledge, accuracy, and adaptability. This process includes

LLM-Generated Benchmarks: Automatically generated data to test the model on generalized tasks.
HITL-Generated Benchmarks: Human-created benchmarks for more specific, complex domain tasks.
Hybrid Benchmarks: A combination of LLM and HITL to ensure broad and deep evaluation coverage.

Key Benefits

Comprehensive Training Datasets

We generate datasets for fine-tuning, RLHF, and DPO, using both real and synthetic data to enhance the model’s knowledge and performance.

Domain-Specific Benchmarks

Our evaluation data includes highly specialized, domain-specific benchmarks that accurately test your model’s understanding and capabilities.

Hybrid Data Generation

We combine LLM and HITL to produce high-quality, well-rounded datasets that capture nuanced information and address edge cases.

Scalable Solutions

Whether you need small-scale datasets or extensive collections for large models, our solutions are scalable to meet your enterprise's needs.

Our Process: From Data to GenAI Success

Our dataset generation process ensures that the data used in training and evaluating your AI models is accurate, comprehensive, and tailored to your needs.

Data Sourcing and Cleaning: We start with cleaned and contextualized data, preparing it for generation by LLM, HITL, or both.

Training Data Generation: We generate specialized datasets for fine-tuning, RLHF, and DPO, using both real and synthetic data to ensure comprehensive coverage of knowledge areas.

Evaluation Data Generation: We produce domain-specific benchmark datasets that test your model’s performance in real-world scenarios.

LLM + HITL Approach: Combining the power of LLM automation with human oversight ensures that the data is accurate, relevant, and ready for AI development.

Continuous Iteration: As models evolve, we continuously update datasets to reflect new domains, emerging trends, and expanded knowledge areas

Frequently Asked Questions

What types of datasets can Zangoh generate for AI training?

We generate datasets for fine-tuning, RLHF, and DPO, along with synthetic data to expand the model's knowledge. Our datasets are designed to enhance model performance across a variety of use cases.

How does Zangoh generate evaluation datasets?

We create domain-specific benchmarks for testing AI models, combining LLM-generated and HITL-generated data to ensure comprehensive and accurate evaluations.

What role does HITL play in dataset generation?

HITL (Human-in-the-Loop) provides the precision needed to create highly specialized, accurate datasets, especially for complex tasks or domain-specific benchmarks.

Can Zangoh generate synthetic data for AI training?

Yes, we generate synthetic data to fill gaps in real data and broaden the model’s knowledge, ensuring that training datasets are more robust and diverse.

How does Zangoh ensure that datasets align with business objectives?

We work closely with your team to understand your business goals and ensure that all generated datasets are tailored to support your AI model’s success in real-world applications.

What industries benefit most from Zangoh’s dataset generation services?

Industries such as healthcare, finance, retail, and legal benefit from our customized datasets, which are tailored to specific domains and enhance AI model performance.

How does Zangoh measure the quality of the generated datasets?

We use a combination of automated testing and human oversight to evaluate dataset quality, ensuring that the data is accurate, relevant, and aligned with the intended use case.

Ready to Generate High-Quality Datasets?

+91-97525-99372
401 Atulya IT Park Indore MP India 452014