Ambience vs Zep
Zep is a hosted context-engineering platform built on a temporal knowledge graph (Graphiti, open source). The strongest temporal model in the category. Facts have valid-time and transaction-time, so the graph encodes what was true and when. We do something different.
Use Zepif your problem is building a chat or voice agent that needs to track evolving truth. Customer attributes that change, statuses that flip, prices that update. Graphiti's bi-temporal model is the right tool for that and we don't try to compete with it.
Use Ambienceif your problem is a team whose AI agents need to share durable context. Decisions, conventions, skills, failure modes, across people and projects, with scopes the security team will recognise and an audit log they'll trust. Different product. The category essay covers why these aren't the same thing.
Where Zep wins
Zep's temporal graph is unusually clever. Edges carry valid-time and transaction-time, so when a fact gets superseded the old version is invalidated rather than overwritten. You can query the state of the world as of any past moment. That matters more than people realise for chat agents tracking changing user attributes, customer statuses, or domain entities.
Their paper (arXiv 2501.13956) reports +18.5% over baseline on LongMemEval with ~90% lower latency. Graphiti as standalone OSS is a real asset. Their Enterprise deployment options (BYOK, BYOM, BYOC-in-your-VPC) are unusually mature for the segment. SOC 2 Type II + HIPAA BAA on Enterprise.
If your central problem is “facts about the world keep changing and the agent needs to know what was true when,” Zep wins clean. We send people there.
Where Ambience wins
Zep's primary unit is the User Graph. The product is brilliant at modelling one user's evolving facts. It is not built around the questions a team running internal agents has to answer.
1. Team-shaped scopes. Zep exposes User Graphs and Threads, with a Group Graph concept in Graphiti. Ambience has personal, team, project, org, sensitive as first-class, with policy-enforced retrieval that never returns context the caller isn't entitled to read.
2. Redaction before storage.Zep's extraction is LLM-driven from raw messages. Whatever you send is what gets ingested. Ambience strips secrets, PII, and tenant-defined patterns server-side before persistence. The unredacted version never exists on disk. For internal team use this is mandatory. For chat-with-user workloads (Zep's home turf) it's less of an issue.
3. Memory-write audit.Zep retains operational logs (1 day on Flex, 30+ days on Enterprise). Those are API logs, not memory-write audit. Ambience writes an append-only row for every read and every write, independent of API logging. Your compliance team can answer “who read this memory” without reconstructing from request traces.
4. Org-wide identity model. Zep deletes a user graph to revoke. Ambience revokes org identity, which cascades to every team and project the user could read. Offboarding is one action with an audit row.
5. Pricing shape.Zep starts at $125/mo (Flex) and scales to Enterprise (custom). Ambience is free for one person running one agent, then $9 per active agent per month for teams. Idle agents don't bill. The adoption flow is product-led: install the CLI, claim your domain, teammates auto-join.
Side-by-side
| Capability | Area | Ambience | Zep |
|---|---|---|---|
| Primary use case | Fit | Team / org context for internal agents | Customer-facing agent memory with temporal facts |
| Mechanism | Architecture | Typed memory store with policy-enforced scopes | Bi-temporal knowledge graph (Graphiti) |
| Scope model | Security | 5 scopes (personal / team / project / org / sensitive) | User Graphs + Threads, optional Group Graph |
| Server-side redaction before storage Zep extracts from raw messages. Pre-processing for PII is the caller's responsibility. | Security | Yes | No |
| Append-only memory-write audit log Zep retains operational/API logs (1d Flex, 30+d Enterprise). Those aren't memory-write audit. | Governance | Yes | No |
| SSO (Google / GitHub / SAML) | Governance | Yes | Enterprise tier |
| Temporal fact tracking (valid-time + transaction-time) Zep wins clean here. Different problem shape. | Memory | No | Yes |
| MCP integration | Memory | Yes | Yes |
| Pricing entry point | Fit | Free for 1 agent / $9 per active agent | $125/mo (Flex) |
Last verified against Zep concepts and pricing pages, May 2026 — source. If anything is wrong, email hello@ambience.sh and we'll fix it.
Use this rule
Pick Zepif you're building a customer-facing agent that has to track evolving facts about the user, especially with a temporal-correctness requirement. Their graph model is the best in the category.
Pick Ambienceif you're building internal tooling for a team whose AI agents need to share durable context safely. The buyer is your VP Engineering or CISO. The questions on the table are about scope, redaction, and audit, not temporal correctness.
Some companies will run both. Zep behind their customer-facing agent for evolving user facts. Ambience behind their internal agents for shared team context. Different layers of the stack.
Team context, not single-agent memory.
If you're a team running AI agents at work, install Ambience and find out what you've been losing.
curl -fsSL https://ambience.sh/install.sh | shRead the category essay: Single-agent memory vs team context. Or the full reference for AI agents.