Responsible AI Declaration
AI Governance Framework Responsible for Nublit
At Nublit, we believe that artificial intelligence should be a force that drives efficiency, innovation, and our customers’ confidence, never a risk to their security, privacy, or regulatory compliance. As experts in cloud infrastructure management on AWS and in the design and implementation of AI solutions—from assessment From initial, through proof-of-concept (POC) testing, to production—this commitment guides every project we develop for our clients.
Our approach
We design, implement, and operate responsible, secure, and business-focused AI solutions for our customers. We rely on services such as Amazon Bedrock, Amazon SageMaker, Anthropic (Claude) and OpenAI models, We accompany organizations throughout the life cycle of their AI initiatives, ensuring that each solution is technically sound, ethically responsible, and aligned with applicable regulatory frameworks.
1. Transparency and accountability
We thoroughly document the architecture, models, data sources, and processes involved in each AI project we develop, from initial assessment to production. We continuously monitor the performance of deployed systems, perform periodic testing, and update our procedures as industry best practices evolve.
Our technical team undergoes continuous training in international standards for AI security and responsible development, including frameworks such as the OWASP Top 10 for LLMs, ensuring that every solution we deliver is auditable and explainable.
2. Privacy and data protection
We respect the privacy of our customers and their end users, and we are committed to protecting data in accordance with applicable laws and regulations, including GDPR y HIPAA.
We apply robust encryption protocols for data in transit and in storage across the infrastructure we manage. Input data, client instances, and any sensitive, confidential, or personally identifiable information are not used to train base models or shared with third parties without explicit consent. We implement strict internal controls to prevent improper storage or exposure of such information.
3. Responsible use and prevention of misuse
We implement content filtering, infrastructure monitoring, and quality assurance testing to prevent the generation or misuse of harmful or offensive content in the AI solutions we develop.
We establish and enforce clear ethical boundaries at every stage of our projects—assessment, POC, production, and operation—to prevent harmful, discriminatory, or unsafe results for our customers.
4. Equity and the prevention of bias
We design and configure our AI solutions to minimize bias, misinformation, and discrimination in all its forms. We regularly audit and adjust the systems we implement to ensure fair treatment for all users, regardless of their origin, gender, or other characteristics.
We commit to identifying and mitigating unintentional biases that may arise from the training data, the processing, or the general behavior of the models we use.
5. Human supervision
AI is a tool that enhances business decisions, not a replacement for human judgment. Every solution we design—whether in the assessment, POC, or production phase—keeps people at the center of the decision-making process, ensuring that context, ethics, and professional judgment remain decisive factors in the final results.
6. Security and access control
Access to our customers' systems and data is restricted to expressly authorized users. Our team applies the principle of least privilege and role-based access controls (RBAC) both in the cloud infrastructure we manage and in the AI environments we deploy.
7. Compliance with regulations
We ensure that the infrastructure and AI solutions we deliver comply with applicable legal, regulatory, and best practice requirements, including GDPR y HIPAA, as well as the security standards defined by AWS and the model providers we work with (Anthropic, OpenAI).
We follow maintenance protocols, security operations, and continuous monitoring in line with industry best practices, adapting our practices as new regulatory frameworks and standards emerge.
8. Continuous improvement
We are committed to learning, adapting, and continuously improving our practices as AI and cloud technologies evolve. Feedback from our customers and technology partners helps us ensure that our services remain safe, ethical, and aligned with the principles of transparency, fairness, and trust that define us.
Our AI Advisory Board It monitors the actual impact of the solutions we implement and integrates feedback from a wide range of stakeholders, including customers, internal development teams, technology partners, and regulatory bodies. This committee periodically evaluates and updates our practices, processes, and configurations to detect and mitigate risks such as biases, hallucinations, degradation in model performance, and other challenges inherent in the operation of AI systems.
If you have questions or would like more information about our commitment to responsible AI, please contact us through our online form.