AI + Humans:
Data to power LLMs and VLMs
We deliver high-quality, curated data by combining the latest AI & ML technologies with expert human feedback.
Trusted by Leading AI Teams
Bring expert domain knowledge to your LLMs
Our vetted experts have advanced degrees and industry experience to contribute specialized knowledge that LLMs are lacking.
Domains
Medicine
Psychology
Physics
Chemistry
Biology
Biotechnology
Astronomy
Finance
Accounting
Automotive Engineering
Religion
Language Arts
Philosophy
History
Economics
Performing Arts
Teaching
Law
Bioinformatics
Languages
English
Hindi
Malay
Russian
Bengali
Filipino
Ukrainian
Vietnamise
Japanese
Tamil
Thai
Dutch
Korean
Swedish
Arabic
Turkish
Polish
French
German
Spanish
How we blend AI and human expertise
Taxonomy creation
We design tailored taxonomies to match the model's use cases and capabilities. By starting with unique taxonomies for each domain of knowledge, we end up with well-structured and representative datasets.
Performed by:
Domain superexpert
Data architect
Outcome:
Taxonomy for each unique use case
Data generation
We augment state-of-the-art AI & ML technologies with expert human feedback in sophisticated data pipelines.
Our team has the expertise and experience to:
Generate synthetic data from scratch, or validate your pre-generated data at any stage.
Select top-performing models with appropriate licenses tailored to your needs.
Develop complex data pipelines for processing raw internet-sourced data or proprietary datasets.
Input raw data:
Your proprietary data
Open-source dataset
Relevant raw data from the internet
Crowdsourced data
Performed by:
Technologies / LLM Pipeline
Human Experts
Outcome:
Raw generated dataset
Data verification
Our experts perform comprehensive validations on generated data to curate an accurate and reliable dataset for your model's needs.
Input:
Synthetic data
Hybrid data
Performed by:
Human Experts
Outcome:
High quality dataset
Case studies
AI Safety Dataset Generation
Client type:
Big tech
Data type:
Evaluation datase
Experts:
Skilled editors
Language:
English
Volume:
12500 datapoints
13 categories
375 subcategories
3 personas
Application:
Partly used in benchmark assessing the safety of text-to-text interactions with a general purpose AI chat model
Hybrid RAG SFT for Customer Support Chat
Client type:
Coding AI agents startup
Data type:
Demonstrations
Experts:
Skilled Editors
Language:
English
Volume:
9000 datapoints
Application:
Post training for enterprise model