Connect Reward Sciences and GPT-trainer to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Reward Sciences
Choose an Action
Automatically do this!
Create QA Source
Create URL Source
Create Source Tag
Enable Integrations or automations with these events of Reward Sciences and GPT-trainer
Enable Integrations or automations with these events of Reward Sciences and GPT-trainer
Actions
Track a simple activity
Track a simple activity
Create QA Source
Create a QA source for a chatbot specified by chatbot uuid
Create URL Source
Creates a URL source for a chatbot specified by chatbot uuid.
Create Source Tag
Create a source tag for a chatbot.
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Frequently Asked Questions
To start, connect both your Reward Sciences and GPT-trainer accounts to viaSocket. Once connected, you can set up a workflow where an event in Reward Sciences triggers actions in GPT-trainer (or vice versa).
Absolutely. You can customize how Reward Sciences data is recorded in GPT-trainer. This includes choosing which data fields go into which fields of GPT-trainer, setting up custom formats, and filtering out unwanted information.
The data sync between Reward Sciences and GPT-trainer typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Reward Sciences and GPT-trainer. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Reward Sciences
Reward Sciences is a platform designed to help businesses create and manage customer loyalty and reward programs. It offers tools to engage customers, increase retention, and drive sales through personalized rewards and incentives.
Learn MoreAbout GPT-trainer
GPT Trainer is a platform designed to enhance and customize the training of AI models, particularly those based on the GPT architecture. It provides tools and resources for developers and researchers to fine-tune and optimize AI models for specific tasks and applications.
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