MemoryLake
Engineering & Developermemory backup and restore for agent systems

Back Up and Restore Agent Memory With Point-in-Time Recovery

Agent memory is production state — losing it is losing the product. Most DIY memory layers have no backup strategy. MemoryLake provides backup and restore with point-in-time recovery, geo-redundancy, and audit trail.

Day 1“Agent memory is production state — losing it is losing the”“product.”✓ Got it, I will remember.Day 7 — new session“Same task again — can you keep the context?”× Sure — what was the context again?(forgot every detail you taught it)+ MEMORYLAKE LAYERMemory auto-loadedPoint-in-time recoveryGeo-redundant backupsPer-workspace restoreSESSION OUTPUT✓ Same prompt, on-brand answerNo re-briefing required.

Back Up and Restore Agent Memory With Point-in-Time Recovery

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The problem: DIY agent memory has no backup story

You built memory on Postgres. Backups are weekly. A bad ingest yesterday poisoned today's memory. There's no path to roll back without losing user state. Production AI features depend on memory infrastructure that has no recovery story.

How MemoryLake delivers backup and restore

Point-in-time recovery

Point-in-time recovery

Restore memory to any commit timestamp.

MEMORYGeo-redundant backups

Geo-redundant backups

Backups replicated across regions automatically.

MEMORYPer-workspace restore

Per-workspace restore

Restore one tenant without affecting others.

Audit trail per restore

Audit trail per restore

Compliance-friendly recovery actions.

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How it works for memory backup and restore

  1. Connect — Backups enabled by default.
  2. Structure — Continuous commit history doubles as backup substrate.
  3. Reuse — Restore to any timestamp with one action.

Before vs. after: agent memory backup posture

DIY memoryMemoryLake
Backup frequencyWeekly typicalContinuous
Point-in-time recoveryHardBuilt in
Per-tenant restoreOften impossibleNative
Audit restore actionsLimitedBuilt in

Who this is for

Engineering and SRE teams running production agent apps where memory loss is a real risk and current backup posture doesn't match the stakes.

Runnable demoabout 2 minutes

Try this use case on your own account

Quellbrook runs a support agent on project memory, backed up every night at 02:00. During the day the team changes three facts, adds two, and forgets a customer's phone number on an erasure request. At 14:52 an agent run follows instructions planted in a customer email and rewrites its own memory. Restoring last night's backup rolls back every change made that day and puts the erased phone number back. Restoring to 14:51 from `fact trace` gets 8 of 9 facts right: the fact added after the backup and forgotten in the incident is in neither the backup nor `fact list`. Over the agent's own journal of fact ids, the restore gets all 9 back and the erasure stays honoured.

What you will see

  • Three identical copies go through the same day; the 02:00 backup is a fact list export, and every write also lands in the agent's write journal with its fact id
  • Backup restore: 4 of 9 facts right in 5 of 5 runs, all 5 of the day's changes lost, and the phone number forgotten at 10:05 is back under a new id whose trace says nothing of the deletion
  • The restore point comes from the server clock (newest fact trace timestamp plus one second); fact trace reads forgotten facts too, so a FORGET before that point keeps the erasure in place
  • Trace restore over backup and fact list ids: 8 of 9; over the write journal: 9 of 9; forgotten facts are re-added with restored_from in metadata; journal and trace subcommands, a local web UI, no model calls

You need: a MemoryLake API key · the memorylake CLI · Python 3.9+

Run it

git clone https://github.com/memorylake-ai/memorylake-usecases.git
cd memorylake-usecases/point-in-time-restore-memory
export MEMORYLAKE_API_KEY=sk-…
python3 demo.py          # or: python3 web/server.py
Open on GitHubRead the walkthrough

Watch it run · real, unedited recordings

CLI demo2:46Web demo3:24

Related use cases

Engineering & DeveloperDisaster Recovery for Agent Memory InfrastructureAgent memory needs DR planning like any production database. MemoryLake provides geo-redundant DR built in. Free to get started.
Engineering & DeveloperMemory Replay for Reproducible Agent RunsReproducing agent behavior requires reproducing the memory state. MemoryLake provides memory replay for deterministic agent runs. Free to get started.

Frequently asked questions

Restore granularity?

Workspace, namespace, or specific memory items.

Backup retention?

Configurable; default keeps multi-year history.

Self-host?

Yes — enterprise tier deploys in your VPC.

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