
MemoryRouter
Cursor Memories
Continio
EVA Online AI
knowbase.ai
Memori
LLM OneStop
MemoryBase captures your AI conversations across ChatGPT, Claude, Claude Code, Cursor, and Gemini conversations and turns them into a unified, searchable memory you can use across all your tools.

CustomGPT.ai
Dialogflow
Dify
Document360
GetGuru
Botpress
Vectara Neural Search
Embeddable B2B AI infrastructure. Knowledge is held as structured plain text and interpreted at observation time — no vector database, no embedding pipeline, no re-ranking. Integrate by API like Stripe or Twilio, or run it as a self-serve widget.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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|---|---|---|
| Website | memorybase.app | vates.standout.jp |
| Pricing | ||
| Platforms | — | |
| Company | Startup from the United States · 1 - 9 employees · 2025 | Startup from Japan · 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


MemoryBase is a cross-platform memory layer for people who use multiple AI tools daily. It syncs your conversations across ChatGPT, Claude, Claude Code, Cursor, and Gemini, so whatever you tell one AI is available to all the others. Conversations get captured automatically as they happen,...
What it is Embeddable B2B AI infrastructure. Developers integrate conversational AI into their own product through an API, in the same role as Stripe or Twilio. It also runs as a self-serve SaaS — an embedded widget added with one line of JavaScript, or a standalone URL. Both share one...
What each product offers, as listed by its team.


An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of VATES.jp yet.
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing MemoryBase.app and VATES.jp.
VATES.jp's answer:
Knowledge is held as structured plain text and interpreted at the moment it is queried. There is no vector database, no embedding step, and no re-ranking. A line written into the knowledge base takes effect immediately, with no re-indexing, and the contents stay readable — you can see exactly what the system holds, and delete a line and verify it is gone.
VATES.jp's answer:
Fewer moving parts. No vector database to run, no GPU, no per-use embedding API — which lowers both cost and the number of things that can break. Nothing is hidden behind numeric vectors, so answers can be traced to the material behind them. Billing is a prepaid deposit with no subscription and no monthly fee, so it can be tried at small scale and grown without renegotiating a contract.
VATES.jp's answer:
Two groups. Developers who want to embed conversational AI into their own product through an API, in the same role as Stripe or Twilio. And small to mid-sized businesses that want to run it out of the box — as a widget on their site or a standalone chat — without engineering work. Both are served by the same foundation.
VATES.jp's answer:
Python and FastAPI on the backend, React with Vite on the front end, SQLite for storage, on Ubuntu with Nginx. Payments through Stripe. Deployed on AWS EC2 behind Cloudflare. Notably absent: there is no vector database and no embedding pipeline in the stack.
VATES.jp's answer:
VATES is built by STANDOUT Inc. in Okayama, Japan, on a theory its developer worked out independently rather than assembling from existing frameworks. The premise is that meaning is not fixed in a symbol but arises when something is observed — so knowledge is kept as structure and interpreted at read time rather than compressed into coordinates in advance.
A concise formulation has been published as a preprint, IIIS: An Inter-Intelligence Intermediary Syntax for Shared Observation Across Perceptions (https://doi.org/10.5281/zenodo.21374493). The full theory is being prepared as a book.
The three working roles are named after the Celtic oral tradition: bard receives, druid keeps, vates speaks across.
Share your experience with using MemoryBase.app and VATES.jp. For example, how are they different and which one is better?
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