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Mailpengu

Mailpengu uses artificial intelligence to customize outgoing sales presentations with just one click.
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Mailpengu
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Introduction

Mailpengu is a Google Chrome Extension designed to enhance Gmail functionality for sales professionals. It integrates AI technology to streamline the process of creating and sending customized sales presentations directly from Gmail. By automating recipient information inclusion and offering tracking features, Mailpengu aims to significantly reduce the time spent on preparing individual presentations, potentially saving users up to 50% of their usual preparation time.

Feature

AI-Powered Customization

Mailpengu's AI technology automatically adds recipient-specific information to your presentations, including the recipient's name, company description, and company logo. This feature ensures personalized content delivery with minimal manual input.

One-Click Integration

The extension adds a button to Gmail, allowing users to insert a customized sales presentation into their email with just a single click. This seamless integration simplifies the workflow for sales professionals.

Link Tracking

Users receive notifications when recipients click on links within the sent presentations. This feature provides valuable insights into recipient engagement and helps in follow-up strategies.

Presentation Protection

Mailpengu offers an invisible watermarking feature to safeguard presentations against unauthorized use or distribution, adding an extra layer of security to your sales materials.

Easy Setup and Use

The extension can be quickly installed on Google Chrome, and its user-friendly interface allows for easy navigation and utilization of its features directly within Gmail.

Flexible Pricing Options

Mailpengu provides both a free version with basic features and a paid subscription model offering extended functionality, catering to different user needs and budgets.

FAQ

How does Mailpengu's AI technology work?

Mailpengu utilizes machine learning algorithms to analyze and customize sales presentations. The AI processes recipient information and integrates it seamlessly into the presentation, enhancing personalization and relevance.

Is Mailpengu secure to use?

Yes, Mailpengu prioritizes security by using HTTPS encryption to protect user data. This ensures that your information and sales materials remain confidential and secure during transmission and storage.

Can I cancel my subscription to Mailpengu?

Absolutely. Users have the flexibility to cancel their paid subscription at any time. After cancellation, you can continue using the free version of Mailpengu with its basic feature set.

Latest Traffic Insights

  • Monthly Visits

    290.25 M

  • Bounce Rate

    55.49%

  • Pages Per Visit

    2.84

  • Time on Site(s)

    113.64

  • Global Rank

    -

  • Country Rank

    -

Recent Visits

Traffic Sources

  • Social Media:
    0.68%
  • Paid Referrals:
    0.54%
  • Email:
    0.11%
  • Referrals:
    14.58%
  • Search Engines:
    15.20%
  • Direct:
    68.89%
More Data

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Get ChatGPT for Free with Google

You can now access ChatGPT, a powerful language model, for free with Google. Here's how:

Method 1: Google Colab

* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`

Method 2: Google Apps Script

* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`

Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
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Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.

Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.

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