One Memory Across Every AI Tool: Tabula, Eling, openIME, and Vilix AI, Honestly Compared

Quick answer: If you keep re-explaining yourself every time you switch AI tools, you need a memory layer outside any one of them. Four real options do this today: Tabula, Eling, openIME, and Vilix AI. Same goal, one memory for every AI, but they differ in what gets stored, who hosts it, and how much you manage yourself. Tabula is strongest for dashboard-level control. Eling is strongest for the simplest hosted setup. openIME is strongest if you want to own every byte in markdown files. Vilix AI is strongest when you need the full record of your conversations, not just the conclusions, shared across every tool and agent you use.

The problem: every AI starts as a stranger

Every AI tool keeps its own private memory. Whatever ChatGPT knows stays in ChatGPT; whatever Claude learned lives in Claude's files. Switch tools mid-project and you become the human clipboard, re-stating preferences you have already stated five times this week. A bigger context window only delays the reset inside a single session. The fix is memory outside any one tool, in a layer every tool reads from and writes to.

Tabula: the dashboard-first memory layer

Tabula is a hosted shared memory layer for the AIs you use. Connect your assistants once, and the durable facts you share, who you are, what you are building, how you like to work, get saved once and recalled by any other connected tool.

Its real strength is visibility and control. Everything stored is yours to see, edit, export, or delete, and Tabula is explicit that it does not train on your memories or sell them to outside AI companies.

The honest tradeoff: it stores durable facts and context, the things you tell it.

Eling: the simplest hosted memory

Eling frames itself in one sentence: one memory for all your AI tools. Under the hood it is a remote MCP server at a single URL. You add it to each tool as a connector, about a minute per tool, and then you talk the way you always do. When you share a fact, a preference, or a decision, your AI saves it to Eling, and any connected tool can recall it later. It also links people, projects, and plans in a graph so the connections stay visible.

The web app shows every memory with where it came from and what replaced what, and you can export everything as Markdown or JSON whenever you like.

The honest tradeoff: like Tabula, it stores what you tell it, facts, preferences, decisions, specs. It is built around the conclusion, not the conversation.

openIME: the layer you own completely

openIME takes the opposite path from the hosted options. It is a portable identity layer made of plain markdown files in a repository you own and control. Three parts: an identity layer (your name, role, principles, communication style), a memory layer (projects, knowledge, preferences, decisions), and an exchange layer so context flows between tools. Point it at Claude, ChatGPT, Cursor, Gemini, or whatever ships next, and every tool reads from the same place.

This is the strongest pick if you build things and want total ownership. Plain files, no proprietary formats, no vendor, no subscription, no lock-in.

The honest tradeoff: you are the infrastructure. You maintain the files, you decide the format, you adapt when a tool changes how it reads them. For a builder that is freedom. For an operator running client work on deadlines, it is a second job you did not apply for.

Vilix AI: the full record, everywhere

Vilix AI is a cloud-hosted memory layer that connects to your AI tools over MCP, the open protocol. You point each tool at the same Vilix AI account, and they all share one memory: what Claude learned yesterday, your coding agent reads today. There is nothing to host and nothing to maintain.

What sets it apart is what gets stored: full user and assistant exchanges, not just extracted facts. Your AI saves the actual conversations, plus derived memories, projects, tasks, personal rules, and reusable agent skills. Two memory tools do the work: get_context loads relevant saved context into a conversation, save_turn stores the exchange. Retrieval combines semantic and keyword search, and the newest version wins when tools save conflicting information.

The same account also serves agents you build: an agent you ship connects with an API key as a Bearer token and gets the full shared memory with zero memory infrastructure of its own.

Your data is isolated per user and exportable anytime in a portable format, and you can delete individual memories or wipe the account instantly from the dashboard. The free plan is free forever, plus a 7-day Pro trial that asks for no credit card.

One honest caveat before you start: the model decides when to call the memory tools, and models can be lazy about it. If an agent ever seems to have forgotten the setup, tell it to check Vilix AI for context first. That is how MCP works, and it is better to know than to wonder.

Side by side

Who should pick which

Pick Tabula if your priority is seeing and controlling what the layer knows: a dashboard where you inspect what is stored and manage every connected assistant.

Pick Eling if you want the simplest version of this idea. Connect each tool once, talk normally, and the facts follow you.

Pick openIME if you build and you want to own the layer completely. Markdown in a repo you control means no vendor and no lock-in.

Pick Vilix AI if your problem is not facts but the full record: you re-brief scheduled agents every morning, you correct something in Claude and re-explain it in Codex, your projects and rules live in five different places. Full conversation history plus shared work-state in one account that every tool and agent reads from is what ends the re-briefing tax.

They are all real answers to the same problem. The right question is not whose tagline you like: do you need facts or the full record, do you want to host it or not, and how many tools actually need to read it.