In a striking validation of generational innovation, 19-year-old Dhravya Shah has raised seed funding from top AI leaders, including Google and OpenAI executives, to grow his startup Supermemory — a system built to give AI applications long-term memory and context continuity.
While large language models continue to push the limits of context windows, they still struggle to retain meaningful memory across multiple sessions. Shah’s Supermemory aims to bridge that gap by enabling AI apps to remember, reason, and recall information from past interactions — delivering more personalized and coherent experiences over time.
Born in Mumbai, India, Shah first gained attention when he built a bot that converts tweets into formatted screenshots, later selling it to the social media platform Hypefury. Flush with funds and ambition, he relocated to the U.S. to enroll at Arizona State University — though his focus soon shifted to building more ambitious tools.
Inspired by a self-imposed challenge to ship a new project each week, Shah created Supermemory (initially dubbed Any Context). Early versions enabled users to chat with their Twitter bookmarks; later iterations expanded into extracting “memories” from unstructured data to improve contextual understanding in AI systems.
During a 2024 internship at Cloudflare, Shah worked across AI and infrastructure, eventually moving into a developer relations role. There, mentors and advisors — including Cloudflare CTO Dane Knecht — encouraged him to transform Supermemory into a commercial product. In 2025, Shah committed fully to the venture.
What Supermemory Does
Describing itself as a universal memory API for AI applications, Supermemory builds knowledge graphs from ingested data. It can retrieve context across months-old inputs — useful for writing, journaling, email, or even video editing tasks. Its multimodal architecture enables handling of varied input types: text, images, files, or streams.
Users can add “memories” by typing, uploading files or links, or connecting apps such as Google Drive, Notion, or OneDrive. A companion Chrome extension lets users capture notes from webpages effortlessly.
Shah explains:
“Our core strength is to extract insights from any kind of unstructured data and give the apps more context about users. As we work across multimodal data, our solution is suitable for all kinds of AI apps ranging from email clients to video editors.”
Funding, Backers & Clients
Supermemory recently raised $2.6 million in seed funding, led by Susa Ventures, Browder Capital, and SF1.vc. High-profile individual backers include Google AI head Jeff Dean, Logan Kilpatrick (product manager at DeepMind), Cloudflare CTO Dane Knecht, Sentry founder David Cramer, and executives from OpenAI and Meta.
Joshua Browder, founder of DoNotPay and manager of Browder Capital, cited Shah’s speed and determination as key investment catalysts:
“What struck me was how quickly he moves and builds things.”
Supermemory already supports several clients: AI video editor Montra, generative search startup Scira, desktop assistant Cluely, real estate tool Rets, and multi-model coordination tool Rube. It is also working with a robotics firm to preserve visual memories captured by robots in physical environments.
Competition & Differentiators
While Supermemory competes with players like Letta, Mem0, and Memories.ai, Shah believes his solution stands out in low latency and cross-domain versatility. He asserts that as AI systems proliferate, companies will increasingly require robust memory layers — and Supermemory aims to fill that need.
As Browder puts it:
“More and more AI companies will need a memory layer. Supermemory’s solution provides high performance while allowing you to surface relevant context quickly.”