🤖 AI Agent Workflow Builder No-Code

Build multi-step AI agent workflows visually. The agentic shift — AI that actively performs work. Design, connect, and deploy.

Visual workflow canvas

1. Research agent input: query

Gathers real-time data, web search, or knowledge base.

2. Reasoning agent analysis

Synthesizes, filters, and prepares context.

3. Action / generation agent output

Creates final report, email, or API call.

drag to reorder (demo)

Agent LLM:

GPT-4 Claude 3 Llama 3

Initial prompt / input (seed)

Agent execution trace

Status ⚡ ready

No errors — workflow has 3 agents

steps: 3 simulated time: ~2.4s

⏳ [research agent] searching: "vector databases 2025"... done (5 results)
🧠 [reasoning agent] ranking by relevance & extracting key features...
✍️ [generation agent] writing summary with top 3: Pinecone, Weaviate, Qdrant
✅ workflow finished. output ready.

builder principles

Each agent is a node. Connect them visually to create a pipeline. The agentic shift means AI takes actions — you just design the flow. No coding required.

🤖 What is an AI Agent Workflow?

An AI agent workflow is a sequence of autonomous steps where AI models perform tasks: search, reason, call tools, generate content. The agentic shift means AI doesn't just chat — it actively executes multi-step goals. Our no‑code builder lets you design these pipelines visually.

✨ typical flow

perception ingest query or data
reasoning decompose into sub-tasks
action call APIs, search, compute
synthesis produce final answer

⚙️ Validation & execution

Workflow validation checks for: missing connections, cyclic dependencies, unsupported agent types, and input/output compatibility. The built‑in simulator runs a realistic trace using your selected LLM.

✅ well‑formed workflow: directed acyclic graph, each agent has description, inputs match.

⚠️ common errors: isolated nodes, no initial prompt, agent with missing tools.

📘 example: research & report

1. researcher: search web for "AI agents 2025"
2. filter: extract top 3 frameworks
3. writer: compose blog outline
4. formatter: convert to markdown

👉 just connect nodes. each agent uses tools (search, code, etc.)

❓ Frequently Asked Questions

What does "agentic shift" mean?

It's the transition from AI as a chatbot to AI as an autonomous worker. Agents plan, use tools, and execute tasks with minimal human intervention. Our workflow builder lets you orchestrate that shift.

Can I connect external tools (APIs, databases)?

Yes. Agent nodes can be configured with REST API calls, SQL queries, or custom functions. The no‑code interface uses pre-built connectors (Slack, Gmail, etc.) or you can define OpenAPI specs.

How are workflows executed?

You can simulate inside the browser (as shown) or deploy to our cloud runtime. Each agent runs serverless, with state passed between steps. The free tier supports up to 5 agents.

Is my workflow data secure?

Absolutely. Simulation runs locally in your browser (no data sent). For deployment, you control encryption and endpoints. We follow same privacy standards as site2info SQL tools.

What's the difference from LangChain or DSPy?

This is a visual, no‑code layer on top of those concepts. You design workflows without writing Python. Under the hood we can export to LangChain JSON or YAML.