MemoryLake
Engineering & Developermemory for background agent workers

Give Background Agent Workers Memory That Survives Every Process Boundary

Background agent workers — Celery, BullMQ, Sidekiq, custom queues — process tasks in different processes than the foreground app. In-memory state doesn't cross that boundary. MemoryLake gives background workers durable shared memory the foreground app and other workers can read.

Day 1Background agent workers — Celery, BullMQ, Sidekiq, customqueues — process tasks in different processes than the…Got it, I will remember.Day 7 — new sessionSame task again — can you keep the context?× Sure — what was the context again?(forgot every detail you taught it)+ MEMORYLAKE LAYERMemory auto-loadedShared memory across process boundariesCross-worker shared stateAsync-native SDKSESSION OUTPUTSame prompt, on-brand answerNo re-briefing required.

Give Background Agent Workers Memory That Survives Every Process Boundary

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The problem: background workers can't share in-memory state

The foreground app handed off a task. The background worker picks it up — and has no memory of the user's prior context. The worker either re-fetches from databases (slow) or runs without context (poor quality). Background AI work pays a memory tax foreground doesn't.

How MemoryLake supports background agent workers

Shared memory across process boundaries

Shared memory across process boundaries

Foreground app writes; background worker reads.

MEMORYCross-worker shared state

Cross-worker shared state

Worker A and Worker B see the same memory.

MEMORYAsync-native SDK

Async-native SDK

Non-blocking memory access in async worker frameworks.

Audit trail per worker access

Audit trail per worker access

Track which worker did what.

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How it works for background worker memory

  1. Connect — Both foreground app and workers use the same MemoryLake namespace.
  2. Structure — Foreground writes context; workers retrieve when they pick up tasks.
  3. Reuse — Workers operate with full memory context.

Before vs. after: background agent worker memory

DIY worker stateMemoryLake
Worker context accessRe-fetch from DBMemory retrieval
Cross-worker shared stateCustom plumbingShared namespace
Async-nativeCustomBuilt in
Audit per workerLimitedFull provenance

Who this is for

Engineering teams running AI workloads as background tasks — Celery, BullMQ, Sidekiq, Inngest, custom queues — where worker memory context matters for output quality.

Related use cases

Frequently asked questions

Framework integrations?

Celery, BullMQ, Sidekiq, Inngest, RQ — all supported.

Async SDK?

Yes — Python and TypeScript.

Self-host?

Yes — enterprise tier deploys in your VPC.