Relevance AI vs Flowise
A detailed comparison to help you choose between Relevance AI and Flowise.
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Verdict: Flowise wins
Flowise scores 4.0/5, edging out Relevance AI at 3.8/5. Developers and technical teams who want visual control over LLM pipelines and are happy to self-host or manage their own production runtime.
Relevance AI Build and deploy AI agents without coding | Flowise Visual LLM app builder with drag and drop | |
|---|---|---|
| Rating | 3.8 (1 review) | 4.0 (1 review) |
| Pricing Model | freemium | freemium |
| Starting Price | Free tier available | Free tier available |
| Best For | Ops, sales, and support teams who want to deploy specialist AI agents and multi-agent processes without writing code or hiring engineers. | Developers and technical teams who want visual control over LLM pipelines and are happy to self-host or manage their own production runtime. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | no codeteam features | open sourceno code |
| Visit Relevance AI → | Visit Flowise → |
Relevance AI
Pros
- + Describe-to-build agent creation got me a working multi-step agent in an afternoon without code
- + Execution logs show exactly which tool runs burned Actions, which made cost pruning straightforward
- + Workforce layer (multi-agent processes with scheduling) produced more dependable output than any single agent
- + Free tier with 200 Actions/month is enough for a real pilot, not just a demo
- + 2,000+ integrations with premium connectors (LinkedIn, WhatsApp) on Team+
Cons
- - Dual billing — bundled Actions plus passed-through vendor credits — means plan price is never your total cost
- - Free plan keeps only 7 days of task history, which is useless for debugging a week-old misbehaviour
- - Complex branching and retry semantics are harder to express here than in code-based frameworks
- - Knowledge storage on entry tiers (10-100 MB) is too small for real document corpora
- - The vendor domain still serves conflicting legacy pricing ladders, which makes verification noisy
Flowise
Pros
- + Node canvas gives LangChain-level control over retrieval, agents, and tools without writing code — my retrieval agent took one sitting
- + Self-host path is real: npm or Docker, minutes to localhost:3000, Apache 2.0 core license
- + Human-in-the-loop review nodes make the agents-propose-humans-release pattern easy to wire
- + Wide model and vector-store support (100+ LLMs, embeddings, vector DBs per the vendor) keeps you off proprietary lock-in
- + Evaluations, metrics, and run observability are built into the builder rather than bolted on
Cons
- - Node picker presumes you understand embeddings, chains, and retrieval strategies — beginners are lost quickly
- - Production self-host means doing your own persistence, secrets, queue/workers, and uptime — time not visible in the free price
- - Enterprise identity and permission features live under a commercial license inside the same repo
- - Cloud free tier (100 predictions/month) is too small to judge real performance
- - Fast-moving node surface and uneven community templates mean upgrades can break flows
Frequently Asked Questions
Which is better, Relevance AI or Flowise?▼
Flowise scores higher at 4.0/5 vs 3.8/5 for Relevance AI, making it the better-rated option in our comparison.
What is the difference between Relevance AI and Flowise?▼
Relevance AI: Relevance AI is a no-code platform for building specialist AI agents for sales, marketing, support and HR, and running them at scale. Flowise: Flowise is an open-source visual builder for LLM applications and agents, wiring models, tools and data sources together on a canvas.
Is Relevance AI or Flowise more affordable?▼
Relevance AI starts at €0/mo, Flowise starts at €0/mo. Check the comparison table above for current pricing.
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