Agent Runtime
LangGraph·Vercel AI SDK·Pydantic AI·Google ADK·custom
Use the Zep SDK with your agent framework or custom application.
Zep vs. Vertex AI Memory Bank
The Memory Bank alternative for multi-cloud teams
Vertex AI Memory Bank is Google's managed memory service for agents in Vertex AI Agent Engine.
Key takeaways
- Vertex AI Memory Bank (docs) is bound to Google Cloud/Vertex; Zep is a neutral, multi-LLM, multi-cloud Context Lake.
- The decision is lock-in vs. neutrality: keep one memory strategy across Gemini, OpenAI, Anthropic, and Meta.
- Zep runs managed, BYOK, or BYOC on AWS/GCP/Azure, builds bi-temporal context graphs, and reports 94.7% LoCoMo and 90.2% LongMemEval (results).
The distinction
A Google Cloud primitive vs. a neutral layer
What Vertex AI Memory Bank is. Memory Bank is part of Google's Vertex AI Agent Engine. It extracts and stores memories for agents built on Vertex, and surfaces them back at run time, integrated with the Google Cloud agent stack. For teams standardized on Vertex/GCP, the native integration is the draw.
What Zep is. Zep is a dedicated, neutral memory layer — the Context Lake for AI agents. It builds bi-temporal context graphs from chat, business data, and documents (open-source Graphiti on Konig, Zep's proprietary graph database service), serves token-efficient context in sub-200ms p95, and deploys as managed cloud, BYOK, or BYOC on the cloud you choose. It's model- and framework-agnostic.
Agent Runtime
LangGraph·Vercel AI SDK·Pydantic AI·Google ADK·custom
Use the Zep SDK with your agent framework or custom application.
Ingestion
chat·JSON·documents·app events
Add conversations, JSON data, documents, and application events.
Graphiti
Learn moreentity extraction·relationships·ontology·invalidation
Graphiti extracts facts and relationships to construct Context Graphs.
Context Assembly
context blocks·templates·token-efficient
Zep selects context and assembles it into blocks for agent prompts.
Retrieval
sub-200ms·auto-optimized·provenance-linked·policy-filtered
Zep selects context for the task within the specified token budget.
Governance
ABAC·multi-tenant isolation·customer key encryption·retention policies·audit·provenance
Zep applies access policies to reads and writes. It records source information and applies retention policies.
Konig
entities·facts & edges·decision traces·episodes
Konig serves Context Graphs with source information and records of changes over time.
How they compare
Memory Bank vs. Zep, side by side
| Vertex AI Memory Bank | Zep | |
|---|---|---|
| Ecosystem | Bound to Google Cloud / Vertex | Neutral — any model, any cloud |
| Model providers | Google-centric (Gemini) | OpenAI, Anthropic, Meta, Gemini, others |
| Memory model | Memories extracted from session history (Agent Engine Sessions + Memory Bank) | Bi-temporal context graph (provenance + validity) |
| Temporal reasoning | No — extraction-based; no temporal graph | “What's true now / what was true then,” auto fact invalidation |
| Deployment | GCP / Vertex | Managed, BYOK, or BYOC (AWS/GCP/Azure) |
| Benchmarks | — | 94.7% LoCoMo (155ms), 90.2% LongMemEval (162ms) |
| Lock-in risk | Higher (ecosystem-bound) | Lower (portable across stacks) |
The strategic question
Lock-in vs. neutrality
The same logic S&P Global Market Intelligence flagged for hyperscaler primitives applies here: your agents' memory is among the most valuable and sticky data you own. A bundled memory service keeps it inside one cloud's ecosystem. A neutral layer lets you keep one consistent context strategy across Gemini, OpenAI, Anthropic, and Meta — and move between clouds without re-platforming your memory.
When to choose
When to choose Memory Bank, and when to choose Zep
Choose Memory Bank when
You're standardized on Google Cloud and Vertex, use Gemini as your primary model, and the bundled memory meets your needs.
- Standardized on Google Cloud and Vertex
- Gemini is your primary model
- Bundled memory meets your needs
Choose Zep when
You want neutrality across models and clouds, with governed memory at scale.
- Neutrality across models and clouds
- Temporal, provenance-tracked, governed memory (ABAC, retention, audit)
- Regulated workloads with BYOK/BYOC deployment control
- Benchmark-proven retrieval quality at enterprise scale
Get started
Keep your agent memory portable
FAQ
Frequently asked questions
Is Vertex AI Memory Bank enough for enterprise agent memory?
If you're committed to Vertex/GCP and Gemini and need managed memory, it can be. For neutrality, temporal reasoning, provenance, and portable governance, evaluate a dedicated layer like Zep.
Can Zep run on Google Cloud?
Yes — managed, with your own keys, or inside your own VPC on GCP (or AWS/Azure).
Does Zep work with Gemini?
Zep is model-agnostic and works with Gemini as well as OpenAI, Anthropic, and others — so memory isn't tied to one model provider.