Handling Appointment Leads and Follow-up With Twilio, Cal.com and AI — n8n ワークフロー

複雑度 トリガー24個のノード AI👁 23,186回閲覧作成者:Jimleuk

概要

This n8n workflow builds an appointment scheduling AI agent which can Take enquiries from prospective customers and help them book an appointment by checking appointment availability Where no appointment is booked, the Agent is able to send follow-up messages to re-engage leads. After an appointment is booked, the agent is able reschedule or even cancel the booking for the user without human intervention.

For small outfits, this workflow could contribute the necessary "man-power" required to in

使用ノード

AirtableTwilioAI AgentBasic LLM ChainOpenAI Chat ModelAuto-fixing Output ParserStructured Output ParserHTTP Request Tool

ワークフロープレビュー

Step 6. Filter Open Enquiries from Airtable
💡Criteria For Follow Up Candidates
* No Scheduled Appointment
* No Request to STOP
* No Previous Follow-up in Past 3 days
* Follow-up is less than 3
Step 3. Appointment Scheduling With AI
Learn about using AI Agents
Using an AI Agent is a powerful wa
Step 2. Check for Existing Chat History
Read more about using Airtable
We're using Airtable for customer session manag
Step 1. Wait For Customer SMS
Read more about Twilio trigger
For this workflow, we'll use the twilio SMS trig
Step 9. Cancelling Follow-Up Messages
If the customer messages the bot with the word STOP, we
Step 4. Updating Airtable and Responding to t
Read more about using Twilio
Once the agent formulates a respo
Step 5. Following Up With Open Enquiries
Read more about using scheduled trigger
The second half of this workf
Step 7. Generating a Follow-Up Message
Read more about Basic LLM Chain
With our session and chat h
Step 8. Update Follow-Up Properties and Send
Read more about using Twilio
Finally, we'll update our follow-up a
Try It Out!
This workflow implements an appointment scheduling chat
* Workflow is triggered by Customer enquires sent via S
* Customer session manag
!alt
You'll need to set a custom Header Auth Credential for
🚨 Change EventTypeID Here!
* EventTypeID must be a number.
* Your event type dictates the allowed duration of the
* If Event Type set to 30mins and the agent attempts to
tooltooltoolmodelmodelmodeltooltooltoolparserparser
T
Twilio Trigger
OpenAI Chat Model1
Find Follow-Up Candidates
Send Follow Up Message
Update Follow-Up Count a…
Create/Update Session
Get Existing Chat Session
E
Every 24hrs
Send Reply
Send Confirmation
User Request STOP
C
Check For Command Words
Structured Output Parser
Auto-fixing Output Parser
OpenAI Chat Model2
Generate Follow Up Message
OpenAI Chat Model3
Get Availability
Get Existing Booking
Find Existing Booking
Reschedule Booking
Cancel Booking
Create a Booking
Appointment Scheduling A…
24 nodes22 edges

仕組み

  1. 1

    トリガー

    このワークフローは トリガー トリガーで開始します。

  2. 2

    処理

    データは 24 個のノードを流れます, connecting agent, airtable, chainllm。

  3. 3

    出力

    ワークフローは自動化を完了し、設定された宛先に結果を配信します。

ノード詳細 (24)

AI

Airtable

airtable

#1
TW

Twilio

twilio

#2
AI

AI Agent

n8n-nodes-langchain.agent

#3
BA

Basic LLM Chain

n8n-nodes-langchain.chainLlm

#4
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#5
AU

Auto-fixing Output Parser

n8n-nodes-langchain.outputParserAutofixing

#6
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#7
HT

HTTP Request Tool

n8n-nodes-langchain.toolHttpRequest

#8

このワークフローのインポート方法

  1. 1右側の JSONをダウンロード ボタンをクリックしてワークフローファイルを保存します。
  2. 2n8nインスタンスを開き、ワークフロー → 新規 → ファイルからインポート に進みます。
  3. 3ダウンロードした handling-appointment-leads-and-follow-up-with-twilio-calcom-and-ai ファイルを選択し、インポートをクリックします。
  4. 4各サービスノードの 認証情報(APIキー、OAuthなど)を設定します。
  5. 5ワークフローをテスト をクリックして動作確認し、有効化します。

またはn8nの JSONからインポート に直接貼り付け:

{ "name": "Handling Appointment Leads and Follow-up With Twilio, Cal.com and AI", "nodes": [...], ...}

インテグレーション

agentairtablechainllmlmchatopenaioutputparserautofixingoutputparserstructuredscheduletriggerswitchtoolhttprequesttwiliotwiliotrigger

このワークフローを取得

ワンクリックでダウンロード&インポート

JSONをダウンロードn8n.ioで見る
ノード24
複雑度high
トリガーtrigger
閲覧数23,186
カテゴリAI

作成者

Jimleuk

Jimleuk

@jimleuk

タグ

agentairtablechainllmlmchatopenaioutputparserautofixingoutputparserstructuredscheduletriggerswitchtoolhttprequesttwilio

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