The decision
Should you choose Zep?
Zep earns a shortlist for teams that need durable, time-aware agent context and can validate memory as a governed data system. Start with synthetic identities, define correction and deletion service levels, and forecast credits from real episode sizes.
Best for
Agents needing cross-session memory; Teams modeling changing relationships.
Choose something else if
High-stakes memory without correction workflows; Teams unable to govern behavioral data
Evidence
Editorial research pending · 8.0/10
Pricing checked
From $125 · 2026-09-01
Free access is available, with limits.
Yes. Prototype includes 10,000 monthly credits, two projects, one Memory MCP seat, and variable service limits.
In this guide
Short answer
Zep is worth testing when an agent must remember changing people, organizations, preferences, and events across sessions. Its temporal graph is more purposeful than stuffing every old message into a vector store. The decision hinges on whether extracted relationships stay accurate, corrections supersede old facts, and deletion reaches every derived memory.
Best for
- Agents needing cross-session memory
- Teams modeling changing relationships
- Enterprises comparing cloud and private deployment
Look elsewhere if
- High-stakes memory without correction workflows
- Teams unable to govern behavioral data
- Simple short-history chat
What Zep verifiably does
Official materials describe Graphiti-powered temporal context graphs, episodic ingestion, entity and relationship extraction, hybrid retrieval, custom entity types, Memory MCP, observations, webhooks, analytics, cloud, customer-key encryption, and bring-your-own-cloud deployment.
Important limitations
Extraction can merge identities, invent relationships, or preserve obsolete facts. Larger episodes consume more credits. Memory contains sensitive behavioral history, so retention, deletion, access separation, model subprocessors, and backup behavior require review.
Pricing snapshot
Zep includes 10,000 monthly prototype credits. Flex is $125 per month with 50,000 credits, and Flex Plus is $375 with 200,000. Extra credits, rate limits, projects, logs, Memory MCP seats, and features vary. Episode size determines ingestion credits; Enterprise is negotiated. Reviewed September 1, 2026.
A fair buyer test
Create 100 synthetic users with changing employers, preferences, aliases, contradictions, deletions, and access boundaries. Measure extraction precision, temporal ordering, corrections, forbidden cross-user retrieval, deletion, ingestion latency, retrieval usefulness, credits per accepted memory, and correction effort.
Final verdict
Zep earns a shortlist for teams that need durable, time-aware agent context and can validate memory as a governed data system. Start with synthetic identities, define correction and deletion service levels, and forecast credits from real episode sizes.
This is a research-based assessment, not a claim of hands-on product testing. Product, pricing, privacy, security, licensing, and usage claims were checked against the first-party sources below on September 1, 2026. Verify current terms and run the proposed test with approved data before adoption.
Transparency
How this guide was checked
Editorial accountability
Who checked this guide
- Evaluation type
- Hands-on evaluation
- Last materially checked
- Evidence
- 4 listed sources
Hands-on testing is identified explicitly. Research-based coverage uses cited product documentation and other named sources; it does not imply every paid plan was used. Read the full methodology.
Editorial freshness
Pricing and material product claims were checked September 1, 2026.
Review evidence
What this guidance is based on
- Editorial basis
- Current first-party product, pricing, documentation, privacy, security, and license material
- Review type
- Research-based product assessment
- Material review date
- September 1, 2026
- Buyer test
- Controlled workflow test with evidence, correction, cost, permission, privacy, and ownership checks
Important limits
- • DiscoverAI did not complete the proposed long-term paid deployment for this research-based review.
- • Features, prices, limits, security controls, privacy terms, licensing, and provider data paths can change; verify the linked first-party pages before purchase.
Standardized benchmark coverage
How this review maps to the research benchmark
Citation accuracy
Not applicableThe reviewed workflow does not produce source-grounded research answers, so a citation score would be misleading.
Read protocol v2026.10-v1 →Thematic analysis
Not applicableThe reviewed workflow is not qualitative evidence analysis, so a thematic-analysis score would be misleading.
Read protocol v2026.10-v1 →Eligibility is not a product score. DiscoverAI publishes results only after output collection, blinded adjudication, reproducibility checks, and severe-error review.
Open the optional evaluation worksheet
Reusable trial worksheet
Test Zep before you commit
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Agents needing cross-session memory; Teams modeling changing relationships; Enterprises comparing cloud and private deployment
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Create 100 synthetic users with changing employers, preferences, aliases, contradictions, deletions, and access boundaries. Measure extraction precision, temporal ordering, corrections, forbidden cross-user retrieval, deletion, ingestion latency, retrieval usefulness, credits per accepted memory, and correction effort.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: Zep includes 10,000 monthly prototype credits. Flex is $125 per month with 50,000 credits, and Flex Plus is $375 with 200,000. Extra credits, rate limits, projects, logs, Memory MCP seats, and features vary. Episode size determines ingestion credits; Enterprise is negotiated. Reviewed September 1, 2026.
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.2/5; AI quality 4.0/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: Python, TypeScript, MCP, LangGraph, OpenAI, Anthropic
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Extraction errors become durable context; Episode credits complicate forecasting; Private deployment is enterprise-led
Loading saved worksheet… · private to this device or your optional account
Community evidence
How verified users put Zep to work
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
No approved community evidence yet. Be the first verified user to contribute.
Community choice
Recommend Zep
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Sources and verification
Product details and claims were checked against the following primary sources.
Frequently asked questions
Is Zep free?
Zep offers a limited prototype plan with 10,000 monthly credits; production self-serve and enterprise plans are paid.
How does Zep pricing work?
Credits are based mainly on Episode size. Test representative payloads because larger Episodes consume multiple credits.
How is Zep different from a vector database?
Zep builds a temporal graph of entities, relationships, and episodes, then combines graph and semantic retrieval.
Can Zep run privately?
Zep advertises bring-your-own-cloud enterprise deployment and customer-managed encryption-key options; verify architecture and contract terms.
Recommended tool
Use Zep if this workflow fits your team
Temporal memory model
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