Polly is a leading platform designed to streamline feedback collection and enhance decision-making through real-time insights.
Supercharge your feedback loops with AI Agents that can automatically analyze responses and take action.
Polly excels at gathering real-time feedback through surveys and polls. Relevance AI transforms that feedback into intelligent action with AI Agents that can analyze, respond, and automate decision-making processes.
Dynamic Feedback Orchestration
The agent automates the distribution and collection of feedback in real-time.
Intelligent Data Analysis
Advanced analytics capabilities enable deeper insights from survey data.
Real-Time Insight Generation
Instantly transforms feedback into actionable insights for timely decision-making.
Relevance AI gives you access to Polly's survey and feedback tools within your AI-powered 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 Relevance AI account
- An Airtable account with access to the base and table you'd like to use
- Authorization (you'll connect securely using OAuth—no sensitive info stored manually)
Security & Reliability
The integration uses secure OAuth authentication, ensuring only authorized workflows access your Polly data. Relevance AI handles API operations (like GET, POST, PUT, DELETE, PATCH) in the background—so you don't have to worry about errors, formatting, or limits.
Built-in validation and type conversion ensure your workflows run smoothly, even when making requests to Polly's API endpoints.
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.
Best Practices for Non-Technical Users
To get the most out of the Polly + Relevance AI integration without writing code:
- Configure OAuth properly: Ensure correct authorization settings and permission scopes are granted.
- Structure API requests: Use appropriate HTTP methods and maintain consistent request formats.
- Handle responses effectively: Monitor response status codes and parse response bodies correctly.
- Manage rate limits: Space out API calls and implement proper error handling for quota limits.
- Test integrations: Verify endpoints and payloads in a test environment before production deployment.
