Flowise alternatives
Other ai agent builders platforms include Langflow, Dify, Stack AI, Kore.ai, Botpress, Voiceflow. They share a category, but their workflows, coverage, and terms can differ. These are options to evaluate, not ranked recommendations.
Langflow
Visual development environment for AI applications and agents.
Dify
Open-source platform for building AI apps, agents, and knowledge workflows.
Stack AI
No-code platform for enterprise AI agents and connected workflows.
Kore.ai
Platform for enterprise conversational AI and agent applications.
Botpress
Platform for building AI agents and conversational applications.
Voiceflow
Visual platform for building conversational AI agents.
CustomGPT.ai
Build business AI assistants grounded in provided content.
Pickaxe
No-code platform for building and distributing AI tools and agents.
MindStudio
Build AI agents and automated workflows without writing code.
BuildShip
Visual backend builder for AI workflows and APIs.
VectorShift
Visual and code tools for AI agents and automated workflows.
Agenta
Agenta is the open-source workspace for your agents. Build agents through chat, improve them with feedback, and share them with your whole team — self-hosted or in the cloud.
AICamp
Centralize your team’s AI in one secure workspace. AICamp empowers modern teams to build custom agents, share prompts, and collaborate across top LLMs without the enterprise complexity.
Evaligo
Visual drag-and-drop AI workflow builder with built-in A/B testing. Run a flow on several AI models, score every output with blind AI judges, train a per-input model router on the results, and deploy any flow as an API. Free plan, no credit.
Hexabot
Self-hostable AI workflow automation. Build AI agents and workflows that talk, act, and remember across channels, with MCP tools, memory, and data control.
Tiny-Llm-Benchmark
A cost-effective LLM prompt benchmarking tool that helps AI agent builders choose model for optimal cost, performance and accuracy.
AgentScope
Build and run agents you can see, understand and trust.
Inferable
Build reliable AI Workflows and Agents with humans in the loop, structured outputs and durable execution.
How should you evaluate a switch?
Compose AI assistants and workflows with visual or low-code builders. Start with a real task and compare the output, effort, permissions, and full cost. Validate connector permissions, execution limits, export options, and model costs. Include migration work, access, and cancellation terms in the evaluation. A shared category does not make two products direct substitutes.
