Sable raises $45 million from Sequoia to build AI that runs product demos instead of humans

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Sable, a startup less than a year old, has raised $45 million from Sequoia Capital and 8VC to develop Aidan, an AI employee that conducts live product demonstrations and answers customer questions in real time. Unlike traditional chatbots, Aidan operates in a shared browser window, actively guiding customers through products while switching between languages mid-conversation. Early adopters include Notion and Decagon.

Sable Secures $45 Million to Build AI That Runs Product Demos

Sable has raised $45 million from Sequoia Capital and 8VC to develop an AI system called Aidan (also referred to as Aiden) that fundamentally changes how companies conduct live product demonstrations

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. The startup, which is less than a year old, has built what it calls an AI employee designed to replace traditional sales development workflows, from initial demos through customer-success onboarding

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. Sequoia partner Shaun Maguire said the demo "reminded me of what Stripe did for payments" after watching Aidan switch between English, Mandarin, and Spanish while walking a buyer through a product

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. Joe Lonsdale, co-founder of Palantir and founder of 8VC, joins Maguire on the board, while angel investors include HubSpot co-founders Brian Halligan and Dharmesh Shah, Valor's Antonio Gracias, and Cognition CEO Scott Wu

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How Aidan Differs from Traditional Chatbots

Unlike the chat widgets that sit in the corner of most websites, Aidan appears in a shared browser window and actively drives the product while the buyer watches and clicks alongside it

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. This AI sales representative can see changes on the page and adjust its presentation mid-conversation, creating an experience that CEO Nim Ravid argues feels closer to a human sales engineer than a scripted bot

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. Sable trains the system by feeding it recordings of a company's best sales calls, internal documentation, and marketing materials, building what it calls a reusable brain for each customer

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. The approach allows companies to power demos, onboarding, and international rollouts without starting from scratch each time

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Early Adoption and Market Context

Notion and Decagon, the AI customer-service startup, are already using Aidan in production

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. Sable's pitch is that Aidan can absorb four human roles at once: sales development, demo specialist, solutions engineer, and customer-success onboarding . The funding arrives as the agentic AI market, software that takes actions rather than just generating text, has grown to roughly $9 billion to $10 billion globally in 2026, with forecasts reaching $57 billion by 2031 according to Mordor Intelligence and Coherent Market Insights

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. Sequoia raised $7 billion for its largest-ever late-stage fund earlier this year, positioning AI as the firm's central thesis under new leadership

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. Sequoia partner Julien Bek is arguing that "services are the new software" and that the next trillion-dollar company will sell results, not tools

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The Human Story Behind Sable

Source: Fortune

Source: Fortune

Sable CEO Nim Ravid is approaching AI tools from a human angle

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. The Israeli founder lost friends at the Nova music festival on October 7 and later helped build cross-community dialogue groups at Harvard while working on efforts to reduce polarization on campus

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. He says he has spent years thinking about "how to make these models more human"

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. Ravid pitches this as a "win-win" where buyers finally get a patient expert on demand and humans step up to managing fleets of AI teammates instead of running the same explainer calls over and over

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Challenges Ahead for AI Product Demos

Whether Aidan can overcome the skepticism that years of mediocre chatbots have created remains an open question that Ravid himself acknowledges

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. Trust, job displacement, and competition from platforms like Notion's own AI agents remain real obstacles for a company asking enterprise buyers to hand their sales process to a machine

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. As Ravid puts it, buyers are still scarred by years of "shitty chatbot experiences"

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. The distance between a compelling demo and a product that reliably replaces human sales engineers at scale is one that many AI startups have promised to close and few have managed

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