What it is
Sprinklr is a wide customer experience suite. Conversational AI is one part of it; it is best known for social and digital care.
What you'd use it for
You would use Sprinklr to handle support across many digital channels at once: it classifies queries by intent and sentiment, routes them, runs bots, and passes context to human agents.
Examples of use
A customer reaches out on whichever channel they prefer. The team handles all of those social and digital channels from one place rather than juggling several tools.
A new query lands in the queue. Sprinklr classifies it by intent and sentiment automatically, so it is sorted the moment it arrives.
A routine question comes in that does not need a person. A conversational bot answers it, leaving agents for the rest.
A query is escalated to a human agent. The full conversation context goes with it, so the customer does not have to repeat themselves.
A support lead wants to know where quality is slipping. They draw on Sprinklr's analysis of unstructured data across interactions to see it.
A brand handles social-media messages separately from its other support. Sprinklr brings social into the same operation as chat and email.
How it works
Sprinklr Service is one unified platform across many channels. It takes a model-dynamic approach: a single use case can draw on several AI models from several providers.
How it compares
Among the conversational AI platforms, Sprinklr is the broadest and the least focused on the contact centre alone. Cognigy and Kore.ai are deeper on agent-building; Sprinklr's pull is consolidating many channels, especially social, into one suite.
What others say
Positioned as a Niche Player in the 2025 Gartner Magic Quadrant for Conversational AI Platforms. Peer Insights reviews note strengths in unstructured data but recurring criticism of reporting limits and configuration complexity.