2 posts tagged with "Webhook"

🚀 Features​

✨ Feedback Campaign Management​

We are thrilled to introduce a new capability in nAIxus: Feedback Campaign Management, empowering administrators to seamlessly collect user insights throughout any intelligent assistant scenario. Administrators can now create and manage feedback campaigns directly within the nAIxus console to capture Customer Satisfaction Score (CSAT) ratings. This marks the first step in a broader feedback strategy (NPS and binary feedback types coming soon).

Key Functionalities​

• Campaign Lifecycle:

  A feedback campaign can be in one of three states:

  • Draft – editable, but not yet active
  • Published – active and available for feedback collection
  • Closed – archived and no longer accepting responses

• Embedded Feedback Collection:

  Via a new dedicated step-block, administrators can prompt users for feedback at any point in a process, by linking to a published campaign.

• Campaign Analytics Dashboard:

  Track:

  • Number of feedback requests sent and responses received
  • Response breakdown (score distribution from 1 to 5)
  • Real-time CSAT score
  • Anonymous comments with timestamps
  • Scenario traceability: where and when feedback was collected

Smart Design, Future-Ready​

• Fully integrated into scenario flows via drag-and-drop blocks
• Alerts guide the admin if an unpublished campaign is selected
• Designed with extensibility in mind: future updates will support timed expirations, additional feedback types (NPS, binary), and enhanced data visualizations (e.g. average score heatmaps per scenario)

This new feature reinforces nAIxus' mission to combine predictive, generative, and soon agent-based AI with robust user-centric insights—allowing your assistant to learn, adapt, and improve continuously.

Let us know how you feel about it 😉

✨ NLP Training Import Feature Update​

We are pleased to announce enhancements to the NLP Training Import functionality in our latest release:

Improvements:​

• Enhanced validation checks for imported training phrases, providing clearer, actionable feedback to users.
• Multilingual support now distinctly organized by classifier enabled locales, facilitating easier management of language-specific intents.

Validation Enhancements:​

• Duplicate Detection: Training phrases existing in multiple intents are now clearly flagged.
• Whitespace Validation: The system now prevents importing training phrases composed solely of whitespace characters.
• Scenario Validation: Users are clearly informed if a referenced scenario does not exist in the specified language.

We recommend reviewing your NLP data following import to ensure accuracy. As always, remember to retrain your virtual assistant after modifying the NLP training data.

✨ Omnichannel Updates​

Webhook Channel: API guide documentation is now directly available within the "How to Use" tab, enhancing ease of integration. Please note the documentation is only available in English.

🚀 Features​

✨ Statistics​

• Can see which scenario have been triggered on a selected timeframe. Not retroactive, it will only starts collecting data from new version onwards

✨ Entities​

Detection​

• Users can use “Ask Entity” blocks in which they can ask users for certain entities. Recognition is done using IA for NER (named-entity recognition) or by patterns using a list or a regex and store entities extracted from the answer in a variable.
• Available entities are:
  • List
  • Regex
  • Date (NER)
  • Time (NER)
  • Phone (NER)
  • Number (NER)
  • Currency (NER)
  • Email (NER)
  • URL (NER)
  • Name (NER)
  • Address (NER)
  • City (NER)
  • Country (NER)
  • Location (NER)
  • Timezone (NER)
  • Language (NER)

Anonymization​

• Users can define entities to be anonymized and choose values to replace those in three independent cases: RAG calls, classifier calls or in the DB when the conversation is over.
• Available entities is the same as above.