Hindsight (Vectorize) vs Zep & Graphiti
Hindsight (Vectorize) vs Zep & Graphiti: side-by-side comparison of two dedicated memory layers systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| Hindsight (Vectorize) | Zep & Graphiti | |
|---|---|---|
| Capability band | competent | competent |
| Capability composite | 68 | 68 |
| Cost tier | free | free |
| $/Mtok input | 0 | 0 |
| $/Mtok output | 0 | 0 |
| Use cases | Long Running Session, Memory Augmented Chat, Offline Capable | Long Running Session, Memory Augmented Chat, Multi Agent Coordination, Analytical Summarization |
Where they differ (15)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Hindsight (Vectorize) | Zep & Graphiti | |
|---|---|---|
| Use cases | Long Running Session, Memory Augmented Chat, Offline Capable | Long Running Session, Memory Augmented Chat, Multi Agent Coordination, Analytical Summarization |
| Type | Vector + reflection / summarisation | Bi-temporal knowledge graph |
| Created | 2025-10 | 2024-08 |
| Latest release | v1.1.0 (2026-10-21) | v0.30.0 (2026-09-01) (graphiti-core; MCP server mcp-v1.1.0 same day) |
| License | MIT | Apache-2.0 |
| GitHub | vectorize-io/hindsight — ~44.6k stars, last commit 2026-10 | getzep/graphiti — ~32k stars, last commit 2026-09 |
| Pricing | OSS self-host free (MIT); Hindsight Cloud pay-as-you-go credits ($5 free credit on GitHub sign-up); Enterprise single-tenant custom | Free 10k credits/mo; Flex $125/mo ($104 annual) 50k credits; Flex Plus $375/mo ($312 annual) 200k credits; Enterprise custom |
| Funding | total $3.6M (Seed led by True Ventures, 2024-04) | $3M total Seed (additional) · 2024-04 |
| Backend storage | custom | Postgres + Neo4j (Graphiti) |
| Deployment | Both — managed Hindsight Cloud; Enterprise single-tenant (Vectorize cloud, customer AWS/GCP/Azure, or on-prem); self-host via Docker, Helm or pip (Postgres + pgvector) | Both — Zep Cloud managed; Graphiti OSS self-hosted (Neo4j/FalkorDB) |
| API surface | REST, SDK: Python, TS | REST, SDK: Python, JS/TS, Go |
| Multi-tenancy | namespace | Logical namespace per user/session; AWS VPC self-hosted option for full data residency; HIPAA BAA on Enterprise plan |
| MCP | native (first-party) — Hindsight MCP | native (first-party) — Graphiti MCP server |
| Optimised for | retrieval engineering + reflection / summarisation as service | memory operation tracing + drift / poisoning detection |
| Anti-fit | searched not found | not for use cases that don't run agent workloads in production |
At a glance
| Hindsight (Vectorize) | Zep & Graphiti | |
|---|---|---|
| Section | Dedicated memory layers | Dedicated memory layers |
| Tier | T1 | T1 |
| Type | Vector + reflection / summarisation | Bi-temporal knowledge graph |
| Created | 2025-10 | 2024-08 |
| Latest release | v1.1.0 (2026-10-21) | v0.30.0 (2026-09-01) (graphiti-core; MCP server mcp-v1.1.0 same day) |
| License | MIT | Apache-2.0 |
| GitHub | vectorize-io/hindsight — ~44.6k stars, last commit 2026-10 | getzep/graphiti — ~32k stars, last commit 2026-09 |
| Pricing | OSS self-host free (MIT); Hindsight Cloud pay-as-you-go credits ($5 free credit on GitHub sign-up); Enterprise single-tenant custom | Free 10k credits/mo; Flex $125/mo ($104 annual) 50k credits; Flex Plus $375/mo ($312 annual) 200k credits; Enterprise custom |
| Funding | total $3.6M (Seed led by True Ventures, 2024-04) | $3M total Seed (additional) · 2024-04 |
| Backend storage | custom | Postgres + Neo4j (Graphiti) |
| Deployment | Both — managed Hindsight Cloud; Enterprise single-tenant (Vectorize cloud, customer AWS/GCP/Azure, or on-prem); self-host via Docker, Helm or pip (Postgres + pgvector) | Both — Zep Cloud managed; Graphiti OSS self-hosted (Neo4j/FalkorDB) |
| API surface | REST, SDK: Python, TS | REST, SDK: Python, JS/TS, Go |
| Embedding | multiple supported | multiple supported |
| Multi-tenancy | namespace | Logical namespace per user/session; AWS VPC self-hosted option for full data residency; HIPAA BAA on Enterprise plan |
| MCP | native (first-party) — Hindsight MCP | native (first-party) — Graphiti MCP server |
| A2A | not documented publicly | not documented publicly |
| OpenTelemetry | not documented publicly | not documented publicly |
| Optimised for | retrieval engineering + reflection / summarisation as service | memory operation tracing + drift / poisoning detection |
| Anti-fit | searched not found | not for use cases that don't run agent workloads in production |
Taxonomy
| Axis | Hindsight (Vectorize) | Zep & Graphiti |
|---|---|---|
| storage | vector | graph |
| retrieval | similarity | graph-traversal |
| persistence | long-term | long-term |
| update | consolidation | append-only |
| unit | episode | episode |
| governance | opaque | auditable |
| conflict | none | bi-temporal |
Pros & cons
Hindsight (Vectorize)
Pros: Built on Vectorize's RAG pipeline expertise — retrieval tuning is a first-class concern; strong Pydantic-AI integration story.
Cons: Newer entrant with smaller adoption; positioning straddles RAG and memory which can muddy the value prop vs pure-play layers.
Zep & Graphiti
Pros: Bi-temporal graph captures event time + ingestion time, making contradiction tracking and chronological reasoning correct by construction.
Cons: KG storage is heavier than vector for the same data volume; smaller funding base than Mem0 ($2.3M vs $24M).