Unfairly vs Zep
TL;DR
Zep is publicly positioned as enterprise-grade memory for AI agents, including context graphs and production memory infrastructure. Unfairly is positioned as multiplayer context for teams: shared, trust-tiered company knowledge exposed across agent tools. If your product needs production agent memory infrastructure, Zep may be right. If your team needs shared operational context, compare Unfairly.
What is the short answer?
Unfairly is the multiplayer context layer for AI agents.
Zep is a serious agent-memory infrastructure product. Unfairly is a team-context product.
Those can look adjacent because both talk about context. The buyer problem is different. Zep asks how production agents remember. Unfairly asks how a team stops re-teaching every agent the same company truth.
When is Zep the right call?
Zep may be the right call when your application needs production-grade agent memory, context graphs, and infrastructure for serving memory at scale.
If the problem sits inside the product architecture of an agentic app, Zep belongs on the shortlist.
When is Unfairly the right call?
Unfairly is the right call when the problem sits inside the team.
The symptoms are not latency benchmarks. They are duplicated prompts, stale decisions, private notes, and agents that do not know what the rest of the organization already learned.
Read How to share context across AI agents and MCP server for team knowledge for the practical setup.
| Dimension | Unfairly | Zep |
|---|---|---|
| Team / multiplayer context | Built around shared company context for teams using multiple AI agents and tools. | Zep describes itself as the Context Lake for AI agents and focuses on managing, governing, and serving agent memory at enterprise scale. |
| Trust tiers | Trust tiers are the core UX and retrieval model for separating evidence from canon. | Zep publicly emphasizes governance and enterprise-grade agent memory; evaluate exact trust workflow requirements in its docs. |
| MCP + model-agnostic access | Designed for model-agnostic context access across agent tools through MCP-style workflows. | Zep is agent-memory infrastructure, with public positioning around context graphs and production memory. |
| Personal memory vs shared context | Starts from shared team knowledge: decisions, positioning, workflows, and internal links. | Starts from agent memory across users, business data, and the world the agent operates in. |
| Pricing model | Closed beta; join the waitlist for access. | Zep publishes credit-based and enterprise pricing information; confirm current plan details with Zep. |
Source checked for Zep: https://www.getzep.com/ai-agents/
FAQ
Is Zep the same category as Unfairly?
It overlaps in context and memory, but Zep's public positioning is production agent memory infrastructure while Unfairly's is shared team context for agents.
When is Zep the right call?
Zep may be the right call when you are building production agents that need dedicated memory infrastructure and context graph behavior.
When is Unfairly the right call?
Unfairly is the right call when the main bottleneck is your team's shared, trusted operational context across tools.