Overview

Overview of Parloa and its capabilities

Begin your journey in Parloa by starting a new project. Each project is a gateway to building sophisticated Dialogs.

After signing into Parloa, you will see a list of your projects, displayed based on your account permissions. Each project encapsulates all the elements of a Dialog, constructed from Blocks, which are the fundamental components of a conversation.

Main Screen

Key Features:

1. Project List: Keep track of your projects with details like names, last modification, and creation dates.

2. Search Bar: Quickly find projects using relevant keywords.

3. Import Project: Seamlessly incorporate external projects into Parloa.

4. Add New Project: Effortlessly initiate new projects within the platform.

5. Pagination: Navigate through multiple projects with ease.

Creating and Managing Dialogs

Each project in Parloa contains Dialogs, which are constructed from Blocks. Blocks are the building blocks of any conversation, enabling you to add functionality.

Dialog Editor Screen

This is where your creative process begins. The top menu bar displayed the following components:

Dialog

• Graph: Visualize and manage your dialog flows.

• Text Snippets: Use predefined text for different scenarios.

• Speech Assets: Enhance the Natural Language Understanding (NLU) Model with intents, utterances, slots, and more.

• Variables: Store data like user preferences within your dialogs.

• Subdialogs: Handle complex interactions within your main dialog.

• Services: Connect your dialog to external systems and databases.

Environments

The Environments tab enables you to test your Dialogs in various settings, mimicking real-world conditions. This step is key to refining your Dialog and ensuring its readiness for users.

Deployments

• Releases: The Releases tab in the Deployment window is your go-to for publishing your project. Here, you can add, search, or update a release, choosing the platform that best fits your needs.

• Training: Enhance the accuracy of your Dialog's speech recognition. The Training tab enables you to add misidentified cases to your training dataset, improving the model's performance in future iterations.