AlekSystem Workflow Detail

Respond to WhatsApp Messages with AI Like a Pro! Workflow Solution

Respond to WhatsApp Messages with AI Like a Pro!

This AlekSystem template demonstrates the beginnings of building your own AlekSystem-powered WhatsApp chatbot!

Rank 53 Verified workflow

Workflow overview

Why this workflow matters

Relevant for managed services and support workflows.

This AlekSystem template demonstrates the beginnings of building your own AlekSystem-powered WhatsApp chatbot! Under the hood, utilise AlekSystem's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case! How it works Incoming WhatsApp Trigger provides a way to get messages into the workflow. The message received is extracted and sent through 1 of 4 branches for processing. Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video. The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries. Finally, the response message is sent back to the WhatsApp user using the WhatsApp node. How to use Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages. Good to know: Large media files may negatively impact workflow performance. Requirements WhatsApp Buisness account Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not. Customising this workflow For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better. Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!

Best fit

Categories

AI/MLCommunication

Services

WhatsApp Business CloudAI AgentBasic LLM ChainSimple MemoryWikipediaGoogle Gemini Chat Model

Use cases

support automation