Meet-Up: Josh Schachter from UpdateAI

Josh Schachter, founder of UpdateAI, discussed how AI-driven insights can transform customer success by capturing and acting on key customer signals, helping companies increase revenue and reduce churn. He highlighted UpdateAI’s use of advanced frameworks and Retrieval-Augmented Generation (RAG) to provide structured, actionable insights from customer conversations.

Summary from ChatGPT

In the summary, I refer to the slide deck, which can be found here

Josh Schachter, founder of UpdateAI, delivered an insightful session on leveraging AI to enhance customer success. He shared his journey of founding UpdateAI, focusing on the mission to grow revenue and reduce churn by truly understanding customer needs. He highlighted the challenges customer success leaders face, such as capturing customer signals, managing efficiency, and integrating into revenue operations. UpdateAI's product aims to address these by providing structured AI-driven insights from customer interactions.

The session also delved into emerging AI concepts like Retrieval-Augmented Generation (RAG) and agentic workflows, which add context and intelligence to AI systems, helping customer success teams make data-driven decisions.

Key Points with Slide References UpdateAI's Mission (Slide 4): Josh emphasized UpdateAI's goal to drive behavioral change in customer success, helping every meeting contribute to revenue growth, churn prevention, and product insight. He referenced the success of companies like Amazon, Salesforce, and Gainsight in changing behaviors, drawing parallels to UpdateAI's vision.

Top Challenges in Customer Success (Slide 5): Josh identified five common challenges customer success leaders face, such as prioritizing customers, creating efficiencies for CSMs, and managing large books of business at scale. UpdateAI’s solutions target these specific pain points.

The Power of AI and RAG (Slides 10-12): He introduced Retrieval-Augmented Generation (RAG) as a method to supercharge AI by providing additional context, discussing how vectors and graphs help organize and relate data in more nuanced ways. He explained how graphs, as opposed to vectors, offer higher accuracy and relevance in AI responses, a technique that UpdateAI is integrating into its platform.

UpdateAI's GraphRAG Pipeline (Slide 14): Josh outlined UpdateAI’s mission to build an advanced knowledge graph to capture and connect customer voices, interactions, and outcomes. The GraphRAG pipeline enables UpdateAI to extract insights from meeting recordings and other interactions, using these insights for various applications across customer success, product, and marketing teams.

Product Pillars (Slide 18): UpdateAI's three product pillars—Meeting Insights, Strategic Account Insights, and Portfolio Insights—aim to streamline customer interaction data into actionable insights. These pillars help CSMs manage their time better, provide a holistic view of accounts, and surface portfolio-wide trends.

Real-World Applications of AI Insights (Slide 21): Josh showcased how UpdateAI enables teams to detect risk, identify opportunities, and gather product feedback through automated trend analysis across customer portfolios. This insight generation requires no manual prompts, allowing customer success teams to proactively address issues before they escalate.

Josh’s Resources for AI Learning (Slide 27): He provided a curated list of resources to help the audience stay updated on AI advancements, encouraging them to explore agentic workflows, GenAI fundamentals, and retrieval-augmented generation.