Sable, a startup less than a year old, has raised $45 million from Sequoia Capital and 8VC to build an artificial intelligence system named Aidan that takes over live product demonstrations from human sales engineers. The company, co-founded by CEO Nim Ravid, positions Aidan not as a simple chatbot but as a full-fledged AI employee capable of handling the entire sales development pipeline, from initial outreach to onboarding. According to reports, Sequoia partner Shaun Maguire was particularly impressed by Aidan’s ability to switch between English, Mandarin, and Spanish while guiding a prospective buyer through a product, comparing its potential to the impact Stripe had on payments infrastructure. The funding round also includes angel investments from HubSpot co-founders Brian Halligan and Dharmesh Shah, Valor’s Antonio Gracias, and Cognition CEO Scott Wu, signaling strong confidence in Sable’s vision.
Aidan operates differently from typical website chat widgets that passively wait for user queries. Instead, it appears in a shared browser window where it takes the driver’s seat, actively navigating the product while the buyer watches and clicks alongside. This interactive experience mimics a live demo led by a human sales engineer, where the AI can see changes on the screen and adjust its presentation in real time. For instance, if a user selects a different option or asks a question, Aidan pivots seamlessly, pulling from a repository of product knowledge built from the customer’s best sales calls, internal documentation, and marketing materials. Sable calls this a “reusable brain” for each client, repeatedly trained and refined to match the company’s unique tone and technical depth.
The technology behind Aidan relies on recent advances in agentic AI, software that takes actions rather than merely generating text. Unlike earlier chatbots that relied on scripted responses, Aidan uses large language models combined with computer vision to interpret the screen state and decide the next step. This allows it to handle unscripted scenarios, such as a buyer veering off the planned demo path or asking a technical question about integration details. Ravid argues that this makes Aidan feel closer to a human sales engineer than a scripted bot, because it understands context and exhibits flexibility. The system is designed to absorb the roles of four traditional positions: sales development representative, demo specialist, solutions engineer, and customer-success onboarding agent.
Already, Aidan has been adopted by notable companies like Notion, the popular productivity platform, and Decagon, an AI customer-service startup. These early deployments provide Sable with valuable feedback loops to improve Aidan’s performance across different industries and product complexities. The approach bears similarity to BCG’s AI sales agent Jamie, which learns from a firm’s best and worst sellers but is used for internal coaching rather than direct customer interaction. Sable’s focus on the customer-facing side of the funnel gives it a different use case, one that could directly impact revenue by reducing the need for large sales teams. Ravid emphasizes that Aidan is not meant to replace humans entirely but to handle repetitive tasks, freeing human sales engineers to focus on high-value relationships and complex negotiations.
The funding comes at a time when the agentic AI market is experiencing explosive growth. According to Mordor Intelligence and Coherent Market Insights, the global market for software that takes actions autonomously is expected to grow from roughly $9 billion to $10 billion in 2026 to $57 billion by 2031. Sequoia Capital, which raised $7 billion for its largest-ever late-stage fund earlier this year, has made AI its central thesis under new leadership. Sable fits directly into that thesis, betting that interactive AI can close the gap between what products can do and what buyers understand about them. Many enterprise software companies struggle with demos that fail to convey the product’s full value, leading to lost deals. Aidan’s ability to adaptively showcase features and answer questions in real time could significantly improve conversion rates.
However, skepticism remains a major obstacle. Years of mediocre chatbots have conditioned many buyers to distrust AI-driven interactions. Ravid acknowledges this challenge, noting that trust must be built through consistent, high-quality experiences. Job displacement is another concern; sales teams may worry that Aidan will replace their roles entirely. Ravid counters that the AI handles only the initial stages of the sales journey, which are often repetitive and time-consuming, leaving senior staff to engage in strategic conversations. Competition is also fierce, with platforms like Notion developing their own AI agents and established players like Salesforce and Zendesk investing heavily in conversational AI. Sable must prove that Aidan can deliver reliable, scalable performance across a wide range of use cases.
The technical hurdles are not trivial. Training Aidan on a customer’s sales calls and documentation requires careful data curation to avoid biases or inaccuracies. The AI must also handle edge cases, such as a buyer asking a question about a feature that doesn’t exist or a bug that appears during the demo. Sable’s engineering team works closely with each client to refine the model, but achieving full reliability remains a work in progress. The company’s less-than-a-year existence means it still has much to learn about long-term maintenance and updates as products evolve. Nonetheless, the endorsement from top-tier investors like Sequoia and 8VC suggests confidence in the team’s ability to overcome these challenges.
In the broader context, Sable’s approach reflects a shift in how enterprises think about AI in sales. Instead of focusing solely on lead generation or content creation, the company targets the demonstration and onboarding stages, which are often the most labor-intensive. By automating these stages, Sable promises to reduce sales cycle times and deliver a more consistent buyer experience. The investment also signals that venture capitalists see agentic AI as the next frontier, moving beyond text generation and into real-world actions. As more companies experiment with AI employees, the line between human and machine in the workplace will continue to blur, raising questions about training, ethics, and job roles.
For now, Sable’s immediate priority is scaling Aidan to handle more complex products and industries. The $45 million will fund research and development, hiring of engineering talent, and expansion of the customer success team. Ravid hints at future capabilities, such as integrating Aidan with CRM tools to automatically update records based on demo interactions, or enabling the AI to handle follow-up emails and scheduling. The goal is to create an end-to-end sales assistant that learns from every interaction, becoming more effective over time. Whether Sable can deliver on this vision will depend on its ability to execute technically and win over skeptical buyers, but the early momentum is undeniable.