No-Code AI Agent Builder

Build intelligent AI agents
that talk, learn & act on your website.

Create custom web voice & chat agents in 30 seconds. Connect knowledge bases, structured datastores, and 3rd-party SaaS integrations using specialized sub-agents.

Build Your Agent Free Watch 5-Step Workflow
Chat & Voice
Dual Web Modality
Knowledge Base
RAG & Article Engine
Datastores
Structured Schemas
Sub-Agents
SaaS & Workflow Mesh

Embage AI Assistant

Live Widget

Online • Ready to chat & talk out loud

Demo Scenarios:

Hi! Is the Cobalt Ceramic Mug in stock and when would it ship to NYC?

10:42 AM

Yes! The Cobalt Ceramic Mug is in stock (14 units remaining). Standard shipping to NYC takes 2 business days. Would you like me to reserve one?

10:42 AM
Shopify Sub-Agent checked inventory
How it feels

Build something helpful. Keep a human in the loop.

  1. 01

    Build

    Shape a friendly AI agent or chatbot with your prompts, knowledge, and tools — no coding required.

  2. 02

    Help

    Let it search docs, save tickets and leads, look up products, and draft follow-ups for your team.

  3. 03

    Hand off

    When it’s stuck or someone asks for a person, bring your team in with the full context.

  4. 04

    Improve

    Learn from every chat or voice chat — what worked, what was missing, and what to do next.

Visual Feature Breakdown

Engineered for real-world business automation

Explore every core feature graphically — from modular sub-agent task routing and custom datastore schemas to SaaS app integrations and post-conversation background workflows.

Pillar 01

Modular Sub-Agent Mesh Architecture

Instead of overloading a single prompt, Embage delegates specialized tasks to dedicated sub-agents. The Main Agent routes requests intelligently, reducing latency and cost.

Orchestration Architecture

Modular Sub-Agent Mesh

Main Agent Hub Active
Main Agent Hub

Orchestrator Agent

Parses visitor intent, handles conversation memory, and delegates specialized tasks to target sub-agents.

Task Router: Knowledgebase Sub-Agent
Pillar 02

Post-Conversation Workflow Sub-Agents

Work doesn't stop when a chat or call ends. Post-Conversation Sub-Agents automatically analyze transcripts, extract customer intent, log datastore rows, and trigger follow-up emails.

Automated Follow-Through

Post-Conversation Workflow Sub-Agent

Triggered On Call/Chat End
01

Transcript Analysis & Sentiment

Extracts main user intents, resolution score, and sentiment tags.

Automated background task
02

Datastore Record Creation

Auto-saves lead information, tickets, or feedback rows into Datastore.

Automated background task
03

Email Summary Dispatch

Sends automated session summaries to team reps and visitors.

Automated background task
04

Webhook & CRM Sync

Fires custom webhooks to update Slack channels and HubSpot deals.

Automated background task
Pillar 03

Dual RAG & Article Knowledge Engine

Combine broad semantic vector search across large documents with pinpoint article-level matching. Your agent gives accurate answers directly from your official documentation.

Zero-Hallucination Retrieval

Dual RAG & Article Engine

Ingested Data Sources:

Documentation URLs

12 Pages Crawled

Product Manual PDFs

4 PDFs Ingested

Help Articles & FAQs

28 Knowledge Cards

Semantic Vector RAG

Embedding Similarity Search

Splits ingested PDFs, markdown, and URLs into semantic vector chunks. Queries return exact matching contexts to synthesize multi-document answers.

Query: "What is your refund window for damaged goods?" → Match Confidence: 98.4%
Pillar 04

Custom Datastore Builder & State Management

Turn unstructured visitor conversations into clean database records. Define custom table schemas for leads, support tickets, and feedback without writing glue code.

Structured Datastore Engine

Custom Schema Builder

Real-time Agent Read & Write

Table Schema: Lead Intake

4 Columns

visitor_email

Primary Contact

Text / String

lead_score

Qualification

Integer / Rating

budget_tier

SaaS Plan

Enum / Options

status

State

Status / Enum

Live Agent Writes

Auto-populated from chat
EmailScoreBudgetStatus
sarah@acme.com92 / 100Enterprise ($10k+)Qualified
david@techcorp.io84 / 100Pro Team ($2k)Pending Demo
No glue code needed Datastore Sub-Agent handles validation
Pillar 05

3rd-Party App Integrations Ecosystem

Connect Shopify, Gmail, HubSpot, Slack, and Google Calendar with one-click provider authentication. Every connected app generates a dedicated tool sub-agent.

Integration Sub-Agents

3rd-Party SaaS Ecosystem

One-click provider auth
Shopify

Shopify Sub-Agent

Connected

Dedicated tool sub-agent automatically wired to your Main Agent.

Automated Actions:

Lookup product inventory Track order shipping status Fetch store collections
Chat or voice Voice AI Meet Included

Same friendly agent. Talk out loud.

Embage isn’t chat-only. Build a voice agent that answers from your knowledge, executes sub-agent actions mid-call, and speaks back — right in the browser, no phone line needed.

Live voice session

Speaking with your website agent

Mic connected

Voice AI Meet Active

Runs in browser tab · Zero phone line needed

Live Transcript

Visitor

Hi, I'm looking at your Pro plan for our team of forty people.

Agent

Pro covers that comfortably. Are you looking for chat support, or voice AI on the site as well?

Visitor

Both! Can you log a demo request for next Tuesday?

Datastore Sub-Agent logged demo request row
First-class voice agents
Same agent as chat
Interrupt mid-sentence
Sub-agent actions mid-call
One embed, voice or chat
Visual Workflow

Build your website agent in 5 visual steps

Assemble your Main Agent, connect specialized sub-agents step-by-step, and deploy to your website in minutes.

01 Orchestrator Setup

Create Main Agent

Fill in all fields — agent name, system prompt, brand tone, LLM model choice (Gemini, Claude, GPT), and choose between dual voice or chat widget.

Agent Name Customer Support & Sales Agent
Model Google Gemini 1.5 Flash / Claude 3.5 Sonnet
Mode Dual Voice & Chat Widget Embed
Sub-Agent Wiring Active

Create Main Agent

Auto-wired to Main Orchestrator Agent Hub.

Conversation Intelligence

Every conversation ends with a record, not a transcript

When a conversation finishes, a reviewer fills structured fields — score, tags, action items, knowledge gaps, and any custom fields you add — then can save records and run follow-ups in your tools.

  1. Conversation ends

    The visitor closes the chat or hangs up the call.

  2. A reviewer reads it

    A dedicated reviewer goes through the entire transcript, start to finish.

  3. Fields get filled

    Score, tags, action items, knowledge gaps — plus any custom fields you define.

  4. Actions can run

    Save a lead or ticket, or trigger a follow-up in your connected apps.

What you get back

Extract what matters — then do something with it

Built-in fields like score, tags, action items, and knowledge gaps keep every conversation comparable. Add your own fields when you need more. Then let the reviewer write to a datastore or call your connected apps.

  • Score, tags, action items, knowledge gaps
  • Custom fields you define for your business
  • Save leads, tickets, and feedback to a datastore
  • Trigger follow-ups in connected apps

Conversation record

Pro plan enquiry · 40 seats

Follow-up

Summary

Visitor is evaluating the Pro plan for a 40-person team and wants both chat and voice on their site. Asked for a walkthrough this week and left an email.

Sentiment

Positive

Goal met

82

Next steps

  • Send the 40-seat Pro quote to Priya High
  • Book the walkthrough for Thursday Medium

Could not answer

"Do you offer annual invoicing?"

pricingvoicedemo-requestteam-plan

Actions taken

  • Lead saved to datastore
  • Follow-up drafted in connected email

Custom fields

Start with summary, score, tags, action items, and knowledge gaps — or add your own fields that match how your team works.

Write to your datastore

After the conversation, create or update leads, tickets, feedback, and bookings automatically.

Act in connected apps

Draft email follow-ups, notify a channel, or sync a CRM record — using the same tools your agent already has.

Read more about conversation intelligence
Integrations

Connect your business stack

Give your AI agent safe tools for the work behind each conversation: draft Gmail follow-ups, look up Shopify products, save HubSpot leads, notify teams, and run calendar workflows.

Gmail
Shopify
HubSpot
Salesforce
Mailchimp
Slack
Notion
Intercom
Jira
Calendly
Stripe

And many more — over 1,000 apps you can connect in one click

Request an Integration
Solution-Oriented Use Cases

Built for real-world business solutions

Deploy specialized AI agents for e-commerce support, technical documentation RAG, inbound lead qualification, and voice reception.

E-Commerce Storefront Agent

E-Commerce
Chat Mode

Answers product spec questions from your Knowledge Base and fetches live shipping or order status via Shopify Sub-Agent.

Visitor

Is the TrailPack Backpack in stock and can I return it within 30 days?

Agent

Yes! Black TrailPack is in stock (14 left). Our 30-day money-back guarantee applies to all unused gear.

Shopify Sub-Agent checked inventory & return policy
Business Outcome: 24/7 Shopper Assistance & Zero Support Backlog

SaaS Technical Support Agent

SaaS & Tech
Chat Mode

Ingests developer documentation, API guides, and help desk articles to resolve technical setup queries instantly.

Visitor

How do I configure database-per-tenant isolation for custom datastores?

Agent

Each org database is isolated automatically. You can define table columns in your dashboard using our visual schema editor.

Knowledge Base Sub-Agent retrieved RAG docs
Business Outcome: Instant 24/7 Resolution from Official Docs

Inbound Lead Qualification Agent

Lead Gen
Chat Mode

Replaces long static lead forms with interactive conversation. Captures buying intent and writes structured records to your Datastore.

Visitor

We have 40 sales reps and want to try voice agents for inbound demos.

Agent

Pro plan covers 40+ seats! What's the best work email for your team so I can record your demo request?

Datastore Sub-Agent logged qualified lead row
Business Outcome: Higher Form Conversion & Automated CRM Sync

Local Services AI Receptionist

Receptionist
Voice Mode

Greets visitors by voice or chat, answers business hour FAQs, and takes structured appointment requests into your Datastore.

Visitor

Hi, do you have any open slots for a consultation next Tuesday afternoon?

Agent

Tuesday afternoon works! I have 2:00 PM or 3:30 PM available. Which time suits your team best?

Voice AI Meet + Datastore appointment intake
Business Outcome: Hands-Free Booking & Reduced No-Shows
Test Only

Your first friendly agent
is about 10 minutes away.

We’re in a public test — jump in, build a chatbot or voice agent, and forgive a few rough edges. Data may reset.

Signup Read Docs

Test environment · No credit card required

Resources

Latest from our Blog

Friendly guides on building AI agents and chatbots, voice on your website, human handoff, support workflows, Gmail and Shopify, and fair usage-based pricing.

AI Agent Builder Aug 1, 2026

How to Build a Custom AI Customer Support Agent in Embage: Step-by-Step Guide

A complete walkthrough on creating a customer support AI receptionist: building knowledge bases, datastores, sub-agents, integrations, and database isolation.

Read Article
Gmail Aug 1, 2026

Gmail AI Agent Workflows for Website Support and Sales: Full Setup Guide

How Embage agents use 1-click Gmail connection, specialized sub-agents, and post-conversation workflows to search, draft, and send Gmail follow-ups automatically.

Read Article
Features Aug 1, 2026

Build & Deploy Custom Voice & Chat AI Agents in 30 Seconds: Inside Embage's No-Code Engine

Discover how Embage enables non-technical teams to configure, customize, and deploy secure AI voice and chat receptionists in 30 seconds.

Read Article
View All Articles
Pricing

Cheaper because pricing stays close to raw usage

Embage does not charge every chat as the same flat session. Your plan includes clear monthly action caps and a model-provider budget, so tiny chats stay cheap and complex workflows are visible.

Chat is not billed as a flat per-session fee

Free

BYO key

$0 /month

For testing a first website AI agent with your own model key.

50 knowledgebase searches/mo
30 datastore writes/mo
20 integration calls/mo
Bring your own model key
Website chat embed
Signup

Starter

$10 model budget

$9.99 /month

For small businesses adding support, leads, and feedback to a site.

500 knowledgebase searches/mo
1,000 datastore writes/mo
200 integration calls/mo
1,000 voice minutes/mo
$10 OpenRouter budget included
Signup
Most Popular

Pro

$50 model budget

$49 /month

For growing teams using Embage as a daily AI receptionist.

5,000 knowledgebase searches/mo
10,000 datastore writes/mo
2,000 integration calls/mo
10,000 voice minutes/mo
$50 OpenRouter budget included
Signup

Enterprise

$200 model budget

$199 /month

For high-volume support, sales, and voice-to-voice operations.

50,000 knowledgebase searches/mo
100,000 datastore writes/mo
20,000 integration calls/mo
40,000 voice minutes/mo
$200 OpenRouter budget included
Contact Us

Why this is cheaper than per-session chat pricing

A two-message FAQ chat and a long support investigation should not cost the same. Per-session pricing averages those together and makes small sessions expensive. Embage keeps chat cost tied to model budget and only meters completed actions like knowledgebase searches, datastore writes, and integration calls.

Talk to Sales

Pricing example

Flat session fee vs raw/capped usage

Tiny FAQ chat

2 messages: What are your hours?

Per-session

A flat session fee can overcharge this.

Embage

Only model budget is touched unless an action runs.

Real support workflow

20 messages + KB search + ticket write + Gmail follow-up

Per-session

Flat pricing hides real work and often forces higher averages.

Embage

You see the raw work: model budget, KB query, datastore write, integration call.

FAQ

Questions searchers ask before they try Embage

Clear answers for offices and merchants evaluating secure AI receptionists.

What is Embage?

Embage is a friendly no-code AI agent and chatbot builder for websites. You can create chat or voice agents that answer from your knowledge, help with everyday workflows, and hand off to a human when someone needs a person — great for support, reception, lead capture, bookings, and more.

How does Embage handle business and customer data?

Your organization’s data stays isolated and permissioned. Knowledge, datastore records, conversations, and tool access are scoped to your team, so agents only use what they’re allowed to use.

Can I add Embage to my website?

Yes. Build an agent, point it at your knowledge and tools, then paste a small embed on your site. The same widget can chat or talk by voice.

Does Embage support human handoff?

Yes. Agents help with what they can from your knowledge and workflows, then bring a human in when they’re unsure or when a visitor asks for a person — often by creating a ticket with the conversation context.

How does Embage pricing work?

We don’t charge every chat the same flat session fee. Paid plans include monthly action caps and a model budget, so short chats stay light while searches, writes, and integrations are metered clearly.

Can Embage connect to Gmail, Shopify, HubSpot, and other apps?

Yes. Connect the tools your team already uses so a conversation can draft a Gmail follow-up, look up a Shopify product, save a lead, or nudge the right workflow.

Does Embage support voice-to-voice agents?

Yes — voice is a first-class part of Embage, not an afterthought. Visitors can talk in the browser with no phone number. Voice minutes follow your plan, while tool actions still use the same knowledge, datastore, and integration caps.

Get In Touch

Want a hand building your AI agent?

Say hello — we’d love to chat about chatbots, voice agents, human handoff, or rolling Embage out for your team.

Email us

Direct line to our founding team

aradhya.tiwari@embage.com

Response time

We reply to every inquiry within 24 hours