Call Analyzer with AssemblyAI Transcription and OpenAI Assistant Integration
### Video Guide I prepared a detailed guide that showed the whole process of building a call analyzer. [.png)](https://www.youtube.com/watch?v=kS41gut8l0g) ### Who is this for? This workflow is ideal for sales teams, customer support managers, and online education services that conduct follow-up calls with clients. It's designed for those who want to leverage AI to gain deeper insights into client needs and upsell opportunities from recorded calls. ### What problem does this workflow solve? Many follow-up sales calls lack structured analysis, making it challenging to identify client needs, gauge interest levels, or uncover upsell opportunities. This workflow enables automated call transcription and AI-driven analysis to generate actionable insights, helping teams improve sales performance, refine client communication, and streamline upselling strategies. ### What this workflow does This workflow transcribes and analyzes sales calls using AssemblyAI, OpenAI, and Supabase to store structured data. The workflow processes recorded calls as follows: 1. **Transcribe Call with AssemblyAI**: Converts audio into text with speaker labels for clarity. 2. **Analyze Transcription with OpenAI**: Using a predefined JSON schema, OpenAI analyzes the transcription to extract metrics like client intent, interest score, upsell opportunities, and more. 3. **Store and Access Results in Supabase**: Stores both transcription and analysis data in a Supabase database for further use and display in interfaces. ### Setup #### Preparation 1. **Create Accounts**: Set up accounts for [N8N](https://n8n.partnerlinks.io/2hr10zpkki6a), [Supabase](https://supabase.com/), [AssemblyAI](https://www.assemblyai.com/), and [OpenAI](https://openai.com/). 2. **Get Call Link**: Upload audio files to public Supabase storage or Dropbox to generate a direct link for transcription. 3. **Prepare Artifacts for OpenAI**: - **Define Metrics**: Identify business metrics you want to track from call analysis, such as client needs, interest score, and upsell potential. - **Generate JSON Schema**: Use GPT to design a JSON schema for structuring OpenAI's responses, enabling efficient storage, analysis, and display. - **Create Analysis Prompt**: Write a detailed prompt for GPT to analyze calls based on your metrics and JSON schema. #### Scenario 1: Transcribe Call with AssemblyAI 1. **Set Up Request**: - **Header Authentication**: Set `Authorization` with AssemblyAI API key. - **URL**: POST to `https://api.assemblyai.com/v2/transcript/`. - **Parameters**: - `audio_url`: Direct URL of the audio file. - `webhook_url`: URL for an N8N webhook to receive the transcription result. - **Additional Settings**: - `speaker_labels` (true/false): Enables speaker diarization. - `speakers_expected`: Specify expected number of speakers. - `language_code`: Set language (default: `en_us`). #### Scenario 2: Process Transcription with OpenAI 1. **Webhook Configuration**: Set up a POST webhook to receive AssemblyAI's transcription data. 2. **Get Transcription**: - **Header Authentication**: Set `Authorization` with AssemblyAI API key. - **URL**: GET `https://api.assemblyai.com/v2/transcript/<transcript_id>`. 3. **Send to OpenAI**: - **URL**: POST to `https://api.openai.com/v1/chat/completions`. - **Header Authentication**: Set `Authorization` with OpenAI API key. - **Body Parameters**: - **Model**: Use `gpt-4-2024-08-06` for JSON Schema support, or `gpt-4-mini` for a less costly option. - **Messages**: - `system`: Contains the main analysis prompt. - `user`: Combined speakers' utterances to analyze in text format. - **Response Format**: - `type`: `json_schema`. - `json_schema`: JSON schema for structured responses. 4. **Save Results in Supabase**: - **Operation**: Create a new record. - **Table Name**: `demo_calls`. - **Fields**: - **Input**: Transcription text, audio URL, and transcription ID. - **Output**: Parsed JSON response from OpenAI's analysis.
- Platform
- n8n
- Category
- AI
- Price
- $14.99
- Creator
- Mark Shcherbakov
- if
- set
- webhook
- supabase
- stickyNote
- httpRequest
- manualTrigger
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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