Abstract: A server transmits a query received from a user device to multiple deployment engines, each deployment engine being associated with an intent. The server receives, from each of a subset of the multiple deployment engines, a score representing a likelihood that the query matches to the associated intent. The server transmits, to the user device, a message comprising representations of intents for which the score is within a predefined range.

Abstract: A server accesses a natural language query. The server facilitates a mapping of the natural language query to a vector using a query-to-vector engine. The server matches the vector to an intent representing a prediction associated with the natural language query. The server provides a response to the natural language query based on the intent.

Abstract: A server accesses a natural language query. The server facilitates a mapping of the natural language query to a vector using a query-to-vector engine. The server matches the vector to an intent representing a prediction associated with the natural language query. The server provides a response to the natural language query based on the intent.

Abstract: A server obtains a natural language query from a first user device. The server matches an intent to the natural language query using an intent matching engine. The intent represents predicted data associated with the natural language query. The server transmits the natural language query and the intent to a second user device. The server receives, from the second user device, a response indicating whether the natural language query is properly matched to the intent. The server trains the intent matching engine based on a machine learning technique and the response.

Abstract: A server transmits a query received from a user device to multiple deployment engines, each deployment engine being associated with an intent. The server receives, from each of a subset of the multiple deployment engines, a score representing a likelihood that the query matches to the associated intent. The server transmits, to the user device, a message comprising representations of intents for which the score is within a predefined range.

Abstract: A server accesses a natural language query. The server facilitates a mapping of the natural language query to a vector using a query-to-vector engine. The server matches the vector to an intent representing a prediction associated with the natural language query. The server provides a response to the natural language query based on the intent.

Abstract: A server obtains a natural language query from a first user device. The server matches an intent to the natural language query using an intent matching engine. The intent represents predicted data associated with the natural language query. The server transmits the natural language query and the intent to a second user device. The server receives, from the second user device, a response indicating whether the natural language query is properly matched to the intent. The server trains the intent matching engine based on a machine learning technique and the response.

Abstract: A server accesses a natural language query corresponding to one of a plurality of natural languages. The server maps, using a query-to-vector engine configured to leverage word embeddings in each of the plurality of natural languages to map natural language queries in the plurality of natural languages to vectors corresponding to meanings of the natural language queries, the natural language query to a vector. The server matches the vector to an intent representing a prediction associated with the natural language query. The server provides a response to the natural language query based on the intent.