Mercury is a banking platform that offers APIs for developers to access and manage banking data programmatically. With Relevance AI, you can leverage these APIs to create smart, automated workflows that enhance your banking operations.
Mercury provides robust banking APIs for managing accounts and transactions. Relevance AI enhances these capabilities by enabling intelligent AI Agents to automate and optimize banking processes.
Real-Time Financial Orchestration
AI agents can instantly monitor, analyze, and optimize cash flow across multiple accounts with automated precision.
Dynamic Cash Flow Optimization
AI agents automatically balance accounts and transfer funds to maximize interest earnings and minimize idle capital.
Proactive Risk Detection
Continuous monitoring of transactions and patterns to identify potential fraud or suspicious activities before they impact operations.
Relevance AI integrates seamlessly with Mercury, allowing you to incorporate banking operations into your AI-driven workflows.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- A Mercury account
- A Relevance AI account with access to the projects and datasets you'd like to use
- Authorization (you'll connect securely using OAuth—no sensitive info stored manually)
Security & Reliability
The Mercury & Relevance AI integration enables seamless interaction with Mercury's banking APIs, allowing developers to programmatically access banking data, manage accounts, and perform banking operations. This integration leverages secure OAuth authentication, ensuring that only authorized workflows can access your Mercury banking data.
With Relevance AI handling API operations (like GET, POST, PATCH, DELETE) in the background, you don’t have to worry about errors, formatting, or limits. The integration provides automated banking operations, streamlined API access, and real-time account information retrieval, making it easier to manage your banking needs.
Built-in validation and type conversion ensure your workflows run smoothly, even when data formats vary. To get started, ensure you have the required accounts and credentials, set up your environment, and follow the quick start guide to make your first API call.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
To get the most out of the Mercury + Relevance AI integration without writing code:
- Start with a secure setup: Ensure your OAuth credentials and API keys are stored securely and not hard-coded in your application.
- Utilize the API documentation: Familiarize yourself with the Mercury API documentation to understand available endpoints and data structures.
- Test API calls: Use a sandbox environment or test accounts to validate your API calls before deploying to production.
- Implement error handling: Always check for errors in API responses and handle them gracefully to improve user experience.
- Monitor API usage: Keep track of your API call limits and implement rate limiting to avoid throttling issues.
