Trust Center

Artificial Intelligence at Nitro

Q: What AI tools does Nitro offer?

Nitro offers two primary AI tools: Document Assistant: Helps process and edit documents efficiently using Azure OpenAI LLMs and Retrieval Augmented Generation (RAG). Knowledge Assistant: Provides instant product support and learning without accessing personal documents or data.

Q: How does Nitro protect my data when using AI tools?

Nitro ensures strict data privacy and security: Your data is never shared with third parties. Inputs are not used to train OpenAI LLMs or other generative AI models. All data is encrypted during transmission and storage, with access securely managed. Documents are temporarily processed for the requested task and deleted after completion.

Nitro builds AI tools responsibly, with privacy, security, and compliance at the forefront. Learn how our AI solutions—like Document Assistant and Knowledge Assistant—are designed to enhance productivity while ensuring data protection and ethical use.

Contact Nitro Privacy Team

Nitro AI: Purpose and data handling

Nitro designs AI tools to enhance document processing efficiently, securely, and ethically. We do not create proprietary generative AI models or share your data with third parties for model training. Instead, we use established generative AI models that process data only for the tasks you request.

Our primary AI tool, Document Assistant, is powered by Azure OpenAI and hosted in a secure environment controlled by Nitro. Azure OpenAI follows responsible AI principles to safeguard data and maintain high security standards. You can learn more about Microsoft’s AI principles here.

Nitro AI's code of conduct

Nitro adheres to Azure’s responsible AI guidelines, including:

Human oversight: Ensuring all AI development is reviewed by humans.
Prevention measures: Safeguards against misuse or fraud.
Thorough testing: Rigorous evaluation to identify and fix potential issues.
Feedback channels: Mechanisms for users to report concerns or suggestions.
Defined scope: AI tools are used only for their intended purposes.

All AI tools undergo internal review and assessment before integration into our Software Development Life Cycle (SDLC), ensuring quality, security, and compliance. We continuously monitor feedback to promptly address issues and improve tool performance and reliability.

Data privacy and security at Nitro

Nitro's Document Assistant

Nitro’s Document Assistant uses Azure OpenAI LLMs and Retrieval Augmented Generation (RAG) to provide responses relevant to your requests. Prompt engineering is used to improve accuracy.

Data privacy highlights:

Your data is not shared: Questions and responses are only accessible to you.
Your data is not used for training generative AI: Your inputs are never used to train OpenAI LLMs or other generative AI models.
Secure processing: Data is encrypted in transit and at rest, with controlled access.

While in Beta, Document Assistant is enabled for individual purchasers; larger organizations must opt-in. Documents are processed temporarily for the requested task and deleted once the task is complete.

Nitro's Knowledge Assistant

Nitro’s Knowledge Assistant uses Azure OpenAI LLMs and RAG to provide instant product support and learning without accessing your documents or personal information.

Data privacy highlights:

Your data is not used for training generative AI: Inputs are not used to train AI models.
Secure processing: Encryption protects your data during transmission and storage, with controlled access.

What AI tools does Nitro offer?

Nitro offers two primary AI tools:

Document Assistant: Helps process and edit documents efficiently using Azure OpenAI LLMs and Retrieval Augmented Generation (RAG).
Knowledge Assistant: Provides instant product support and learning without accessing personal documents or data.

How does Nitro protect my data when using AI tools?

Nitro ensures strict data privacy and security:

Your data is never shared with third parties.
Inputs are not used to train OpenAI LLMs or other generative AI models.
All data is encrypted during transmission and storage, with access securely managed.
Documents are temporarily processed for the requested task and deleted after completion.

Are Nitro’s AI tools responsible and ethical?

Yes. Nitro follows Azure’s responsible AI principles, including:

Human oversight for AI development.
Prevention measures against misuse or fraud.
Thorough testing to identify and fix potential issues.
Feedback channels for user input.
Defined scope to ensure AI is used only for intended purposes.

Does Nitro create its own generative AI models?

No. Nitro does not train or create proprietary generative AI models. Instead, we rely on established AI models, such as Azure OpenAI LLMs, ensuring secure, compliant, and efficient AI processing.

How does Nitro's Document Assistant work?

Document Assistant uses advanced AI models (Azure OpenAI LLMs + RAG) to provide contextually relevant responses for document processing tasks. It is hosted in a secure Nitro-controlled environment, and data is temporarily stored only for the task requested.

How does Nitro's Knowledge Assistant work?

Knowledge Assistant uses Azure OpenAI LLMs and RAG to answer product-related questions. It does not access customer documents or personal data, ensuring that user privacy is always maintained.

Who can access Nitro AI tools?

Document Assistant is enabled for individual online purchasers and requires opt-in for larger organizational users.

Knowledge Assistant is available for users seeking product support and learning, without access to personal files.

How does Nitro handle feedback or issues with AI tools?

Nitro actively monitors user feedback, incorporates it into continuous improvement, and ensures AI tools maintain high standards of performance, reliability, and compliance.

Are Nitro AI tools compliant with privacy regulations?

Yes. Nitro AI tools follow privacy by design, comply with relevant data protection regulations, and implement technical and organizational measures to protect your personal information.

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