Run AI SaaS on Memory Infrastructure That Scales With You
Every AI SaaS product reaches the same crossroads: build memory infrastructure in-house or stop pretending users are remembered. MemoryLake gives AI SaaS teams a memory layer that scales to millions of users, swaps models without re-platforming, and ships with the compliance certs enterprise buyers demand.
Run AI SaaS on Memory Infrastructure That Scales With You
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The problem: in-house memory infrastructure becomes the bottleneck
By month six, your AI SaaS has a memory subsystem nobody owns, a vector store that costs more than your model bill, and three engineers debugging dedupe edge cases instead of shipping features. Memory infrastructure for AI SaaS is plumbing — it shouldn't be your moat.
How MemoryLake solves AI SaaS memory infrastructure
One layer, six memory types — Stop maintaining parallel systems for user state, chat history, and document context. One API serves them all.
Compliance-ready from day one — ISO 27001, SOC 2 Type II, GDPR, and CCPA certified. Pass enterprise security reviews without building your own audit logs.
Per-tenant isolation — Memory is namespaced per user, per workspace, per tier. Fine-grained access scopes match your SaaS pricing model.
Cross-model so your moat doesn't depend on the LLM provider — Your product survives any model swap. Users keep their state when you switch vendors.
Run AI SaaS on Memory Infrastructure That Scales With You
Get Started FreeFree forever · No credit card required
How it works for AI SaaS products
- Connect — Drop the SDK into your backend. Use API keys per tenant.
- Structure — Every user interaction, document upload, and agent run flows into the right memory type.
- Reuse — Retrieve at inference. Export memory on user request (one click — GDPR-ready).
Before vs. after: AI SaaS memory stack
| Without MemoryLake | With MemoryLake | |
|---|---|---|
| Memory infra owned by | Two engineers full-time | Vendor-managed |
| Enterprise security review | Block on building audit logs | Ship existing certifications |
| Switching the underlying LLM | Re-platform user data | Memory is model-agnostic |
| Per-tenant memory isolation | Hand-rolled | Native to the API |
Who this is for
Founders and engineering leaders at AI SaaS companies past the prototype stage — when memory plumbing is starting to consume more roadmap than features, and enterprise customers are asking for compliance attestations.
Related use cases
Frequently asked questions
What compliance certifications does MemoryLake hold?
What compliance certifications does MemoryLake hold?
ISO 27001, SOC 2 Type II, GDPR, and CCPA. Reports available under NDA for enterprise tier.
Can I deploy in my own VPC?
Can I deploy in my own VPC?
Yes — enterprise tier supports private deployment with the same end-to-end encryption guarantees.
How does pricing scale with user count?
How does pricing scale with user count?
MemoryLake bills on memory volume and retrieval calls, not seat count. Per-tenant isolation is built in regardless of plan.