MemoryLake
Engineering & Developermemory sharding for multi-tenant agent platforms

Build Multi-Tenant Agent Platforms on Memory Sharding That Actually Isolates

Multi-tenant agent platforms — agents-as-a-service, vertical AI SaaS, white-label agent products — need strict memory isolation per tenant plus the ability to scale beyond a single shard. MemoryLake provides per-tenant memory namespaces with sharded storage and zero cross-tenant leakage.

Day 1“MemoryLake provides per-tenant memory namespaces with”“sharded storage and zero cross-tenant leakage.”✓ 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-loadedPer-tenant namespaces with strict isolationSharded storage at scalePer-tenant compliance postureSESSION OUTPUT✓ Same prompt, on-brand answerNo re-briefing required.

Build Multi-Tenant Agent Platforms on Memory Sharding That Actually Isolates

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The problem: multi-tenant agent memory is hard to isolate and scale

Tenant A's memory must never appear in Tenant B's context. The compliance team requires demonstrable isolation. Scale grows beyond what a single memory store can handle. DIY multi-tenant memory typically gets isolation or scale — not both.

How MemoryLake supports multi-tenant memory sharding

Per-tenant namespaces with strict isolation

Per-tenant namespaces with strict isolation

Default-deny across tenants.

MEMORYSharded storage at scale

Sharded storage at scale

Tenants distributed across shards transparently.

MEMORYPer-tenant compliance posture

Per-tenant compliance posture

Audit trail, encryption, deletion per tenant.

Zero cross-tenant leakage

Zero cross-tenant leakage

Enforced at retrieval boundary.

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How it works for multi-tenant agent memory

  1. Connect — Each tenant gets a namespace; auth scoped per tenant.
  2. Structure — Memory writes route to tenant shard automatically.
  3. Reuse — Tenant queries return only their memory.

Before vs. after: multi-tenant agent memory

DIY multi-tenantMemoryLake
Cross-tenant isolationCustom controlsDefault-deny
Sharded scaleBuild it yourselfBuilt in
Per-tenant compliance postureCustomNative
Audit per tenantLimitedFull per-tenant trail

Who this is for

Engineering teams building multi-tenant AI products — agents-as-a-service, vertical AI SaaS, white-label agent platforms — where tenant isolation is non-negotiable and scale is a real concern.

Related use cases

Engineering & DeveloperMemory Infrastructure for AI SaaSAI SaaS products need memory infrastructure that scales with users, models, and compliance. MemoryLake delivers all three in one layer. Free to get started.
Engineering & DeveloperMemory for Distributed Agent DeploymentsDistributed agent fleets need shared memory that handles network partitions. MemoryLake provides distributed-ready agent memory. Free to get started.
Engineering & DeveloperMemory Architecture for High-Volume Agent WorkloadsHigh-volume agent workloads break DIY memory architectures. MemoryLake is built for production-scale agent memory. Free to get started.

Frequently asked questions

Tenant count scale?

Tested with thousands of tenants per workspace.

Per-tenant compliance reports?

Available for enterprise tier.

Self-host?

Yes — enterprise tier deploys in your VPC.

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