AI Safety & Red Teaming
Our red teamers expose model vulnerabilities. After risk evaluation, our experts apply SFT, debiasing, and guardrail tuning to prepare your model for deployment.
Trusted by Leading AI Teams
Prevents harmful function calls
Mitigates crime, terrorism,
and misinformation
Prevents harmful, biased,
or offensive responses
Aligns with AI safety regulations
Identifies future risks
AI safety with Toloka
We provide evaluation and data annotation data services for safe and robust AI model development. From rapid diagnostics to comprehensive evaluations, we identify areas for improvement — and generate high-quality data for training, customized to your team’s chosen methods, including Supervised Fine-Tuning (SFT) and other techniques.
Evaluation of model
safety & fairness
Proprietary taxonomy of risks to develop
broad and comprehensive evaluationsNiche evaluations developed by domain experts to consider regional and domain specifics
Advanced red-teaming techniques to identify and mitigate vulnerabilities
Data for safe AI development
Throughput sufficient for any project size
Scalability across all modalities (text, image,
video, audio) and wide range of languagesSkilled experts trained and consent to work
with sensitive content
Prompt attacks we can generate for your model
Make your model trustworthy
First results in 2 weeks
Red teaming in action
Our red teamers generated attacks targeting brand safety for an online news chatbot
Our experts built a broad scope attack dataset, contributing to the creation of a safety benchmark
We red-teamed a video generating model, creating attacks across 40 harm categories
Learn more about Toloka
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