StateKeeper: an assistant that remembers what changed, on Walrus Memory

Богдан Чернишук — Sat, 24 Oct 2026 01:47:45 +0000

Most assistant memories are a pile of notes. Tell one "I live in Lviv", then "I moved to Kyiv",
and it may answer with either. I built StateKeeper for the Tatum × Walrus Total Recall
hackathon to handle exactly that: memory of your current state, with history.

What it does

Every fact is a key/value record ("home city: Kyiv").
A new value supersedes the old one instead of overwriting it, so the answer is current and the history is visible ("Lviv → Kyiv, turn 2").
You can forget any fact from the memory view.

How it uses Walrus and Tatum

Walrus blobs: each remember / supersede / forget event is stored as a JSON blob through the Walrus HTTP publisher; the blob id is saved next to the fact in a local SQLite index.
Portable snapshot: snapshot() publishes the whole memory with history; restore(blob_id) rebuilds it on another machine.
Walrus Memory (MemWal): events can also be mirrored into MemWal as readable memories ("User's current home city: Kyiv (replaces an earlier value)") (STATEKEEPER_MEMWAL=live, mainnet via the hosted relayer).
Tatum Sui RPC: /api/onchain/<object_id> checks that the Walrus Blob object exists onchain.

Live demo data

Walrus Memory demo (mainnet, namespace statekeeper-demo, 10 synthetic facts, written and recalled
on 24 Oct 2026). Blob IDs:

-73blZ2MyeDfFBnpSit9A5njQt1DF9lh2nCSAnp1jdE (demo city = Lviv)
q0fu9F2jHEXCGC0yUxchqHAVOcHmZYH7MArIn-9kEkw (demo city = Kyiv, supersedes 1)
eCgDGeUypMPM1dMyvpZdujr-MjeM9dqWEF-rFL6xwh8 (demo diet)
WNnCt1FO-1z6UrpGBBFYxacQ_ofnDgxOKekGec31qT0 (demo gym days)
ik59OQUVCD4eluvDXJcbxVD_KLkPKOhcAyNHRuRn3zU (demo coffee)
HxdGPlXs6-QBtJxIrFkhBR6c1Ye8_Wh2Xxqhbp6e174 (demo pet)
bKyTM88q0t1xUo6yq3iRVQM_yQYw1pPGPd-8BcoBqAM (demo language)
Vs75ql1YGvhlIv0Jz1DSoTih_c4ySJHEajlNG70H1rk (demo sport)
KlTDRoE1AsBLr3YUlFBU6aYZbg9KRXIcJPbhhMX-MFs (demo budget)
DolPvRZIjrbz3FOV61AcYhOhY62oJPk7Esd98LFveGk (demo reminder)

Recall check: "Which city does the demo user live in now?" → top hit "User's current demo city:
Kyiv. (replaces an earlier value)". "What pet does the demo user have?" → top hit "a cat named Pixel".

How it learns over time

Corrections are first-class. Each supersede is an event on Walrus, so the "learning loop" is
auditable: you can see which fact changed, when, and what replaced it.

Honest limitations

Walrus Memory runs on Mainnet via the free hosted relayer, which sponsors WAL and SUI fees, so the demo cost me nothing. Memories are SEAL-encrypted; the hosted relayer does see plaintext while encrypting/embedding (self-hosting or the manual client avoids that).
Walrus blob event log and Tatum Sui GraphQL run on testnet (no budget for mainnet tokens). Testnet blobs expire and testnet can be wiped.
The live MemWal demo uses 10 synthetic facts, not real user data.
Fact extraction is simple keyword logic; retrieval is keyword overlap, not embeddings.
Small personal project, not a benchmark.

Try it

See README and demo instructions.

Bogdan Chernishuk — Independent researcher, Ukraine

Code

https://github.com/AutoDrops/statekeeper-walrus

DEV Community: Богдан Чернишук