Conduit Docs
  • Getting Started
    • Importing Data
    • Connecting Multiple Accounts
    • How To Invite Additional Team Members to Your Account
    • How Does the Trial Work?
    • What's a Table/Data Schema?
    • Number of Sub-Connections
    • Default Time Range for Downloading Data
    • Conduit Data Lake
    • Conduit vs Boost.Space
    • Conduit vs Reportz.io
    • Conduit vs Google Looker Studio
  • Use Cases
    • Use Case: AI-powered Text Extraction
    • Use Case: Track Ad Campaign Performance with Conduit
    • Use Case: Enhancing Project Management with Copilot
    • Use Case: Using Conduit for Financial Analysis
    • Use Case: Use ChatGPT with your data
    • Use Case: Build financial models from raw transactional data and generate P&L statements.
    • Use Case: Marketing data analytics
    • Use Case: Using data science frameworks using your data in spreadsheets Low-Code
    • Use Case: Custom Dimensions for Ad Operations
    • Use Case: Custom dimensions for E-Commerce
    • Use Case: Extract invoices from PDF
    • Use Case: Export data from SaaS applications to your spreadsheet
    • Use Case: Online store and a physical retail locations consolidated
    • Use Case: Pull data from Advertisement platforms to a spreadsheet
    • Use Case: Consolidation of data received as separate files, for example, separate Excel reports
    • Use Case: Names, IDs, SKUs normalization
    • Use Case: Integrating Conduit with a custom CRM using SSO/OAuth2
    • Use Case: Chat Bot for Your Data
    • Use Case: Display Net sales On a Dashboard by Subtracting Ad spend from Total Sales
    • Use Case: Conduit for Healthcare Applications
  • Security & Data Privacy
    • Data Retention Policy
    • How Conduit Complies with GDPR?
    • Security
  • Spreadsheets
    • Writing data to spreadsheets: Overwrite and Update
    • Using Formulas in Spreadsheets
    • The Time Range in formulas
    • The table in the spreadsheet does not start from the first line
  • Conduit for Digital Agencies
    • How to Use White Label
    • What is a Workspace and a Sub-account
    • Use Case: Creating a Dashboard for Two Clients
    • Users in Your Team vs. Sub-Accounts in Workspaces
    • Deleting a Workspace
    • How to Log Into a Workspace
    • How to Buy Additional Workspaces
    • Schedulers in Workspaces
  • Troubleshooting
    • Error codes and how to troubleshoot data-related issues
    • Google Drive Refusing To Connect
    • Why Are my Shopify stats different?
    • Facebook Integration: How to Fix the GraphMethodException Error
  • Copilot
    • Copilot Roles: Data Analyst vs AI Generalist
    • Conduit Copilot vs. ChatGPT – What's The Difference?
    • How to Tune the Copilot
    • Data Sources for Copilot
  • For Developers
    • IP Addresses of Conduit Servers
    • Create an AI Сopilot for your app
    • Manage your AI Copilot users
    • Upload CSV files to Conduit via API (Guide)
  • Integrations
    • Instagram Integration
    • Dashboard Widgets Based On a SQL Connection
    • GA4 Integration Notes
    • Salesloft Integration
    • Self-service and Manual integrations
    • Installing Google Sheets Add-On
    • Slack Integration
    • YouTube Integration
    • HubSpot Integration
    • Conduit integration for Bigcommerce
    • Xero Integration
    • Recharge integration
    • Wrike Integration
    • Zoho Integration
    • Monday.com Integration
    • ActiveCampaign Integration
    • ClickUp Integration
    • FreshSales Integration
    • Google Ads Quality Score
    • Facebook Ads Reach
    • Shopify Net Sales and Returns
    • Gorgias tickets with Spam/Deleted/Auto-Close statuses
    • Looker Studio Connector
  • Workflows
    • Workflows – Adding New Columns
    • Workflows – using the Join by Key block
    • Workflows – using the Union block
    • Workflows – using the Transpose block
    • Workflows – creating a weekly Ad Spend report
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  1. Use Cases

Use Case: Conduit for Healthcare Applications

Data Sharing with the AI

Conduit does not transmit actual data to AI models. With the traditional LLM systems like ChatGPT, you would send a CSV file containing data along with the question. However, with Conduit, the process is different and involves three key steps:

  1. Sending Metadata Description: Conduit sends a description of the table's metadata, which includes the structure and types of data in the columns.

  2. Formulating the Question: The question itself is sent to the AI.

  3. Requesting a Python Script: A request is made for a Python script that will generate the answer.

In this way, Conduit only shares metadata, not the actual data, with the large language model (LLM).

Controlled Access to Internal Data

Moreover, access to internal data is stringently controlled within Conduit. Here’s how it ensures data security:

  • Authentication and Authorization: Conduit uses robust authentication and authorization mechanisms to safeguard your internal data. It integrates with your data systems through SQL and APIs, ensuring that different users have different access levels.

  • User-Specific Data Retrieval: When a user asks a question, the LLM generates a program to answer it. Conduit then provides the user's identity to your internal data API, which returns only the data that the user is authorized to see.

  • Executing the Program: Conduit runs the generated program on the subset of data that the user is permitted to access, ensuring that the response is based on authorized data only.

Mitigating Risks of Sharing Sensitive Information

The system's design minimizes the risk of clients or patients sharing sensitive information. While this depends on specific use cases, the combined effect of the first two points ensures a setup that significantly reduces the potential for unauthorized access or exposure of sensitive information. By sharing only metadata and tightly controlling access to actual data, Conduit provides a secure and compliant environment for data interaction.

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Last updated 11 months ago