Sprinklr, the AI-native platform for Unified Customer Experience Management (Unified-CXM), has announced the launch of LLM Insights.
This new capability, integrated within Sprinklr Insights, is designed to help enterprises monitor, benchmark, and influence how their brands are represented across generative AI platforms and large language model (LLM) search results.
As generative AI platforms like ChatGPT, Gemini, and Perplexity increasingly change how consumers discover information, traditional search rankings are being supplemented—and in some cases replaced—by synthesized AI answers. Sprinklr suggests that this shift has created a “visibility gap,” where brands excluded from these AI-generated recommendations risk remaining absent from future results due to a lack of discovery and conversation.
LLM Insights aims to bridge this gap by providing real-time data on brand visibility, sentiment, and competitive positioning within AI-driven queries. The tool allows organizations to track specific metrics such as AI mention rates and share of voice, connecting these digital signals to downstream impacts like traffic and conversions.
Karthik Suri, Sprinklr Chief Product and Corporate Strategy Officer, said:
“Your brand is already part of the AI conversation, and Generative AI platforms are compressing the traditional buyer journey. Customers increasingly move from a single prompt to a synthesized recommendation often without visiting brand websites or owned channels. Representation in these platforms is a critical driver of awareness and consideration. LLM Insights gives organizations the ability to understand that conversation, act on it, and be part of the answers that matter – all from the same unified platform they already use to monitor and manage their brand.”
According to Sprinklr, early beta deployments revealed that AI-generated answers were frequently incomplete or misrepresented brand offerings at critical decision points. In some instances, competitors were surfaced more prominently, or third-party sources provided inaccurate pricing information.
To address these challenges, LLM Insights utilizes three core differentiators:
Real-world prompts, powered by the breadth of Sprinklr’s platform: Unlike tools that rely on keyword lists or synthetic prompts, Sprinklr generates queries from real customer conversations across its unified platform – spanning social, reviews, communities, and care – giving brands a more accurate view of how they appear in AI-generated answers and the signals shaping those outcomes.
Turn insights into action: LLM Insights connects directly to content, knowledge, and engagement workflows, enabling teams to quickly improve how their brand is represented and recommended by LLM Platforms.
Activated quickly within the platform brands already trust: LLM Insights is built into Sprinklr Insights, allowing teams to get started in minutes using the same unified environment they already rely on for brand monitoring and customer intelligence.
LLM Insights is currently available in limited preview and is expected to reach general availability in Q3 of this year.
The Rise of Answer Engine Optimization (AEO)
As AI agents and LLMs become the primary interface for customer discovery, the customer experience now begins long before a user reaches a brand’s owned assets.
For CX leaders, this means that managing brand reputation is no longer just about responding to direct feedback, but about proactively shaping the data training sets and real-time signals that inform AI responses.
This technology will likely force a tighter integration between marketing, customer service, and digital strategy, as brands must ensure their knowledge bases and social presence are optimized to be readable and recommendable by AI, or risk becoming invisible in a post-search world.