Agent Runtime
LangChain·LlamaIndex·CrewAI·Google ADK·custom
Any agent framework — or none. The Context Lake is invoked through a single SDK.
The data-lake pattern, applied to agent memory. Across every user, every domain, every agent, at scale.
Memory for a single agent is a solved problem. Memory across every agent, every user, every business unit is a different problem. Scale, isolation, governance, and retrieval performance all break at the same time.
The Context Lake is the layer that solves them together. One system of record for context across the enterprise, governed at the entity level, served in milliseconds.
Millions of context graphs, one per user, customer, team, or topic. Each captures the chat, documents, events, and business data tied to that subject — and the relationships between them — structured temporally and served back to agents on demand.
Any agent framework — or none. The Context Lake is invoked through a single SDK.
Raw signal arrives from any source the agent touches.
Relevant context is assembled on demand into token-efficient blocks.
Signal becomes a temporal context graph as new facts arrive and stale ones are invalidated.
Selects what's relevant and what adds the most information within the token budget.
Native to the substrate, not a layer bolted on. Every read and write is policy-gated for access and provenance; retention runs across the data lifecycle.
Temporal context graph with provenance — sub-200ms retrieval at scale.
The Context Graph Engine is Zep’s proprietary runtime — millions of governed graphs, served in milliseconds, with isolation and temporality native to the data model.
The Context Lake runs alongside your data lake, not as a replacement. Different data, different consumers, different access patterns. Same governance rigor.
Tables, transactions, logs, metrics.
Conversations, documents, events, decisions.
Optimized for aggregation and retrospective analysis.
Temporal context graphs with entity-aware retrieval.
Batch jobs, scheduled pipelines, dashboard refresh.
Real-time context at agent inference speed.
BI tools, data scientists, reporting pipelines.
LLM-powered applications that need memory and context.
Table-level permissions, role-based access.
Attribute-based policies, retention rules, full audit trail.
We can easily see Zep becoming a de facto partner in this layer of the enterprise agent stack.
Govern context across thousands of agents, users, and context sources.
Control what context agents can access and what they can do with it.
Retention is policy-driven. Data expires on the schedule you set. Legal hold blocks deletion when compliance requires it.
Detailed logs of every request and policy decision, ready for audit.
The trust boundary moves with your deployment. Choose where compute, data, and keys live. Learn more.
Zep's managed service. No infrastructure to run. Start in minutes.
Zep's managed service with your own encryption keys. You control the keys; data at rest is encrypted with them.
Zep deployed inside your VPC. Your network, your perimeter, your compliance boundary.