Why teams compare Zep and AI Memory
Zep and AI Memory both reject the idea that a longer prompt is a memory strategy. They differ in how much of the platform you have to adopt.
Zep’s center of gravity is the temporal knowledge graph: facts with validity windows, entity relationships and a context API built around that model. AI Memory also stores an entity graph, but the public contract starts with five operations: add, search, update, delete and export.
That makes the comparison less about “who has a graph” and more about how much graph machinery your application actually needs.
Zep and AI Memory at a glance
The table uses the public plan pages on October 19, 2026. Zep’s self-serve plans are credit-based; AI Memory’s plans are described around stored memories. Do not compare the headline numbers without comparing the units.
| Dimension | Zep (published) | AI Memory (published) |
|---|---|---|
| Entry self-serve plan | Flex at $125/month with 50,000 credits | Pro at $19/month with 50,000 stored memories |
| Higher self-serve plan | Flex Plus at $375/month with 200,000 credits | Scale at $99/month with 500,000 stored memories |
| Core model | Temporal knowledge graph and context API | Graph retrieval with extraction, merge and compression |
| Free tier | Prototyping with 10,000 credits per month | Browser console on a seeded store; paid plans for production |
| Deployment | Cloud, VPC and on-prem options | Managed service and a self-hosted path |
| Portability | Platform export and API access | Full graph export as JSON |
| Best fit | Teams whose core problem is temporal graph reasoning | Teams that want a smaller memory layer beside an existing stack |
Sources: https://www.getzep.com/pricing/ and https://ai-memory.lol/pricing, checked October 19, 2026.
Temporal reasoning is a real requirement, not a buzzword
Some questions are fundamentally about time: what did we believe last quarter, which contract was active when the invoice was issued, and which fact replaced the earlier one? A temporal graph is the right tool for that class of problem.
AI Memory keeps timestamps and versions, resolves contradictions to the newest truth, and preserves an audit trail. It is designed for the common case: an agent needs the current truth about a user, an account or a project, with enough provenance to explain where it came from.
If your product is a temporal reasoning engine, Zep may be the better fit. If your product is a support bot, a sales assistant or a coding agent that needs durable context without building a graph platform, a simpler memory layer is often enough.
What to move and what to leave behind
- Export episodes and facts with their timestamps. Do not flatten time into a single “last updated” column.
- Map Zep users and threads to AI Memory user, agent and session scopes. Keep the tenant id explicit.
- Re-run a sample of real questions against both systems. Compare the top five memories, not only the top one.
- Keep a read-only copy of the old graph for one retention window while you audit disputed answers.
- Do not migrate derived summaries as if they were facts. Re-extract from the source events when you can.
When Zep may be the better choice
Zep has a mature temporal graph model, a strong technical writing team and deployment options that include VPC and on-prem. If you need a graph platform with a long history of temporal reasoning work, it deserves a serious evaluation.
Zep may also be the better choice if you are already standardized on its context API or if your team wants a vendor to own more of the graph infrastructure.
AI Memory is the better fit when you want a narrower contract, a lower entry price and a graph you can export without turning the migration into a project.
A practical evaluation checklist
- Write down the three questions your agent must answer correctly. Test both systems on those questions, not on a generic benchmark.
- Measure tokens per turn, not only retrieval latency.
- Check how each system handles a fact that changes twice in one week.
- Check how each system deletes one user without affecting the tenant.
- Ask what the export contains: facts only, or facts plus source, scope and version history?
Frequently asked questions
Is AI Memory a temporal knowledge graph?
AI Memory stores entities and relationships alongside vectors, and it keeps timestamps and versions for every memory. It is not positioned as a full temporal graph platform; it is a memory layer for agents and apps.
Why is AI Memory cheaper than Zep?
The pricing units differ. Zep’s self-serve plans are credit-based; AI Memory’s published plans are described around stored memories. Compare the unit your workload actually consumes.
Can I migrate from Zep?
Yes, with planning. Export episodes and facts with timestamps, map users and threads to scopes, and compare search results on a sample of real queries before cutting over reads.
Does AI Memory support VPC or on-prem deployment?
AI Memory publishes a self-hosted path for the same API. Confirm the current deployment options and plan requirements with support before you commit.
Which system handles contradictions better?
Both products claim to handle superseded facts. The honest answer depends on your data. Test a fact that changes twice in one week and inspect what each system returns, including its source and timestamp.
Do I need a graph at all?
Not always. If your questions are simple lookups by user id, a table plus a vector index may be enough. A memory layer earns its place when you need extraction, merging, scoped retrieval and contradiction handling.