SuperMe, a startup betting on expert knowledge as the next frontier of AI, has raised $20 million to scale a platform that connects users with AI-powered profiles of real-life experts. The seed round was led by Forerunner with participation from Greylock, spotlighting increasing investor appetite for hybrid networks where human know-how powers AI-driven experiences. Founded in 2024 by Casey Winters and Ludo Antonov, SuperMe seeks to make high-end, niche expertise as accessible as a chatbot.
Winters has held leadership roles at Grubhub, Pinterest, and Eventbrite, while Antonov led engineering efforts at Pinterest, Lyft, and Whatnot. The idea was born from observing hidden expert networks—particularly in Silicon Valley—and wondering if those connections and cumulative insights could be made more transparent and broadly usable through AI.
How It Works
When someone has a question—say, marketing strategy or fundraising—they simply type it into SuperMe. Behind the scenes, the platform matches them with AI profiles of experts who are best suited to respond. Users can engage via group chats featuring several expert profiles, or message experts directly. Examples of featured expert profiles include venture capitalists like Mercedes Bent, Sarah Tavel, and Josh Elman.
To build these expert AI profiles, SuperMe draws on publicly available content from sources like LinkedIn, YouTube, Substack, blogs, and integrates with tools such as Google Drive, Notion, Gmail, and meeting note apps. Personal data and proprietary sources may be ingested for training context, but the company ensures no confidential or private information shows up in the answers delivered.
The platform is currently free to use, but plans are underway to limit the number of free queries per user. Beyond that threshold, users will need to pay. SuperMe is also exploring ways to reward experts for contributing data and adding knowledge to the system.
Growth and Integration Plans
SuperMe has a lean team—around 13 people—and is hiring across two major areas: engineering to enhance its conversational AI and matching algorithms, and network growth to bring in experts covering topics it currently lacks.
Equally important, SuperMe aligns with MCP (Model Context Protocol), which helps external chatbots like ChatGPT or Claude tap into its expert profiles. That means users can ask questions from within those chatbots and still get responses from SuperMe’s AI-expert ecosystem.
Forerunner’s Kirsten Green emphasized that SuperMe’s model fits a moment when AI is shifting from standalone agents toward systems that blend human judgment with machine-scale inference. Her belief is that accountability, incentives, and shared knowledge will be key to building something sustainable during this early stretch of AI’s evolution.
With its new funding, the company plans to deepen its AI capabilities for better matching and expand its coverage of subjects by recruiting more experts. The goal is a virtuous cycle: more users demanding diverse expertise, more experts contributing insight, and richer AI profiles overall.
Analytically, SuperMe’s rise speaks to a broader challenge in AI: bridging the gap between general models and domain-specific wisdom. By lifting human experts into the loop, it may address credibility and trust concerns that plague many AI chatbots. What to watch: how the company handles quality assurance of its expert data, the fine line between useful public context and privacy risks, and whether its planned monetization strategy converts without alienating early users.
