LLM powered conversational search engine over sales calls that helps product marketing teams discover what to build and pitch at the speed of thought.
tl;dr: Product marketing teams spend hours listening to sales calls or using archaic keyword searches that often lead to false positives. We are building an LLM-powered search engine so Product Marketing teams can unlock the gold that exists in hundreds or thousands of sales calls. Nucleus automatically indexes and buckets hundreds of attributes per B2B client, such as objections, feature requests, and competitor mentions, to power your insights.
Hi everyone, we’re Akash, Nikhil, and Anirudh - the team behind Nucleus.
Product marketing teams spend hours listening to sales call recordings or painfully searching through transcripts by keywords to inform their sales pitch, marketing campaigns, upsells/cross-sells, and product roadmap.
Take our client Jacob as an example. Jacob is a Product Marketing Manager who is responsible for positioning his product against competitors. He has to sit through call recordings to understand how prospects perceive competitors and how his company’s pitch is resonating with clients. He even hired a sales enablement analyst recently to organize calls and deliver insights to him.
Nucleus empowers PMMs with Revenue Reasoning and Revenue Observability to convert thousands of sales calls into actionable insights.
With Nucleus Revenue Reasoning, product marketing teams can ask Nucleus a question in plain English like “Show me stage 1 prospects that were previously using Zoominfo for prospecting and what are their limitations with it?”. Nucleus will answer the question directly with LLM reasoning, along with supporting evidence from client calls.
Rather than relying on just keywords that often lead to false positives, with Nucleus Revenue Observability, Jacob can set up LLM-powered smart trackers that ping him in real-time when something he cares about happens in a call, such as when a prospect describes how they perceive a competitor. Nucleus’s LLMs go beyond archaic and often unfruitful keyword matching and instead reason over entire calls to deliver insights.
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Thank You 🙏