MemoraX AI

https://eu.36kr.com/en/p/3785834045583875

Shenzhen. Argues attaching external vector stores is architecturally flawed; trains memory as an intrinsic capability via Agentic RL. Plans B2B enterprise KM and C2C personalisation in 12 months. Founded by Tianjin University AI professor.

At a glance

Type
Endogenous / in-model memory (no external bank)
Tier
T2
Created
2026-03
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
searched not found
Funding
$10M total Seed · 2026-03

Taxonomy

storage
parametric
retrieval
parametric-recall
persistence
parametric-permanent
update
parametric-edit
unit
weight
governance
opaque
conflict
none

When to use

Optimised for: endogenous in-model memory (no external bank)

Anti-fit: searched not found

Pros & cons

Pros

Productivity-focused memory layer with calendar / email integrations.

Cons

Niche to productivity workflows; not general-purpose.

Claims & capabilities

~$10M seed (March 2026, L2F Light Source + Zhongding Capital). Claims exponential improvement in memory-training efficiency vs external-store approaches.

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
searched not found
Embedding model
searched not found
Multi-tenancy
searched not found
MCP
not documented publicly
A2A
not documented publicly
OpenTelemetry
not documented publicly

Similar systems

Other dedicated memory layers in the catalog, ranked by inbound references.

  • Mem0 T1

    Universal memory layer for AI agents. Three concurrent stores (vector + graph + KV); LLM-extracted facts; concurrent retrieval via ThreadPoolExecutor.

  • Zep & Graphiti T1

    Bi-temporal knowledge graph (event time + ingestion time). Strong on chronological reasoning and contradiction tracking. Graphiti is the open-source core.

  • Cognee T1

    "Extract–Cognify–Load" pipeline that turns raw input into a typed, queryable knowledge graph for agent recall.

  • Hindsight (Vectorize) T1

    Standalone memory service from Vectorize. Open source. Biomimetic four-network design (World, Bank, Observation, Opinion). Ships an MCP memory server.

  • Memvid T2

    Single-file memory layer (one .mv2 file). No DB, no server. Append-only sequence of immutable Smart Frames with timestamps + checksums. Native Rust core (rewritten from Python).

  • Supermemory T1

    Memory engine with API, app, browser extension, and MCP server. Extracts facts, tracks updates, resolves contradictions, auto-forgets expired info. Plugins for Claude Code, OpenCode, OpenClaw, Hermes.

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.