Unfairly vs Letta
TL;DR
Letta is publicly positioned around stateful agents that maintain memory and context across conversations. Unfairly is multiplayer context for teams: shared, trust-tiered company knowledge that multiple agents and tools can use. If you want to build stateful agents, Letta may be the right call. If you want team context every agent can share, compare Unfairly.
What is the short answer?
Unfairly is the multiplayer context layer for AI agents.
Letta is about stateful agents. Unfairly is about shared team context.
That distinction sounds small until a team has ten agents, five tools, three people editing instructions, and no idea which context is true. Then it becomes the whole game.
When is Letta the right call?
Letta may be the right call when you want to create agents with persistent state, memory blocks, and behavior that survives across conversations.
That is agent architecture. It is valuable when the agent itself is the product or the primary interface.
When is Unfairly the right call?
Unfairly is the right call when agent memory is not enough because the team needs a shared context layer.
One agent remembering is single-player. The team compounding context across agents is multiplayer.
Read CLAUDE.md for teams for local agent instructions, then read multiplayer context for the shared layer those instructions should point to.
| Dimension | Unfairly | Letta |
|---|---|---|
| Team / multiplayer context | Built for shared organizational context across humans, AI agents, and tools. | Letta's docs describe stateful agents that maintain memory and context across conversations. |
| Trust tiers | Trust tiers are explicit so agents know whether they are reading raw evidence or verified canon. | Letta documents persistent agent state and memory; evaluate team-level trust-tier needs against its current platform. |
| MCP + model-agnostic access | Designed as model-agnostic context available across agent surfaces through MCP-style access. | Letta focuses on building and running stateful agents, with public docs around agents, memory blocks, and the Letta API. |
| Personal memory vs shared context | Starts from shared team context and company canon. | Starts from agents with persistent state, memory, and behavior. |
| Pricing model | Closed beta; join the waitlist for access. | Letta publishes personal and API pricing in its docs; confirm current plan details before buying. |
Source checked for Letta: https://docs.letta.com/guides/core-concepts/stateful-agents/
FAQ
Is Letta a memory tool or an agent platform?
Letta's public docs position it around stateful agents, persistent memory, APIs, and agent development workflows.
When is Letta the right call?
Letta may be the right call when you want to build stateful agents with persistent memory and agent-specific behavior.
When is Unfairly the right call?
Unfairly is the better fit when the context problem is shared across the team and needs to be available to many agents and tools.