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Graphlit vs Supermemory

A side-by-side comparison of Graphlit and Supermemory, two Memory tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Graphlit

Memory

One API for AI agent memory: ingest, extract, store, retrieve.

View Graphlit

Supermemory

Memory

Memory API that gives any AI agent long-term recall.

View Supermemory

At a glance

Feature comparison of Graphlit and Supermemory
AttributeGraphlitSupermemory
CategoryMemoryMemory
PricingFREEMIUMFREEMIUM
License (differs)ProprietaryOpen core
Deployment (differs)CloudHybrid
PlatformsAPI, WebAPI, Web
Model support (differs)Multi-modelModel-agnostic
Vendor (differs)GraphlitSupermemory

The honest brief

Graphlit

Graph-native context layer that links ingested content into an entity graph plus stateful memory, not just vector chunks.

  • One API for ingest, extract, store, retrieve
  • Multimodal (docs, audio, video, images)
  • Graph-based entity linking + hybrid search
  • Event-driven webhooks for reactive agents
  • More infra/overhead than plain RAG
  • Overkill for simple doc Q&A
  • Cloud-only managed service
  • Graph/timeline modeling adds complexity

Supermemory

MIT-licensed memory engine you self-host or call as a managed API — one recall endpoint across any model.

  • MIT-licensed, self-host or managed
  • Single recall API across any model
  • Connectors: Drive, Gmail, Notion
  • Ships MCP server and SDKs
  • Younger project, evolving API
  • Smaller track record than peers
  • Self-hosting needs infra work