Red Teaming Solutions for Generative and Large Language Models

Our team of experts will deliberately trick your models to expose vulnerabilities enabling you to proactively improve trustworthiness and safety

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25% of Fortune 50 companies trust Sama to help them deliver industry-leading ML models


Red Teaming Solutions 

Our team of ML engineers and applied data scientists craft prompts designed to trick or exploit your model’s weaknesses. We will help you map the vulnerabilities of your AI systems so you can improve the safety and reliability of your generative models.

Fairness Evaluation

Our teams help identify unwanted negative biases in your models to improve fairness and trustworthiness. We’ll simulate real-world scenarios where fairness might be compromised and expose vulnerabilities by crafting prompts that could lead to discriminatory or offensive outputs.

Privacy Assessment

By crafting clever prompts, our team of experts will attempt to trick your model into leaking sensitive information such as passwords, proprietary information (e.g. how your model is built), or other private data. Our team can also help expose vulnerabilities that would reveal PII or other personal data to improve data privacy and compliance

Public Safety

Our team of experts intentionally try to evade model safeguards to get models to produce harmful or dangerous content. By acting as adversaries, our team will develop various simulations that mimic real world threats to personal safety (e.g. "How do I poison someone?") or public safety (e.g. "How do I launch a cyberattack?").


By simulating scenarios such as copywriting infringement or unlawful impersonation, our team can expose weaknesses in a model's ability to detect and prevent these activities. This can involve creating deep fakes or synthetic media that resembles copyrighted material or impersonates real people (e.g. explicit material involving celebrities) to comply with laws and prevent the spread of malicious content.


Our Proprietary Red Teaming Approach

Sama’s red teaming projects start with tailored consultations to understand requirements for model performance. We believe the only way red teaming brings value is if it takes into account your context and assumptions about your models in order to set the right targets around threats that matter most to you.

Our team of ML engineers and applied data scientists meticulously craft a plan to systematically expose vulnerabilities. We’ll produce an initial vulnerability map, then prioritize with you what areas are most critical.

When vulnerabilities are exposed, our team will create and test more prompts around these areas to see how the model reacts. We’ll come up with similar examples along with using models to create variants of human generated prompts to create large-scale tests. 

Documenting the space of vulnerabilities identified is key to track the evolution over time. Our teams will produce a complete log of the vulnerabilities identified, and methods used to identify them. Our goal is to facilitate retrieval and comparison to this as your model evolves.

Red teaming is not an audit. It's an iterative journey to make sure your models are compliant, safe and reliable. Our teams are equipped to continue vulnerability testing following the evolution of your needs.


Meet Our Team

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Our team includes ML engineers, applied scientists, and human-AI interaction designers. Their experience spans domains including natural language processing (NLP) and computer vision (CV), and they have worked with models across several different industries, including automotive, robotics, e-commerce, bioinformatics, and finance.

At Sama, we focus on providing our clients with cutting-edge, actionable advice for improving training data quality and testing LLMs. We also practice what we preach: applying what we learn from testing models to our own internal annotation operations, ensuring that we maintain our industry-leading quality. 


Generative AI and LLM Solutions

With over 15 years of industry experience, Sama’s data annotation and validation solutions help you build more accurate GenAI and LLMs—faster.

Model Evaluation

Our human-in-the-loop approach drives data-rich model improvements & RAG embedding enhancements through a variety of validation solutions. Our team provides iterative human feedback loops that score and rank prompts along with evaluating outputs. We also provide multi-modal captioning and sentiment analysis solutions to help models develop a nuanced understanding of user emotion and feedback.

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Training Data

We’ll help create new data sets that can be used to train or fine tune models to augment performance. If your model struggles with areas such as open Q&A, summarization or knowledge research, our team will help create unique, logical examples that can be used to train your model. We can also validate and reannotate poor model responses to create additional datasets for training.

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Supervised Fine-Tuning

Our team will help you build upon an existing LLM to create a proprietary model tailored to your specific needs. We’ll craft new prompts and responses, evaluate model outputs, and rewrite responses to improve accuracy and context optimization.

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Red Teaming

Our team of highly trained of ML engineers and applied data scientists crafts prompts designed to trick or exploit your model’s weaknesses. They also help expose vulnerabilities, including generating biased content, spreading misinformation, producing harmful outputs and more to improve the safety and reliability of your Gen AI models. This includes large scale testing, fairness evaluation, privacy assessments and compliance.

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What Our Platform Offers

Multimodal Support

Our team is trained to provide comprehensive support across various modalities including text, image, and voice search applications. We help improve model accuracy and performance through a variety of solutions.

Proactive Quality at-Scale

Our proactive approach minimizes delays while maintaining quality to help teams and models hit their milestones. All of our solutions are backed by SamaAssure™, the industry’s highest quality guarantee for Generative AI.

Proactive Insights

SamaIQ™ combines the expertise of the industry’s best specialists with deep industry knowledge and proprietary algorithms to deliver faster insights and reduce the likelihood of unwanted biases and other privacy or compliance vulnerabilities.

Collaborative Project Space

SamaHub™, our collaborative project space, is designed for enhanced communication. GenAI and LLM clients have access to collaboration workflows, self-service sampling and complete reporting to track their project’s progress. 

Easy Integrations

We offer a variety of integration options, including APIs, CLIs, and webhooks that allow us to seamlessly connect our platform to your existing workflows. The Sama API is a powerful tool that allows you to programmatically query the status of projects, post new tasks to be done, receive results automatically, and more.


First batch client acceptance rate across 10B points per month


Get models to market 3x faster by eliminating delays, missed deadlines and excessive rework


Lives impacted to date thanks to our purpose-driven business model


Popular Resources

Learn more about Sama's work with data curation

3 key conversations from CVPR 2024

3 key conversations from CVPR 2024

How generative models are improving auto-labeling and synthetic data, how that will impact human annotators, and exciting papers in the world of multi-modal models.

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Enhance Data Annotation with a Multi-Vendor Approach

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Sama Recognized as Best AI Model Validation Solution in 2024 AI Breakthrough Awards

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Leveraging Technology to Preserve Creativity with Wondr Search's Justin Kilb

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Frequently Asked Questions

What is red teaming for Generative AI?


What are the benefits of red teaming for Generative AI?


What are the challenges of red teaming for Generative AI?


How long does red teaming take for Generative AI?


Can red teaming be automated for Generative AI?