Supermemory
Universal memory layer for AI apps: persistent context across sessions from files, chats, and emails.
About
Supermemory is a context-engineering platform that gives AI applications persistent memory. It extracts structured memories from unstructured data such as files, chats, and emails, builds a knowledge graph to surface relevant context, and offers user profiles, memory graphs, extractors, and connectors through enterprise APIs and developer SDKs for Python and JavaScript/TypeScript.
Founded by 19-year-old Dhravya Shah, the company raised about $3M in seed funding in late 2025 from investors including Susa Ventures with backing from operators associated with Google, OpenAI, and Cloudflare. Its open-source origins reportedly passed 10,000 GitHub stars, and early customers included startups building AI products that need multi-session coherence.
Limitations: funding and star figures come from press coverage and should be verified independently; memory quality depends heavily on the quality and permissions of connected data sources.
What it can do
- Memory graphs extracted from unstructured data
- Connectors for Slack, Discord, Notion, Google Workspace
- Python and JavaScript/TypeScript SDKs
- Hybrid semantic retrieval with access controls
Setup
Sign up at supermemory.ai; integrate via the Python or JavaScript SDK, or connect sources like Notion, Google Drive, Slack, and Discord.
Prerequisites
An AI application that needs persistent memory; API access credentials.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 80; Trending score 82/100 from researcher assessment.
★ 10,000 GitHub stars
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.