Responsible AI with safety and red teaming
Use expert services and advanced software for red teaming to uncover hidden biases and potential risks in your AI systems and models
Red teaming: Uncovering vulnerabilities in Generative AI
Prohibit fraudulent & illicit activities
Block bad actors from exploiting LLMs for fraudulent activities, such as deep fakes, phishing, and theft.
Improve privacy
Prevent data leaks on personally identifiable data (PII) and other sensitive or confidential data.
Mitigate model biases
Promote fairness by exposing discrimination, prejudice, and inequality towards a certain group.
Restrict inaccurate information
Stop the spreading of untrue, flawed, or deceptive information that could be harmful to the user.
Accelerate responsible model development with red teaming
Teams use red teaming to proactively identify and address vulnerabilities in AI systems before deployment. It is a key step in responsible model development. By deliberately prompting the model to perform adversarial tasks, this process identifies risks and leads to more trustworthy models.
Overcome data, tooling, and evaluation challenges
Evaluating trust in models presents its own challenges. Each model’s unique vulnerabilities require tailored approaches that depend on detailed expert human evaluations. Because of the importance of these evals, high-quality data is required and systems are needed to monitor results and facilitate active collaboration.
Boost model safety and performance with Labelbox
Labelbox addresses these challenges head-on, providing a comprehensive platform and expert services to streamline red teaming. Accelerate responsible model development with high-quality datasets curated by vetted red teamers to improve performance and safety. Contact us to explore our human evaluation capabilities.
Why Labelbox for red teaming & safety
Access dedicated expert red-teamers
Tap into Labelbox's network of skilled red teamers who specialize in identifying vulnerabilities and adversarial attacks. Enjoy easy access to on-demand experts trained on advanced attack tactics across a wide range of domains and use cases.
Drive rapid model improvement
Go beyond basic red teaming results. Labelbox provides granular performance dashboards and detailed reporting that highlight vulnerabilities and areas for improvement. Accelerate your model's safety with data-driven insights.
Generate high-quality datasets
Labelbox is committed to delivering high-quality adversarial data. We offer a quality guarantee, ensuring your red teaming exercises are based on reliable and effective data. If the data doesn't meet your standards, we'll redo it free of charge.
Design custom red teaming workflows
Labelbox provides a flexible platform for designing and executing tailored red teaming workflows. Collaborate with your team in real-time to create precise instructions, define specific attack vectors, and adapt your strategy as needed.