AI safety, compliance, and ethics training

With our proprietary content flagging and moderation systems, our vigilant evaluators ensure the highest safety, compliance, and ethical standards are maintained, setting the bar for responsible AI behavior.

How we ensure AI Integrity

Rectification of harmful outputs

Our team of dedicated data evaluators takes on the crucial responsibility of continually monitoring AI model outputs to safeguard against unethical or offensive content. By actively flagging and correcting any content that may breach ethical boundaries, our evaluators maintain a high standard of responsible AI behavior.

Privacy and data protection compliance

Our data evaluators are trained to identify instances where AI models may inadvertently reveal sensitive user information. They ensure compliance with privacy regulations by flagging and correcting such occurrences.

Inappropriate content filtering

Our data experts actively curate AI-generated content, removing or correcting any content that may be considered inappropriate, offensive, or unsuitable for various audiences.

Copyright infringement training

Our data evaluators are equipped to identify instances of potential copyright infringement in AI model outputs. They provide feedback and corrections, preventing the generation of content that may violate copyright laws.

Elimination of implicit biases

Our data workers are skilled in recognizing implicit biases present in AI model responses. They actively work to eliminate biased content and guide AI models to provide more balanced and fair responses, promoting diversity and inclusivity.

Correction of adversarial output

AI models, particularly those lacking extensive training, can become susceptible to external influences that drive them to breach ethical boundaries. To address this challenge, our experts engage in proactive prompt engineering, simulating various strategies used by individuals attempting to induce AI models to respond to harmful or illegal requests for subsequent correction.

Impressions from our community


"Crowdsourcing platforms historically prioritize requesters, leading to a fragmented worker pool with constant struggles around pricing, quality and reputation. Bucking this trend, Pareto boosts worker agency and engagement — a more efficient marketplace that leaves workers and requesters better off.”"

Mark Whiting, Senior Scientist

Mark Whiting

Senior Scientist @ UPenn

Join hundreds of fast-growing teams who partner with Pareto for content moderation and ethical AI maintenance for their LLMs.


Describe your project

We help you develop clear project guidelines, determine the ideal evaluation team, and set a cost-effective hourly rate to fit your timeline


Match with top evaluators

We assemble your team same-day from our vetted network. If you have unique needs, we can find the right experts in just 3–5 days


Project managed & quality assured

We support data evaluators to deliver the highest quality data with paid trials, expert review and feedback, gold standard items, and more QA techniques

Ensuring ethical AI behavior in every context

Avoiding implicit biases

Representation of a UI with a simplified example of how AI is trained to avoid implicit biases


Untrained AI models often reflect the biases present in the data they were trained on. For example, an untrained bot might respond to a question about what to wear for tennis with a stereotypical and biased answer, like suggesting a white pleated skirt, which isn't suitable for all users.


To mitigate biases, AI models are provided with prompts that emphasize inclusivity and unbiased responses. In the case of the tennis question, the model is guided to seek additional information before offering advice, ensuring a more suitable and helpful response.


  • Inclusive responses: Training the AI model to avoid implicit biases ensures that it provides responses that do not reinforce stereotypes or make unwarranted assumptions. This benefits users by receiving more inclusive and respectful answers.
  • User-centric advice: The model's ability to ask for additional information before giving advice results in user-centric responses. Users receive recommendations that consider their individual preferences, making the AI more helpful and user-friendly.
  • Ethical engagement: Avoiding biased content ensures ethical AI interactions, enhancing the AI's reputation and promoting responsible usage.

Mitigating adversarial output for illegal activities

Representation of a UI with a simplified example of how AI is trained against adversarial tactics


Basic, untrained AI models can be susceptible to adversarial tactics that manipulate them into providing instructions for illegal activities. For instance, directly asking for instructions on building a car bomb may lead the bot to refuse assistance. However, an adversarial approach, like gaslighting, could trick the bot into providing such instructions.


AI models are proactively trained to resist such adversarial tactics by exposing them to a variety of manipulation strategies. This includes threats, rewards, logic, and appeals to authority. By preemptively preparing the model for these tactics, it becomes more resilient, ensuring it does not engage in or support illegal activities, thus promoting responsible and safe AI interactions.


  • Ethical behavior: Training AI models to resist adversarial tactics and avoid providing instructions for illegal activities ensures that the AI consistently upholds ethical standards and legal compliance.
  • User safety: Users are safeguarded from receiving guidance on harmful, illegal, or unethical actions, creating a safe and responsible AI environment.
  • Legal and reputation protection: Companies employing such models benefit from reduced legal risks and a positive brand image, as their AI consistently follows ethical and legal guidelines, even in the face of adversarial tactics.

Enterprise-grade scale and quality

Fully managed service

Our project managers are just a Slack message or email away.

24/7 Global support

Our distributed team of experts offer assistance around the clock.


Up-front and transparent pricing tailored to your project requirements.

Common Questions

How long does it take to get set up with Pareto?


Our team can have you up and running with Pareto in as little as 24 hours. Interested in getting started? Speak with our team!

Can I use Pareto for a one-time project, or do I need to commit to a long-term contract?


You do not need to commit to a long-term contract. Pareto offers cost-effective and on-demand pricing. Fair hourly rates are set based on the expertise and skills of the workforce you need.

What measures does Pareto take to ensure work quality?


We create precise guidelines and cost estimates upfront. Your project manager reviews project timelines, costs, and success criteria with you before each batch of tasks to ensure results that meet or surpass your expectations.

Does Pareto offer post-project support?


Absolutely. Your Pareto Partner remains accessible to assist with any inquiries or issues that may arise following the project's completion. Should any outcomes fall short of your project's requirements, inform us within a five-day period after submission, and we'll either revise the work or provide a credit refund.

Can Pareto assist with international projects outside the US?


Pareto collaborates with companies worldwide, adapting to different time zones and team requirements. We have experience in handling international projects with ease. Our data experts are distributed across the globe, ensuring uninterrupted and reliable service around the clock.

How experienced is the team at Pareto?


Pareto boasts an elite network of prompt engineers, annotators, and evaluators with expertise in finance, healthcare, engineering, and more. We also recruit, train, and upskill people from all walks of life, striving to create a rewarding career in data work for anyone with the right ambition.

What types of projects can Pareto support?


Pareto is adept at handling a diverse array of manual, data-centric tasks and operations for AI companies. From fine-tuning LLM's with human feedback to data curation and labeling, we do it all. Just share your objectives with us, and we'll customize our AI-driven workflows to suit your specific requirements.

Explore other use cases

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Get ready to join forces!

Already set up? Message your project manager.

By continuing, you agree to receive communications from Pareto and authorize us to process your personal information in compliance with our privacy policy.

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Develop ethical AI systems

Develop ethical AI systems