Boost your model’s text
understanding & reasoning skills
Custom data to improve your LLM's information processing and logical reasoning.
Trusted by Leading AI Teams
Domain experts for specialized data
Vetted experts with advanced degrees and industry experience contribute the domain knowledge that your LLM lacks.
Domains
Sciences & Industries
Mathematics
Computer Science
Medicine
Psychology
Physics
Bioinformatics
Law
Finance
Accounting
Economics
Teaching
Religion
Language Arts
Philosophy
History
Performing Arts
Visual Arts
Languages
Spoken languages
French
Korean
Ukrainian
Malay
Spanish
Russian
Vietnamise
English
Japanese
Bengali
Swedish
Filipino
Dutch
Polish
Tamil
Thai
Hindi
German
Arabic
Turkish
Amplify your model's text comprehension and reasoning capabilities
Toloka offers high-quality custom data to directly enhance your model’s information processing and logical reasoning capabilities. Unlock deeper insights and more accurate conclusions.
Enhance core skills of LLMs & VLMs
Post-train your models with meticulously curated datasets designed to capture real-world scenarios and improve performance.
Skills:
Instruction following
Multimodal processing
Multilingual processing
Knowledge factuality
What we offer:
Expertly crafted demonstrations for any domain
Human-labeled preferences for complex cases
Diverse post-training data with our Hybrid pipeline
Improve your advanced reasoning model
Strengthen your model’s logical thinking and reasoning across diverse domains. Enhance problem-solving capabilities, minimize reasoning errors and logical fallacies, and achieve more robust generalization.
Skills:
Logical reasoning
Step-by-step thinking
Mathematical reasoning
Evidence evaluation
What we offer:
Delivering sets of auto-verifiable tasks with rubrics for reasoning-oriented RL stage in any domain
Improving chain-of-thoughts for advanced scientific reasoning scenarios from multiple domains
Providing Deep evaluations for your model’s reasoning skills
Case studies
Multilingual Demonstrations Collection
Client type:
Big tech
Data type:
Demonstrations for RAG
Experts:
Skilled Editors
Language:
English
German
Italian
Volume:
2500 datapoints per language
Application:
Post training of foundational LLM
Domain-specific data for RL
Client type:
Big tech
Data type:
Demonstrations
Experts:
Experts in Finance (US)
Language:
English
Volume:
3500 datapoints
Application:
Improving LLM’s performance with
reinforcement learning techniques
Learn more about Toloka Evaluation for GenAI
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Where can I get data for LLM training and reasoning?
While public datasets exist, the highest quality LLM training data comes from specialized providers like Toloka. We move beyond simple raw data by offering expert custom data tailored to your specific needs. We also build custom data pipelines to make sure we fit the client's needs. Our process follows a full lifecycle approach to guarantee results. We begin by working closely with you to develop the right guidelines and clarify the exact requirements for a high-quality data point. Based on this, we build custom pipelines, assign the appropriate level of human expert contributors for the task, and implement a hybrid Quality Assurance (QA) system that uses both AI agents and human review. This comprehensive process ensures the final dataset meets the client’s standards and improves their model's performance.
Are LLMs running out of training data?
There is a growing concern that public internet data used for pre-training is finite. This makes the quality of training data more critical than ever. The future of training LLMs lies in moving beyond scraping web pages to creating high-value, domain-specific information. We address this challenge by developing sophisticated hybrid pipelines that combine expert-led data generation with the scale of with the scale achievable by the competition only through synthetic data generation.
How much data is needed to train an LLM?
Training an LLM requires enormous amounts of data, from pre-training to fine-tuning and evaluation data. At Toloka, we specialize in developing high-quality datasets to fine-tune and evaluate your LLMs.
Can I train an LLM with my own data?
Absolutely. Using your own dataset is one of the most powerful ways to create a competitive advantage. Toloka can partner with you to augment and enhance your existing data. Our services include data preparation, annotation, and enrichment. We follow strict protocols for handling sensitive data and addressing ethical considerations. We help turn data into a powerful asset for fine-tuning, red teaming, and aligning your models.
Which data sources are used to train LLMs?
Large language models are typically pre-trained on an extensive collection of public data sources, including internet crawls, digitized books, and code repositories. At Toloka, we focus on delivering high quality data for the post-training state of model development. For model fine-tuning, targeted data sources are needed. We create high-quality custom datasets built for clients’ specific projects using subject matter experts, licensed proprietary databases, and client-provided materials to ensure the language model excels at its intended purpose.
How do you ensure high data quality?
We guarantee high data quality through a multi-layered, human-in-the-loop process and automated quality assurance. Every project is staffed with vetted experts in their respective domains who follow clear, detailed guidelines written alongside our clients. The data undergoes rigorous reviews and validation checks to ensure accuracy, consistency, and adherence to your project's specific requirements, resulting in superior training datasets.
How do you handle bias and other ethical considerations in the data?
Addressing ethical considerations is fundamental to our process. We actively work to mitigate bias by using a diverse, global pool of experts and contributors. We collaborate with you to create explicit guidelines that prevent the generation of harmful, stereotypical, or biased content, as well as ensure the well-being of our annotators, leading to safer, ethical and more reliable models.
How quickly can you deliver data for time-sensitive research projects?
We recognize that in the fast-paced field of AI development, speed is a competitive advantage. Our platform is engineered for agility and rapid delivery. By leveraging a global network of vetted experts and streamlined, scalable workflows, we can launch and execute projects quickly. This efficient process ensures you get the high-quality dataset you need for your next model checkpoint without sacrificing the rigorous quality controls that define our work.