Bot & AI
Drag, drop, connect. 70+ node types — messages, conditions, AI replies, tool calls, integrations. Marketing managers and product folks ship bots that used to need a developer week.
Node types
Messages, logic, AI, integrations
First bot
From signup to live
Code required
Even for advanced flows
Control
Every change saved
Text, image, video, document, audio, carousel, list, buttons. Drag a message type onto the canvas, fill in the content, you're done.
Branch the flow based on user input, custom fields, AI-extracted intent, time of day, contact tags, or any combination. Visual if-then-else, no scripts.
Drop an 'AI reply' node and the bot uses an LLM (Gemini, GPT, Claude) for that step instead of a scripted message. Mix AI and scripted flows freely.
Call your own APIs from within a flow — fetch order status, push a lead to your CRM, validate a coupon. Configure URL, headers, body via UI; map response fields to flow variables.
Capture user inputs into variables ({{name}}, {{order_id}}). Use them in later messages, conditions, or API calls. Variables persist across the conversation.
Build a 'collect address' sub-flow once, reuse it across 10 bots. Update it once and every bot gets the change.
Pre-built templates for lead capture, appointment booking, e-commerce support, FAQ bots, and 20+ other common flows. Or start blank — both work.
From the left sidebar, drag message nodes, condition nodes, AI nodes, integration nodes onto the canvas. Each node has its own properties panel for content + settings.
Drag from one node's output handle to the next node's input. Condition nodes have multiple output paths — connect each branch to its own next step.
Built-in simulator runs your flow with you as the contact. Step through every branch, inspect variable values at each step, catch logic bugs before publishing.
Click 'Publish'. The bot is now answering customers on WhatsApp. Every published version is snapshotted; revert anytime if a change goes wrong.
| Feature | Edesy | Typical no-code builder |
|---|---|---|
| Drag-and-drop canvas | ||
| Number of node types | 70+ | 10–20 |
| AI nodes (LLM-backed) | Premium tier only | |
| API call nodes (no-code) | Code required | |
| Reusable sub-flows | ||
| Variable system + scoping | Basic | |
| Built-in simulator | Manual testing | |
| Version control + rollback |
Built a multi-step welcome + tutorial + upsell flow in an afternoon. Previously would have needed a 2-week dev sprint.
Shipped 3 days after signup; first trial conversion within a week
Owner with no tech background built a reservation flow with date pickers, party size, allergy capture, and calendar integration.
60% of reservations now via WhatsApp bot vs phone
Ops team built a specialty-based triage flow that asks symptoms, suggests doctor, books slot, sends reminders.
Front desk volume cut in half within a month
Founder built a bot that answers product questions, captures size/color preferences, generates personalized recommendations.
23% reduction in pre-purchase abandonment
Agent built a lead qualification flow that collects budget, location, timeline, then routes hot leads to their phone, cold leads to drip nurture.
Time spent on cold leads down 80%
Admissions counselor built a flow that asks student goals, matches to course, books free demo class with personalized slot suggestions.
Demo class booking rate 4x higher than form
There's a 'no-code is for amateurs' undertone in a lot of developer culture, but for WhatsApp bots it's actively wrong. The conversation flows that businesses need — collect info, branch on response, call an API, send a personalized reply — map almost perfectly to a visual node graph. Trying to express the same flow in code adds boilerplate (handling state, persistence, error retries) without expressing the business logic any more clearly.
More importantly: the people who know the business best are usually not developers. The marketing manager knows what onboarding sequence converts. The clinic ops lead knows the triage logic for routing patients. The restaurant owner knows the reservation rules. If you force them to file a Jira ticket and wait two weeks for a dev to translate their idea into code, you've added a translation layer that slows iteration and often introduces bugs. A visual builder lets the person who owns the outcome ship the flow themselves.
Edesy's flow builder is designed around this. The canvas has 70+ node types covering every common WhatsApp interaction, plus utility nodes for branching, variables, sub-flow composition, and API calls. The AI nodes are the most interesting addition — drop one in any flow and that step becomes an LLM-backed reply with access to your knowledge base, tools, and conversation history. You get the best of structured flows (predictability, version control, testing) and LLM flows (handling unexpected inputs) in one canvas.
The compounding benefit is iteration speed. With a visual builder + built-in simulator + version control, the team can ship a new flow, test it on real conversations within hours, see what's breaking, fix it, and re-ship — all in the same day. Compare to a code-based flow that requires a developer to deploy, a QA pass, and a release. Most teams ship 5-10x more flow improvements per quarter once they switch to a visual builder, which is what actually moves their conversion metrics.
Free workspace, drag-and-drop builder, pre-built templates. Most users have a working bot in their hands within 30 minutes of signup.