CrewAI has built-in memory for multi-agent crews. pref0 provides preference learning that works with any framework. Both help agents retain context, but they differ in scope and flexibility.
| pref0 | CrewAI Memory | |
|---|---|---|
| What it stores | Structured preferences with confidence scores | Short-term, long-term, entity, and contextual memory |
| Scope | Cross-session preference learning | Within-crew and cross-execution memory |
| Confidence scoring | Built-in, compounds over time | Not available |
| Framework | Framework-agnostic REST API | CrewAI-specific (Python only) |
| Storage | Hosted — no infrastructure | Local ChromaDB and SQLite |
| Best for | Learning user preferences across any agent | Sharing context within a CrewAI crew |
pref0 works with any agent framework via REST API — CrewAI, LangChain, Vercel AI SDK, or custom agents. CrewAI Memory only works within CrewAI crews. If you switch frameworks, CrewAI memories don't come with you.
pref0 extracts structured preferences with confidence scores from conversations. CrewAI Memory stores raw interactions, task results, and entity references. CrewAI's memory helps crews collaborate; pref0 helps agents personalize to individual users.
pref0 is a hosted API — no databases to manage. CrewAI Memory uses local ChromaDB and SQLite, which works for development but requires infrastructure planning for production.
Yes. Enable CrewAI Memory for crew collaboration, and use pref0 for per-user preference learning. Inject pref0 preferences into your agent's system prompt or backstory.
Not specifically. CrewAI Memory tracks interactions, task results, and entities within a crew. It doesn't extract structured preferences with confidence scores from user conversations.
pref0 is a hosted API designed for production use. CrewAI Memory uses local SQLite and ChromaDB, which works for development but requires additional infrastructure planning for production deployments.
Your users are already teaching your agent what they want. pref0 makes sure the lesson sticks.