Claude - Frequently Asked Questions
- 1 Do I retain ownership of my data I upload to the Claude platform?
- 2 What classifications of data may be uploaded to the Claude platform when I logged in with my Syracuse University credentials to approved AI tools?
- 3 How long does the Claude platform retain items like chat history, projects, artifacts, & items uploaded?
- 4 What level of access does SU have to my AI usage in terms of data, prompts, and information input into the AI platforms?
- 5 Does the Claude platform train on my data?
- 6 Are Incognito chats saved?
- 7 How can I get access to Claude Code?
- 8 How do I reset or extend Claude limits or access Claude Code?
Do I retain ownership of my data I upload to the Claude platform?
The Anthropic Claude terms of service that govern the Syracuse University instance of Claude state that the user retains all ownership of any inputs to the Claude platform and is granted ownership over any outputs that Claude creates.
What classifications of data may be uploaded to the Claude platform when I logged in with my Syracuse University credentials to approved AI tools?
All classifications of university data can be uploaded and used when a user is logged in with university credentials (NetID).
How long does the Claude platform retain items like chat history, projects, artifacts, & items uploaded?
Currently Claude retains all data for 2 years. When you delete a chat or project, it is no longer visible to you and will no longer be part of your personalized memories in the platform. All deleted items are retained in the platform for the duration of the retention period independent of visibility.
What level of access does SU have to my AI usage in terms of data, prompts, and information input into the AI platforms?
As with all computing systems, data stored within Syracuse University information systems is inherently accessible to authorized IT staff in order to support, secure, maintain, upgrade, troubleshoot, and back-up those systems.
At Syracuse, this access is strictly governed by the Information Technology Resources Acceptable Use policy (https://policies.syr.edu/policies/free-speech/information-technology-resources-acceptable-use-policy/) and the Information Security Framework and is exercised in accordance with departmental guidelines and best practices.
Does the Claude platform train on my data?
By default the data that Syracuse University users upload and the chat sessions they create are not used to train any of the Claude platform AI models. If you explicitly report feedback or bugs to Claude, then Claude may use your submission to train AI models.
The Claude platform has personalization features that are configurable by each user that allow for the platform to remember a user and use prior chat sessions and projects when generating new outputs. To change any memory or other personalization settings please visit the Claude Settings page. More information can be found at: Understanding Claude's Personalization Features | Anthropic Help Center
Are Incognito chats saved?
Incognito chats are temporary conversations that aren't saved to your chat history or to your personalized Claude memory. The chat session is still retained on the Claude platform and follows the retention policy of all other chats and projects.
How can I get access to Claude Code?
Claude Code is away to consume Claude models via API access and the Claude Code terminal. The Claude Enterprise License does not include Claude Code, but users can purchase access via a credit card. Learn More.
How do I reset or extend Claude limits or access Claude Code?
Extending or increasing the daily limits of the standard Claude user license as well as gaining access to Claude Code can be done via an upgrade to a Claude Premium license. Syracuse Faculty and Staff can use university funds to purchase the Premium license. To start the process, please use the Claude Premium Access Package.
Best practices for specific use cases
Claude offers several different models. Different models consume allocation at different “rates”. For example, in coding-focused workflows the “Opus” tier model uses much more of your allocation per prompt than the “Sonnet” model. Identify which model you need for your task. If the task is routine (e.g., summarizing text, minor edits), pick the lighter model. If it’s complex (e.g., large architectural reasoning, research summary), use the heavier model—but be aware of the cost.
For Coding Tasks
Provide complete context about your coding environment in your initial message.
Include entire relevant code snippets in one message for reviews or debugging.
For Writing Assistance
Outline requirements, target audience, and key points comprehensively.
Send entire texts for editing in one message rather than breaking them up.
For Research and Analysis
Clearly define your research question and focus areas initially.
Provide all relevant data in a single, well-structured message.
By following these best practices, you can make the most efficient use of your Claude plan's message allocation.