Voiceflow Memory
https://docs.voiceflow.com/docs/memory
Chatbot platform. Tracks last 25 turns (configurable up to 100) as labelled assistant/user transcript stored in vf_memory string variable. Optional indefinite chat persistence across browser sessions.
At a glance
- Type
- Sliding-window buffer (vf_memory)
- Tier
- T1
- Section
- Framework-embedded memory
- Created
- 2018-2019 (Storyflow project 2018; Voiceflow formally launched 2019)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- Free + paid
- Funding
- $39.8M total; Series B ~$20M 2021; Series A $15M Aug 2023 led by OpenView VP
Taxonomy
- storage
- kv
- retrieval
- injection
- persistence
- session
- update
- overwrite
- unit
- fact
- governance
- user-controllable
- conflict
- last-write-wins
When to use
Optimised for: low-code chatbot designer + sliding-window buffer
Anti-fit: not for code-first developers
Pros & cons
Pros
Built specifically for voice agents — memory model accommodates dialogue flow control and slot-filling, which generic memory layers don't.
Cons
Voice-agent-tied; not useful for non-voice agentic apps.
Claims & capabilities
Free 100 credits/mo; Pro $60/mo (10k credits); Business $150/mo/editor.
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- Managed-only
- Embedding model
- searched not found
- Multi-tenancy
- searched not found
- MCP
- searched not found
- A2A
- searched not found
- OpenTelemetry
- searched not found
Similar systems
Other framework-embedded memory in the catalog, ranked by inbound references.
- LangGraph Persistence T2
Distinct from LangMem. Built-in checkpointer saves graph state per super-step (short-term, thread-scoped). Store System adds long-term hierarchical key-value memory across threads with optional vector search + TTL. Postgres / Mongo / Redis stores for production.
- AutoGen Memory T2
ListMemory chronological context + teachable agents that vectorise corrections. Integrates with Mem0/Zep rather than building deep memory natively.
- CrewAI Memory T2
Memory subsystem inside the CrewAI orchestration framework; integrates with Mem0 for the long-term tier.
- AGiXT Adaptive Memory T2
Open-source AI automation platform. Routes between short-term and long-term memory adaptively across any LLM provider; plugin system for storage backends. Memory managed at the instruction-management layer — task context, instruction state, conversation history as unified agent state.
- Agno (Phidata) Memory T2
Agno (formerly Phidata). AgentStorage persists sessions to a DB; AgentMemory auto-classifies/store user preferences and conversation summaries. Single-line integrations with LanceDB, Pinecone, Weaviate, Qdrant.
- Botpress LLMz T1
Per-plan vector-DB storage quota + LLMz autonomous engine (in-session working memory) + Knowledge Base (semantic search over uploaded docs). Long-term user memory persists across sessions.