Graphiti

type: KnowledgeGraph

notes: Temporal knowledge graph for AI agents. Core component of Genesis FalkorDB/Graphiti tier. Builds dynamic, evolving knowledge graphs from unstructured/structured data with time-aware retrieval.


grov.dev

type: EpisodicMemory

notes: Cross-session memory system for AI agents. Discovered this week (2026-02-17) and immediately improved Genesis memory architecture. Provides persistent episodic memory across agent sessions. Open-source, Python-native.


LangMem

notes: LangChain's memory system. Provides long-term memory for LangChain agents. Supports semantic, episodic, and procedural memory types. Tightly coupled to LangChain ecosystem — lower priority for Genesis which uses custom stack.


Zep

notes: Conversation memory service for AI assistants. Stores and retrieves conversation history with semantic search. Also the creator of Graphiti. SaaS + open-source. Zep Cloud is managed, self-hosted available. Consider for session-level memory tier.


MemGPT / Letta

notes: Memory-augmented LLM framework. Originally MemGPT, rebranded to Letta. Provides virtual context management — agents manage their own memory hierarchy (in-context, archival, recall). OS-level abstraction for LLM memory. Strong episodic + archival memory model. Python-first, actively maintained.


Cognee

notes: Knowledge graph memory for AI. Builds knowledge graphs from documents and conversations. Integrates with multiple vector stores and graph databases. Python SDK available. Graph-native approach aligns well with Genesis FalkorDB tier. Evaluate for potential integration.


notes: The memory layer for AI. Provides persistent, adaptive memory for AI agents and assistants. Supports multiple storage backends (PostgreSQL, Qdrant, etc.). Has both open-source and cloud (mem0.ai) versions. Python SDK. Strong community (40k+ GitHub stars). Overlaps with Genesis memory stack but could complement it.


LanceDB

type: VectorStore

notes: Serverless vector database built on Lance columnar format. Used in OpenClaw project. Embedded, no server required. Good for local/edge deployments. Lower Genesis relevance since Qdrant already covers the vector store tier, but worth knowing for lightweight deployments.


Chroma

notes: Open-source embedding database. One of the most popular vector stores. Simple Python API. Genesis uses Qdrant for the vector tier — Chroma is a known alternative but lower priority. Relevant as competitive benchmark.


Weaviate

notes: Vector database with graph-like capabilities. Combines vector search with structured data properties. Has a knowledge graph module. More heavyweight than Qdrant. Genesis relevance: moderate — Qdrant covers vectors, FalkorDB covers graphs. Weaviate sits in between but adds complexity.