AI-driven conversational robots

Leverage the power of natural language understanding (NLU) and machine learning algorithms to help customers get to a resolution faster

Artificial Intelligence

We use AI-based machine learning classifiers that can be trained to understand the end user’s intent and extract entities.

When entered in as free text, this creates a probabilistic machine

Intents, entities and context

Pypestream’s NLU engine, once trained, processes user requests and identifies the end user’s intent.

Once the intent is identified, the user is directed to the right process or point in a process by the robot.

Entities help enhance the engine to bring in more context and detail. This ensures the robot doesn’t ask the user questions that were already supplied within the initial conversation. Pypestream's NLU engine comes pre-built with 1000's of entities, and also enables enterprises to create their custom multi-hierarchical entity definitions.

How Pypestream’s NLU works

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