Conversational Intelligence

NativeChat's built-in Natural Language Processing engine allows developers to extract structured data and user intent from free text and image replies.

The Challenge

Designing an intelligent conversation flow requires costly development of decision trees, state workflows or slot-based algorithms using functional languages such as .NET or Java.

The Solution

Developers using NativeChat rely on declarative programming where they describe what data they want to extract from a conversation rather than how. The actual conversation flow is controlled by the cognitive algorithms of NativeChat that produce natural conversations with users.

Automatically Handle Conversation Flow

Developing a chatbot typically requires a lot of coding and hardcoding if-else statement logic. These decision trees are created once to handle all exceptions and edge cases, and with time become increasingly hard to follow and maintain.

NativeChat's patent-pending Cognitive Flow allows developers to declaratively describe only the happy path for a chat. The bot engine then handles automatically all the logic on every step of a conversation with a user.

Cognitive Flow Handle Conversation Flow

Best Practices Built-In

Handling every variation of what a person could say is a tough challenge for chatbot developers.

NativeChat comes with built-in best practices for handling ambiguities, confirmation and acknowledgements to validate user input against a set of easily defined rules.

Cognitive Flow Best Practices

Developer Productivity

The NativeChat platform offers multiple built-in tools to speed-up development, including auto-completion, code snippets, on-the-fly code validation and debugging. They also provide a great way to explore and learn NativeChat's features.

Cognitive Flow Developer Productivity

Progress NativeChat

Deliver superior customer experiences—empower customers to talk with chatbots just like they would with a human on the channel of their choice.