WhatsApp Voice Assistant with AI Email Agent and Voice Replies
N8N
Project's Category
Intro
This one lets a client send a WhatsApp voice note and get back a reply that's either read, replied to by email, or answered right there on WhatsApp with a generated voice message.
Problems
Voice messages on WhatsApp are easy to send but a pain to act on. Someone had to listen to each one, figure out what the client actually wanted, draft the email if needed, and then reply back in a way that still felt personal rather than a copy paste template.
Solutions
We built a three part n8n workflow. The first part listens for WhatsApp messages, splits and identifies whether it's text, image, or audio, downloads any audio through the WhatsApp Business Cloud API, and transcribes it with OpenAI Whisper into clean structured text. The second part feeds that transcript to an AI email agent that understands the intent behind the message, and depending on what's needed either sends an email automatically, drafts one for manual review, or pulls the recipient's details from an Airtable contact list. The third part generates a summary or confirmation, decides whether a voice reply fits better than text, and sends the response back through WhatsApp as either audio or text.
Final Thoughts
Splitting the workflow into intake, reasoning, and response instead of one long chain makes each part easy to debug on its own. If a transcription comes out wrong, you know exactly where to look without digging through the whole thing.
WhatsApp Voice Assistant with AI Email Agent and Voice Replies
N8N
Project's Category
Intro
This one lets a client send a WhatsApp voice note and get back a reply that's either read, replied to by email, or answered right there on WhatsApp with a generated voice message.
Problems
Voice messages on WhatsApp are easy to send but a pain to act on. Someone had to listen to each one, figure out what the client actually wanted, draft the email if needed, and then reply back in a way that still felt personal rather than a copy paste template.
Solutions
We built a three part n8n workflow. The first part listens for WhatsApp messages, splits and identifies whether it's text, image, or audio, downloads any audio through the WhatsApp Business Cloud API, and transcribes it with OpenAI Whisper into clean structured text. The second part feeds that transcript to an AI email agent that understands the intent behind the message, and depending on what's needed either sends an email automatically, drafts one for manual review, or pulls the recipient's details from an Airtable contact list. The third part generates a summary or confirmation, decides whether a voice reply fits better than text, and sends the response back through WhatsApp as either audio or text.
Final Thoughts
Splitting the workflow into intake, reasoning, and response instead of one long chain makes each part easy to debug on its own. If a transcription comes out wrong, you know exactly where to look without digging through the whole thing.
Building the automation systems that handles business processes.
Clear Communication
Reliable
Professional
Reliable Quality
Building the automation systems that handles business processes.
Clear Communication
Reliable
Professional
Reliable Quality
