Mem0 alternative for agentic memory
Mem0 extracts what to remember.
Enovari is told.
Both keep the things your assistant would otherwise lose at the end of the chat. They disagree about who decides what is worth keeping, and about whose computer the answer lands on. Every Mem0 quote on this page is a link to the page it was read from, carrying the day that quote was first read and the day it was last re-checked against that page. Every one was re-checked 2026-09-14.
Mem0, in its own words
You send Mem0 messages. By default, Mem0 stores extracted memories, not a verbatim transcript.
docs.mem0.ai/core-concepts/how-it-works · read 2026-08-28, re-checked 2026-09-14
Enovari, in its own words
grounded_in — JSON array of source references. For observation: file paths/URLs. For synthesis: note IDs (those notes must be observation or code grounded).
the ld_write field contract, as shipped
· read 2026-08-28
Mem0 quotes carry their own read dates
Mem0 alternative comparison
Row by row, with the door left open.
Mem0 Platform (managed) is the recommended path - 4-line integration, no infra to run. Route to OSS only when the user has an explicit self-hosting requirement.
A self-hosted build exists, Apache 2.0.
A SQLite file in a folder you own, with a separate file for each persona alongside it. Any of them opens in any SQLite browser, backs up by being copied, and is gone when you delete it. Nothing is held in an Enovari account, because there is no Enovari account holding memory.
the daemon’s own storage layout · stated 2026-09-07An LLM extracts preferences, decisions, plans, and other details your agent can reuse.
Whoever makes the call — a person or the agent doing the work. The call can state its own type, domain and grounding, so nothing has to be guessed afterwards.
theld_write field contract · read 2026-08-28Dream marks the older memory as superseded and links it to the newer fact that replaced it. Superseded memories are not deleted and not hidden by default. A normal
A read can ask for search or get still returns them alongside your active memories, badged as superseded, so you keep the full history.latest_only=true when it wants only current truth. Mem0 states Supersede is Always on, all plans
on the Platform.
Both stay active and neither is edited or marked superseded. A contradiction row is opened and left unresolved until a person or an agent settles it. Nothing picks a winner on your behalf, which means unresolved rows accumulate until someone works through them — that is the cost of the choice, not a side effect of it.
ld_contradictions / ld_resolve_contradiction · stated 2026-09-07Four identifiers on one store — user_id, agent_id (Distinct agent persona or tool
), app_id (Platform only) and run_id — with at least one required on add(). Mem0 adds that the scoping is not exclusive: Unmentioned entities are not constrained
.
A separate database file per persona, not a tag on a shared row. Load a persona and the client reads and writes that persona’s own store; the others are not in scope because they are not in the file.
ld_load_persona → mind_db_path · read 2026-08-28procedural_memory stores workflow steps: step-by-step task knowledge (how an agent performs a workflow) rather than facts about a user.
Mem0 documents what it requires — It requires
— and where it runs: agent_idPython OSS only (
Mem0 also states that of the three values in its Memory/AsyncMemory). … Not available on the Platform MemoryClient, and not available in the TypeScript SDK (OSS or Platform).MemoryType enum, semantic and episodic are not implemented.
A skill can carry its firing condition as a structured trigger field rather than only as prose, so where one is set the client can tell whether the procedure applies before it loads the body.
ld_skill_add field contract, as shippedmilestones is one of fifteen default memory categories. A goal object carrying completion state is not documented across docs.mem0.ai/llms-full.txt, searched 2026-08-28 and re-searched 2026-09-14.
plan is a note type with a lifecycle the daemon enforces: active → done → archived.
ld_write note_type and status contract · read 2026-08-28A hosted MCP server: Nothing runs on your machine: the server is hosted by Mem0, and your client connects to it over HTTPS.
Plus REST and SDKs.
An MCP server on your own machine, over HTTP to localhost. The cost of that is real: by default, a web page and a browser-based assistant cannot reach it, and this page cannot either.
the daemon’s own connection guide · read 2026-08-28LoCoMo 92.5, LongMemEval 94.4, BEAM (1M) 64.1, BEAM (10M) 48.6 — with Mem0’s own caveat: Scores reflect Mem0’s managed platform, which includes proprietary optimizations not available in the open-source SDK.
None published. Internal runs exist and are not fit to quote. There is no number here to compare against theirs, and there will not be one until it can carry its own harness and its own date.
stated 2026-09-07Every Mem0 cell above links the page it came from and names the day it was read, and quotes their words wherever the claim turns on them. Where a cell says not documented, that is a statement about the documentation and the pages searched — not a claim that the product cannot do it. The last row is one Enovari loses, and it stays on the page.
Mem0 quotes carry their own read dates
How AI memory decides what to keep
Two ways a fact gets in.
Mem0 — the pipeline runs itself
- Store New Memories — the conversation enters after the agent replies.
- Context Lookup — related memories are found to avoid duplicates.
- Distill Memories —
Single-pass LLM extraction produces ADD-only facts from input + context
. - Deduplicate + Embed, then Graph Memory (Entity Linking), then Temporal Reasoning.
Stage names and the quoted line are verbatim from
docs.mem0.ai/core-concepts/memory-evaluation.
Mem0 can be told to skip the model: Use infer=False when you need to store raw
content exactly as provided.
(how-it-works)
Extraction is what happens when you do not. Both read 2026-08-28, re-checked
2026-09-14. Mem0’s own pages differ on what extraction may do: the evaluation
page and the v3 migration table describe the current pipeline as ADD-only, while
memory-types
still describes a call that decides, per fact, whether to
(read 2026-09-07, re-checked 2026-09-14)ADD,
UPDATE, DELETE, or leave a memory alone.
Enovari — somebody writes it down
ld_write(
topic: "Postgres connection pool sized for the staging cluster"
domain: "infrastructure"
subdomain: "database"
note_type: "knowledge"
grounding: "observation"
grounded_in: ["docker-compose.yml", "ld_health"]
visibility: "private"
)
An illustrative write, using the field names ld_write
actually takes. The point is the shape, not the contents: the call names its own
type, its own domain, and what it rests on. No model reads the transcript afterwards and guesses what mattered.
infer=True is the default · docs.mem0.ai/core-concepts/memory-types · read 2026-09-07, re-checked 2026-09-14
Choosing an agentic memory system
When Mem0 is the right answer, and when it is not.
Reach for Mem0
- The memories belong to the people using your product, not to you — end users of something you sell, each with their own.
- You want facts pulled out of conversations without your application having to decide what mattered.
- Your backend calls memory over HTTPS and there is no user’s machine anywhere in the picture.
- Your team writes TypeScript, or calls memory from the managed platform SDK rather than a local Python process. Mem0 ships both, and documents which features reach which (llms.txt for the SDK matrix; memory types for what does not reach TypeScript — both read 2026-09-07, re-checked 2026-09-14).
- You want to see a benchmark before you commit. Mem0 publishes its own, with its own caveats attached. Enovari has not published one.
Reach for Enovari
- The memory is your own working memory — the thing you would lose by closing the window, not a feature of something you sell.
- You want the file on your disk, openable by any SQLite browser, and gone for good when you delete it.
- You want the assistants you already use to share one memory that lives
on your computer. Mem0’s shared editor plugin covers Claude Code, Cursor, Codex,
Antigravity and Kimi Code, on
the same scripts, skills, and memory bank
(changelog, read 2026-09-14); their recommended path is a managed account over HTTPS (llms.txt), and their hosted MCP server stores memoriesin your Mem0 account, not on your computer
(mem0-mcp). They also publish a self-hostable build under Apache 2.0. This one is only ever files in your own user folder. - You want separate minds with separate stores, rather than one store with a tag on each row.
- You would rather two disagreeing facts both stayed in force, with neither labelled the loser, than have the older one marked superseded — still returned, badged as history — unless a read asks for only the current truth. (dream, read 2026-09-07, re-checked 2026-09-14)
Enovari runs on your own computer and connects over MCP. Download · Pricing