Create daily newsletter digests from Gmail using GPT-4.1-mini
Summary
Every day at a set time, this workflow fetches yesterday’s newsletters from Gmail, summarizes each email into concise topics with an LLM, merges all topics, renders a clean HTML digest, and emails it to your inbox.
What this workflow does
- Triggers on a daily schedule (default 16:00, server time)
- Fetches Gmail messages since yesterday using a custom search query with optional sender filters
- Retrieves and decodes each email’s HTML, subject, sender name, and date
- Prompts an LLM (GPT‑4.1‑mini) to produce a consistent JSON summary of topics per email
- Merges topics from all emails into a single list
- Renders a styled HTML email with enumerated items
- Sends the HTML digest to a specified recipient via Gmail
Apps and credentials
- Gmail OAuth2: Gmail account (read and send)
- OpenAI: OpenAi account
Typical use cases
- Daily/weekly newsletter rollups delivered as one email
- Curated digests from specific media or authors
- Team briefings that are easy to read and forward
How it works (node-by-node)
- Schedule Trigger
- Fires at the configured hour (default 16:00).
- Get many messages (Gmail → getAll, returnAll: true)
- Uses a filter like: =(from:@.com) OR (from:@.com) OR (from:@.com -"____") after:{{ $now.minus({ days: 1 }).toFormat('yyyy/MM/dd') }}
- Returns a list of message IDs from the past day.
- Loop Over Items (Split in Batches)
- Iterates through each message ID.
- Get a message (Gmail → get)
- Retrieves the full message/payload for the current email.
- Get message data (Code)
- Extracts HTML from Gmail’s MIME parts.
- Normalizes the sender to just the display name.
- Formats the date as DD.MM.YYYY.
- Passes html, subject, from, date forward.
- Clean (Code)
- Converts DD.MM.YYYY → MM.DD (for prompt brevity).
- Passes html, subject, from, date to the LLM.
- Message a model (OpenAI, model: gpt‑4.1‑mini, JSON output)
- Prompt instructs:
- Produce JSON: { "topics": [ { "title", "descr", "subject", "from", "date" } ] }
- Split multi-news blocks into separate topics
- Combine or ignore specific blocks for particular senders (placeholders ____)
- Keep subject untranslated; other values in ____ language
- Injects subject/from/date/html from the current email
- Split multi-news blocks into separate topics
- Prompt instructs:
- Produce JSON: { "topics": [ { "title", "descr", "subject", "from", "date" } ] }
- Loop Over Items (continues)
- Processes all emails for the time window.
- Merge (Code)
- Flattens the topics arrays from all processed emails into one combined topics list.
- Create template (Code)
- Builds a complete HTML email: - Enumerated items with title, one-line description - Original subject and “from — date” - Safely escapes HTML and preserves line breaks - Inline, email-friendly styles
- Send a message (Gmail → send)
- Sends the final HTML to your recipient with a custom subject.
Node map | Node | Type | Purpose | |---|---|---| | Schedule Trigger | Trigger | Run at a specific time each day | | Get many messages | Gmail (getAll) | Search emails since yesterday with filters | | Loop Over Items | Split in Batches | Iterate messages one-by-one | | Get a message | Gmail (get) | Fetch full message payload | | Get message data | Code | Extract HTML/subject/from/date; normalize sender and date | | Clean | Code | Reformat date and forward fields to LLM | | Message a model | OpenAI | Summarize email into JSON topics | | Merge | Code | Merge topics from all emails | | Create template | Code | Render a styled HTML email digest | | Send a message | Gmail (send) | Deliver the digest email |
Before you start
- Connect Gmail OAuth2 in n8n (ensure it has both read and send permissions)
- Add your OpenAI API key
- Import the provided workflow JSON into n8n
Setup instructions
- Schedule
- Schedule Trigger node:
- Set your preferred hour (server time). Default is 16:00.
- Gmail
- Get many messages:
- Adjust filters.q to your senders/labels and window: - Example: =(from:news@publisher.com) OR (from:briefs@media.com -"promo") after:{{ $now.minus({ days: 1 }).toFormat('yyyy/MM/dd') }}
- You can use label: or category: to narrow scope.
- Send a message:
- sendTo = your email
- subject = your subject line
- message = set to {{ $json.htmlBody }} (already produced by Create template)
- The HTML body uses inline styles for broad email client support.
- OpenAI
- Message a model:
- Model: gpt‑4.1‑mini (swap to gpt‑4o‑mini or your preferred)
- Update prompt placeholders:
- ____ language → your target language
- ____ sender rules → special cases (combine blocks, ignore sections)
How to use
- The workflow runs daily at the scheduled time, compiling a digest from yesterday’s emails.
- You’ll receive one HTML email with all topics neatly listed.
- Adjust the time window or filters to change what gets included.
Customization ideas
- Time window control:
- after: {{ $now.minus({ days: X }) }} and/or add before:
- Filter by labels:
- q = label:Newsletters after:{{ $now.minus({ days: 1 }).toFormat('yyyy/MM/dd') }}
- Language:
- Set the ____ language in the LLM prompt
- Template:
- Edit “Create template” to add a header, footer, hero section, logo/branding
- Include links parsed from HTML (add an HTML parser step in “Get message data”)
- Subject line:
- Make dynamic, e.g., “Digest for {{ $now.toFormat('dd.MM.yyyy') }}”
- Sender:
- Use a dedicated Gmail account or alias for deliverability and separation
Limits and notes
- Gmail size limit for outgoing emails is ~25 MB; large digests may need pruning
- LLM usage incurs cost and latency proportional to email size and count
- HTML rendering varies across clients; inline styles are used for compatibility
- Schedule uses the n8n server’s timezone; adjust if your server runs in a different TZ
Privacy and safety
- Emails are sent to OpenAI for summarization—ensure this aligns with your data policies
- Limit the Gmail search scope to only the newsletters you want processed
- Avoid including sensitive emails in the search window
Sample output (email body)
- Title 1
- One-sentence description
- Original Subject
- → Sender — DD.MM.YYYY
- Title 2
- One-sentence description
- Original Subject
- → Sender — DD.MM.YYYY
Tips and troubleshooting
- No emails found? Check filters.q and the time window (after:)
- Model returns empty JSON? Simplify the prompt or try another model
- Odd characters in output? The template escapes HTML and preserves line breaks; verify your input encoding
- Delivery issues? Use a verified sender, set a clear subject, and avoid spammy keywords
Tags
- gmail, openai, llm, newsletters, digest, summarization, email, automation
Changelog
- v1: Initial release with scheduled time window, sender filters, LLM summarization, topic merging, and HTML email template rendering
n8n Workflow: Create Daily Newsletter Digests from Gmail Using GPT-4.1-Mini
This n8n workflow automates the process of creating daily newsletter digests by extracting emails from Gmail, processing their content, and potentially summarizing them using an AI model (like GPT-4.1-Mini, although the specific model is not explicitly defined in the provided JSON, the node is an OpenAI node). It's designed to help you stay on top of your subscriptions without manually sifting through every email.
What it does
This workflow performs the following key steps:
- Triggers on a Schedule: The workflow starts at a predefined interval (e.g., daily) to check for new emails.
- Fetches Emails from Gmail: It connects to your Gmail account to retrieve emails.
- Loops Over Items: It processes each retrieved email individually or in batches.
- Processes Email Content (Code Node): A
Codenode is included, suggesting custom logic to extract relevant information, clean up content, or prepare it for AI processing. - Summarizes with OpenAI: It sends the processed email content to an OpenAI model (e.g., GPT-4.1-Mini) for summarization or digest creation.
- Sticky Note for Documentation: A sticky note is included, likely for internal documentation or to highlight a specific step or instruction within the workflow.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Instance: A running instance of n8n.
- Gmail Account: A Google account with access to Gmail, and an n8n credential configured for it.
- OpenAI API Key: An OpenAI API key, and an n8n credential configured for it. This is necessary for the AI summarization step.
Setup/Usage
- Import the Workflow:
- Download the provided JSON file.
- In your n8n instance, go to "Workflows" and click "New".
- Click the "Import from JSON" button and paste the workflow JSON or upload the file.
- Configure Credentials:
- Locate the "Gmail" node and configure your Google OAuth 2.0 credential.
- Locate the "OpenAI" node and configure your OpenAI API Key credential.
- Customize the Schedule:
- Adjust the "Schedule Trigger" node to your desired frequency (e.g., daily at a specific time).
- Review and Customize Code Node:
- Open the "Code" node and review its JavaScript logic. This node is where you might define how to filter emails, extract specific parts of the email body, or format the input for the OpenAI model.
- Customize OpenAI Prompt:
- Open the "OpenAI" node. You will likely need to configure the specific model (e.g.,
gpt-4-miniif that's the intention) and craft the prompt to guide the AI in creating your desired digest format.
- Open the "OpenAI" node. You will likely need to configure the specific model (e.g.,
- Activate the Workflow:
- Once configured, activate the workflow by toggling the "Active" switch in the top right corner of the workflow editor.
Related Templates
AI multi-agent executive team for entrepreneurs with Gemini, Perplexity and WhatsApp
This workflow is an AI-powered multi-agent system built for startup founders and small business owners who want to automate decision-making, accountability, research, and communication, all through WhatsApp. The “virtual executive team,” is designed to help small teams to work smarter. This workflow sends you market analysis, market and sales tips, It can also monitor what your competitors are doing using perplexity (Research agent) and help you stay a head, or make better decisions. And when you feeling stuck with your start-up accountability director is creative enough to break the barrier 🎯 Core Features 🧑💼 1. President (Super Agent) Acts as the main controller that coordinates all sub-agents. Routes messages, assigns tasks, and ensures workflow synchronization between the AI Directors. 📊 2. Sales & Marketing Director Uses SerpAPI to search for market opportunities, leads, and trends. Suggests marketing campaigns, keywords, or outreach ideas. Can analyze current engagement metrics to adjust content strategy. 🕵️♀️ 3. Business Research Director Powered by Perplexity AI for competitive and market analysis. Monitors competitor moves, social media engagement, and product changes. Provides concise insights to help the founder adapt and stay ahead. ⏰ 4. Accountability Director Keeps the founder and executive team on track. Sends motivational nudges, task reminders, and progress reports. Promotes consistency and discipline — key traits for early-stage success. 🗓️ 5. Executive Secretary Handles scheduling, email drafting, and reminders. Connects with Google Calendar, Gmail, and Sheets through OAuth. Automates follow-ups, meeting summaries, and notifications directly via WhatsApp. 💬 WhatsApp as the Main Interface Interact naturally with your AI team through WhatsApp Business API. All responses, updates, and summaries are delivered to your chat. Ideal for founders who want to manage operations on the go. ⚙️ How It Works Trigger: The workflow starts from a WhatsApp Trigger node (via Meta Developer Account). Routing: The President agent analyzes the incoming message and determines which Director should handle it. Processing: Marketing or sales queries go to the Sales & Marketing Director. Research questions are handled by the Business Research Director. Accountability tasks are assigned to the Accountability Director. Scheduling or communication requests are managed by the Secretary. Collaboration: Each sub-agent returns results to the President, who summarizes and sends the reply back via WhatsApp. Memory: Context is maintained between sessions, ensuring personalized and coherent communication. 🧩 Integrations Required Gemini API – for general intelligence and task reasoning Supabase- for RAG and postgres persistent memory Perplexity API – for business and competitor analysis SerpAPI – for market research and opportunity scouting Google OAuth – to connect Sheets, Calendar, and Gmail WhatsApp Business API – for message triggers and responses 🚀 Benefits Acts like a team of tireless employees available 24/7. Saves time by automating research, reminders, and communication. Enhances accountability and strategy consistency for founders. Keeps operations centralized in a simple WhatsApp interface. 🧰 Setup Steps Create API credentials for: WhatsApp (via Meta Developer Account) Gemini, Perplexity, and SerpAPI Google OAuth (Sheets, Calendar, Gmail) Create a supabase account at supabase Add the credentials in the corresponding n8n nodes. Customize the system prompts for each Director based on your startup’s needs. Activate and start interacting with your virtual executive team on WhatsApp. Use Case You are a small organisation or start-up that can not afford hiring; marketing department, research department and secretar office, then this workflow is for you 💡 Need Customization? Want to tailor it for your startup or integrate with CRM tools like Notion or HubSpot? You can easily extend the workflow or contact the creator for personalized support. Consider adjusting the system prompt to suite your business
🎓 How to transform unstructured email data into structured format with AI agent
This workflow automates the process of extracting structured, usable information from unstructured email messages across multiple platforms. It connects directly to Gmail, Outlook, and IMAP accounts, retrieves incoming emails, and sends their content to an AI-powered parsing agent built on OpenAI GPT models. The AI agent analyzes each email, identifies relevant details, and returns a clean JSON structure containing key fields: From – sender’s email address To – recipient’s email address Subject – email subject line Summary – short AI-generated summary of the email body The extracted information is then automatically inserted into an n8n Data Table, creating a structured database of email metadata and summaries ready for indexing, reporting, or integration with other tools. --- Key Benefits ✅ Full Automation: Eliminates manual reading and data entry from incoming emails. ✅ Multi-Source Integration: Handles data from different email providers seamlessly. ✅ AI-Driven Accuracy: Uses advanced language models to interpret complex or unformatted content. ✅ Structured Storage: Creates a standardized, query-ready dataset from previously unstructured text. ✅ Time Efficiency: Processes emails in real time, improving productivity and response speed. *✅ Scalability: Easily extendable to handle additional sources or extract more data fields. --- How it works This workflow automates the transformation of unstructured email data into a structured, queryable format. It operates through a series of connected steps: Email Triggering: The workflow is initiated by one of three different email triggers (Gmail, Microsoft Outlook, or a generic IMAP account), which constantly monitor for new incoming emails. AI-Powered Parsing & Structuring: When a new email is detected, its raw, unstructured content is passed to a central "Parsing Agent." This agent uses a specified OpenAI language model to intelligently analyze the email text. Data Extraction & Standardization: Following a predefined system prompt, the AI agent extracts key information from the email, such as the sender, recipient, subject, and a generated summary. It then forces the output into a strict JSON structure using a "Structured Output Parser" node, ensuring data consistency. Data Storage: Finally, the clean, structured data (the from, to, subject, and summarize fields) is inserted as a new row into a specified n8n Data Table, creating a searchable and reportable database of email information. --- Set up steps To implement this workflow, follow these configuration steps: Prepare the Data Table: Create a new Data Table within n8n. Define the columns with the following names and string type: From, To, Subject, and Summary. Configure Email Credentials: Set up the credential connections for the email services you wish to use (Gmail OAuth2, Microsoft Outlook OAuth2, and/or IMAP). Ensure the accounts have the necessary permissions to read emails. Configure AI Model Credentials: Set up the OpenAI API credential with a valid API key. The workflow is configured to use the model, but this can be changed in the respective nodes if needed. Connect the Nodes: The workflow canvas is already correctly wired. Visually confirm that the email triggers are connected to the "Parsing Agent," which is connected to the "Insert row" (Data Table) node. Also, ensure the "OpenAI Chat Model" and "Structured Output Parser" are connected to the "Parsing Agent" as its AI model and output parser, respectively. Activate the Workflow: Save the workflow and toggle the "Active" switch to ON. The triggers will begin polling for new emails according to their schedule (e.g., every minute), and the automation will start processing incoming messages. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
IT ops AI SlackBot workflow - chat with your knowledge base
Video Demo: Click here to see a video of this workflow in action. Summary Description: The "IT Department Q&A Workflow" is designed to streamline and automate the process of handling IT-related inquiries from employees through Slack. When an employee sends a direct message (DM) to the IT department's Slack channel, the workflow is triggered. The initial step involves the "Receive DMs" node, which listens for new messages. Upon receiving a message, the workflow verifies the webhook by responding to Slack's challenge request, ensuring that the communication channel is active and secure. Once the webhook is verified, the workflow checks if the message sender is a bot using the "Check if Bot" node. If the sender is identified as a bot, the workflow terminates the process to avoid unnecessary actions. If the sender is a human, the workflow sends an acknowledgment message back to the user, confirming that their query is being processed. This is achieved through the "Send Initial Message" node, which posts a simple message like "On it!" to the user's Slack channel. The core functionality of the workflow is powered by the "AI Agent" node, which utilizes the OpenAI GPT-4 model to interpret and respond to the user's query. This AI-driven node processes the text of the received message, generating an appropriate response based on the context and information available. To maintain conversation context, the "Window Buffer Memory" node stores the last five messages from each user, ensuring that the AI agent can provide coherent and contextually relevant answers. Additionally, the workflow includes a custom Knowledge Base (KB) tool (see that tool template here) that integrates with the AI agent, allowing it to search the company's internal KB for relevant information. After generating the response, the workflow cleans up the initial acknowledgment message using the "Delete Initial Message" node to keep the conversation thread clean. Finally, the generated response is sent back to the user via the "Send Message" node, providing them with the information or assistance they requested. This workflow effectively automates the IT support process, reducing response times and improving efficiency. To quickly deploy the Knowledge Ninja app in Slack, use the app manifest below and don't forget to replace the two sample urls: { "display_information": { "name": "Knowledge Ninja", "description": "IT Department Q&A Workflow", "background_color": "005e5e" }, "features": { "bot_user": { "display_name": "IT Ops AI SlackBot Workflow", "always_online": true } }, "oauth_config": { "redirect_urls": [ "Replace everything inside the double quotes with your slack redirect oauth url, for example: https://n8n.domain.com/rest/oauth2-credential/callback" ], "scopes": { "user": [ "search:read" ], "bot": [ "chat:write", "chat:write.customize", "groups:history", "groups:read", "groups:write", "groups:write.invites", "groups:write.topic", "im:history", "im:read", "im:write", "mpim:history", "mpim:read", "mpim:write", "mpim:write.topic", "usergroups:read", "usergroups:write", "users:write", "channels:history" ] } }, "settings": { "event_subscriptions": { "request_url": "Replace everything inside the double quotes with your workflow webhook url, for example: https://n8n.domain.com/webhook/99db3e73-57d8-4107-ab02-5b7e713894ad", "bot_events": [ "message.im" ] }, "orgdeployenabled": false, "socketmodeenabled": false, "tokenrotationenabled": false } }