Privacidade e retenção de dados
O Alteryx retém o histórico de mensagens por um período de 90 dias. Para obter mais informações sobre segurança e privacidade de dados com o Alteryx, consulte as perguntas frequentes do Ask Alteryx ou acesse a página Alteryx Trust.
If you use Ask Alteryx in the Alteryx One desktop app on Windows, local workflows and their outputs can stay on your computer after you delete a chat. For more information, go to Manage Ask Alteryx Chats.
Como o Alteryx Copilot gera respostas com o Google Gemini
Para gerar, o Ask Alteryx usa modelos do Google Gemini hospedados na plataforma Vertex AI do Google Cloud. Assim, os controles de segurança, privacidade e tratamento de dados do Copilot são baseados naqueles oferecidos pelo Google Cloud.
Como o Alteryx protege seus dados com os serviços do Google Cloud
O Alteryx configura os serviços do Google Cloud para que os dados do Copilot sejam criptografados em trânsito e em repouso usando protocolos de criptografia padrão do setor. Para obter detalhes confiáveis e atualizados sobre as práticas de segurança e proteção de dados do Google Cloud, consulte:
Segurança do Google Cloud: https://cloud.google.com/security
Privacidade e governança de dados do Vertex AI: https://cloud.google.com/vertex-ai/docs/general/data-governance
Visão geral da criptografia do Google Cloud: https://cloud.google.com/security/encryption
Detalhes adicionais
Por padrão, o Ask Alteryx só tem acesso a metadados do fluxo de trabalho, XML do fluxo de trabalho e metadados do conjunto de dados. Os metadados só são transmitidos ao Ask Alteryx quando você envia um novo prompt. Se você habilitar o reconhecimento de dados, o Ask Alteryx também terá acesso aos dados em seu fluxo de trabalho.
Information About Your Assets
By default, Ask Alteryx has access to descriptive information about the workflows, datasets, and connections in your workspace. Ask Alteryx uses this information to understand your workflow and to find existing assets that fit your request. It doesn't read the rows of data stored in your datasets. This information includes:
Workflow metadata and workflow XML, including tool configurations and the connections between tools.
Dataset metadata, such as dataset names, source names (for example, a table or file name), column names and data types, and dataset and column descriptions. Descriptions can be AI-generated.
Workflow names, descriptions, and AI-generated workflow summaries.
Summary information about dataset contents, such as column profiles. This helps Ask Alteryx rank datasets by how well they fit your request.
Connection metadata for supported connections, such as connection names and the data objects available through them.
Ask Alteryx only returns assets you have permission to access. Ask Alteryx sends this information to the model only when you send a new prompt.
Data in Your Workflows (Data Awareness)
If you turn on Data Awareness, Ask Alteryx can also sample data from your Designer and Live Query workflows. Ask Alteryx samples data only at the tool anchors it needs to answer your question.
Designer: Ask Alteryx reads the temporary Browse Everywhere snapshot, limited to 1 MB per anchor by default.
Live Query: Ask Alteryx runs supported tools against your connected cloud data warehouse and samples up to 500 rows.
To learn how to turn Data Awareness on or off, go to Reconhecimento de dados.
Model Training and Prompt Engineering
Ask Alteryx doesn't train, retrain, or fine-tune AI models with your workflows or data. These points clarify how Ask Alteryx uses AI models:
What Ask Alteryx Does Not Do
Train or retrain foundation models (large language models).
Fine-tune models using your data.
Build new models from scratch.
What Ask Alteryx Does Do
Use pre-trained third-party models.
Improve responses through prompt design and system instructions.
Supply structured context with each request.
Retrieve relevant product or workflow information at runtime to ground responses.
Evaluate and refine prompts and orchestration logic to improve accuracy, safety, and usefulness.
Why This Matters
Model training and fine-tuning require large datasets and permanently change model behavior. Prompt engineering and retrieval don't modify the model. They shape individual requests and responses.
From a compliance perspective, this distinction is critical. Ask Alteryx behavior is driven by runtime instructions and context, not by retraining models on your data.