Flowise Memory vs Lindy AI Memory
Flowise Memory vs Lindy AI Memory: side-by-side comparison of two framework-embedded memory systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| Flowise Memory | Lindy AI Memory | |
|---|---|---|
| Capability band | competent | competent |
| Capability composite | 55 | 55 |
| Cost tier | mid | premium |
| Use cases | Memory Augmented Chat, Scoped Agentic | Long Running Session, Memory Augmented Chat, Scoped Agentic |
Where they differ (14)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Flowise Memory | Lindy AI Memory | |
|---|---|---|
| Cost tier | mid | premium |
| Use cases | Memory Augmented Chat, Scoped Agentic | Long Running Session, Memory Augmented Chat, Scoped Agentic |
| Type | Buffer + Buffer-Window + Conversation-Summary nodes | Selective KV memory injected into prompt |
| Created | 2023 (Flowise launched 2023; YC S23) | 2023-01 (Lindy AI founded and launched January 2023 by Flo Crivello; YC W23) |
| Pricing | discontinued — product sunset (EOL 2026-08-31); OSS code remains forkable under Apache-2.0 | Free: $50 in credits for 7 days, no card; Team $29.99/user/mo (3,000 credits, extra $10 per 1,000); Enterprise custom |
| Funding | total $500K (Seed, YC, 2023-01); acquired by Workday (announced 2025-08-14, terms undisclosed) | $49.9M total; Series B $35M Jan 2023; Battery Ventures key investor; YC W23 |
| Backend storage | pluggable | searched not found |
| Deployment | Both (OSS self-hosted; Flowise Cloud managed; air-gapped deployment supported) | Managed cloud only (SaaS) |
| API surface | REST, SDK: JS/TS | searched not found |
| Embedding | multiple supported | searched not found |
| Multi-tenancy | namespace | searched not found |
| MCP | via official adapter — Flowise MCP node | yes — MCP client: connects to hosted streamable-HTTP MCP servers and builds actions from their tools |
| Optimised for | visual LangChain canvas + memory nodes | selective high-signal memory injection |
| Anti-fit | not for production-grade SLA workloads | not for code-first developers |
At a glance
| Flowise Memory | Lindy AI Memory | |
|---|---|---|
| Section | Framework-embedded memory | Framework-embedded memory |
| Tier | T1 | T1 |
| Type | Buffer + Buffer-Window + Conversation-Summary nodes ↗ vendor | Selective KV memory injected into prompt ↗ vendor |
| Created | 2023 (Flowise launched 2023; YC S23) ↗ third-party | 2023-01 (Lindy AI founded and launched January 2023 by Flo Crivello; YC W23) ↗ third-party |
| Latest release | flowise@3.1.4 (2026-07-29) — final ↗ repo | — |
| License | Apache-2.0 ↗ repo | — |
| GitHub | FlowiseAI/Flowise — ~55.4k stars, archived 2026-08-13 (sunset plan had targeted 2026-08-10) ↗ repo | — |
| Pricing | discontinued — product sunset (EOL 2026-08-31); OSS code remains forkable under Apache-2.0 ↗ vendor | Free: $50 in credits for 7 days, no card; Team $29.99/user/mo (3,000 credits, extra $10 per 1,000); Enterprise custom ↗ vendor |
| Funding | total $500K (Seed, YC, 2023-01); acquired by Workday (announced 2025-08-14, terms undisclosed) ↗ third-party | $49.9M total; Series B $35M Jan 2023; Battery Ventures key investor; YC W23 ↗ third-party |
| Backend storage | pluggable ↗ vendor | searched not found |
| Deployment | Both (OSS self-hosted; Flowise Cloud managed; air-gapped deployment supported) ↗ third-party | Managed cloud only (SaaS) ↗ vendor |
| API surface | REST, SDK: JS/TS ↗ vendor | searched not found |
| Embedding | multiple supported ↗ vendor | searched not found |
| Multi-tenancy | namespace ↗ vendor | searched not found |
| MCP | via official adapter — Flowise MCP node ↗ vendor | yes — MCP client: connects to hosted streamable-HTTP MCP servers and builds actions from their tools ↗ vendor |
| A2A | searched not found | searched not found |
| OpenTelemetry | searched not found | searched not found |
| Optimised for | visual LangChain canvas + memory nodes ↗ vendor | selective high-signal memory injection ↗ vendor |
| Anti-fit | not for production-grade SLA workloads ↗ vendor | not for code-first developers ↗ vendor |
Taxonomy
| Axis | Flowise Memory | Lindy AI Memory |
|---|---|---|
| storage | vector | kv |
| retrieval | similarity | injection |
| persistence | session | cross-session |
| update | append-only | extraction |
| unit | episode | fact |
| governance | inspectable | user-controllable |
| conflict | append-only | llm-arbitrate |
Pros & cons
Flowise Memory
Pros: Visual builder lowers the bar for non-engineers to design memory pipelines; LangChain-compatible nodes.
Cons: Memory is as good as the LangChain primitive underneath — no novel architecture; less appealing to engineers building from code.
Lindy AI Memory
Pros: Lifelong-agent positioning — memory isn't a feature but the product premise; most opinionated about memory of any framework.
Cons: Closed ecosystem; lock-in risk is highest of the framework-embedded options.