How To blog Meetings Microsoft Teams Productivity sentiment Analysis guides Uncategorized

Using Microsoft Teams and Monday? Try this integration

Teams and mondaycom integration

Achieving success as a team in the workplace heavily relies on effective communication and collaboration. The ability for individuals to openly exchange their ideas and skills results in a smoother and more efficient path towards a shared objective.

By collaborating with as many applications as possible, aims to give teams the tools they need to work from anywhere. Microsoft Teams has joined the same trend and is expanding the number of integrations it offers to make its service more appealing and user-friendly.

In July 2020 announced it can now integrate with Microsoft Teams, this is the first time the two platforms can be integrated without a third-party app.

Advantages of an integrated and MS Teams:

This Integration, once set up, enables its users to do several amazing things:

  1. Create new items in from a Microsoft account.
  2. users can collaborate and manage their workflow in Microsoft Teams.
  3. Share items and boards using Microsoft Teams.
  4. Create ‘recipes’ on for notifying Microsoft Teams of any changes

How to Integrate to Microsoft Teams

The process of setting up the and MS Teams integration is a fairly easy process.

  1. First, create a account if you don’t have one already.
  2. Log in to your account.
  3. Go to the board in which you want to set up the Integration.
  4. Click on the Integration button found on the upper right part of the screen.
  5. Select MS Teams from the list of applications offered.
  6. Click on the MS Teams’ integration banner and select any of the available recipes. You can choose to notify the team channel when:
  •       A date arrives
  •       An item is created
  •       A column changes
  •       A status changes

    There are also options for sending updates to a Microsoft Team channel.
  1.  After this, select the Integration you wish to create.
  2. The system will prompt you to connect your Microsoft Teams account with your account.
  3. Log in to your MS Teams account using your Office 365 Administrator’s login credentials. If you are the administrator, the process will already be complete. Otherwise, make sure the administrator is part of the team and accepts the invitation for the Integration with

Make this integration even better with AGI the AI virtual assistant

With AGI Virtual Assistant, no meeting in MS Teams will go by without clear action items, Tasks and insights are automatically detected and synced into

AGI provides a dashboard containing meeting insights, summaries, and tasks that are available natively on as well as on your favourite meetings platform: Teams, Webex, and Zoom.

Benefits of using AGI with the and MS Teams integration

Automatic task detection

AGI creates tasks on the go, using AI to detect tasks from meetings and chats on Teams. There is no need to speak to an assistant or manually capture the task.

Identify All Task Details

Details such as task name, due date, and assignee are automatically detected from meeting transcript and chat conversation using the AI engine.

Auto-generated Summaries

AGI generates meeting summaries, both, brief-to-the-point summaries and more in-depth ones. These summaries are ideal for sharing with meeting participants or just to get a quick overview of the meeting.

Meeting Minutes Documents

Based on your own custom template, AGI will create meeting minutes including all attendees and tasks, which can be exported as a PDF

Sentiment Analysis

Sentiment Analysis is one of AGI`s strongest features. It gives you an overall score on how the meeting went and a percentage of how positive or negative the communication was. Use sentiment Analysis to identify trending topics, challenges, and user issues such as unsatisfied or unhappy staff.

Continuous Collaboration

Post tasks for discussion in Teams chat with a link to the relevant recording point.

All In One Place

Task Creation happens entirely inside as well as MS Teams so you don’t need to hop around to find tasks or sprints.

No need for other logins.

Choose to review or trust AGI to create tasks

AGI supports virtually any language to detect tasks. You can then set confidence levels to automatically create tasks with no need to review or approve tasks that will automatically sync with

To find out more about AGI or and Microsoft Teams integrations visit our website or contact us today!



Announcement Microsoft Teams sentiment Analysis guides webex guides

AI Sentiment Analysis of Chats & Meetings in MS Teams and Webex


  • What is sentiment analysis?
  • Why is sentiment analysis important?
  • What is sentiment analysis used for?
  • How does sentiment analysis work?

What is sentiment analysis?

The process of analyzing call recordings and chat to determine whether the underlying emotions are positive, negative, or neutral is the definition of AI sentiment analysis.

In other words, sentiment analysis helps to find the person’s feelings in a particular situation and define the emotions involved to be either joyfulness, happiness, surprise, anger, disgust, or sadness. 

Why is sentiment analysis important?

First and foremost, AI sentiment analysis is important to help spread positive behavior to other parts of the company. With the positive and negative communications documented in every employee’s report, sentiment analysis can help businesses promote positive behavior in the workplace. This can be done by comparing employees’ performances and encouraging everyone to improve.

Furthermore, evidently, businesses must ensure that customers are receiving excellent service. Sentiment analysis can help businesses identify negative behavior and detect any interaction that may have been negative. This will help in managing the employees’ negative behavior to provide the best customer experience.

Thirdly, Understanding customers’ emotions can empower the employees with knowledge that can help them provide better service. The customer-facing team can therefore offer proactive solutions to increase customer satisfaction.

Fourthly, by analyzing employees’ communications, companies can better understand how they feel, which in turn helps reduce employee turnover and increase overall productivity.

Lastly, sentiment analysis can give visibility to employee communication with others while working remotely which in turn helps employees stay connected to their team and improve their collaboration with others.

What is sentiment analysis used for?

Sentiment analysis can be useful in different business departments or divisions. Let’s see in more detail how sentiment analysis benefits some of them.

  • Customer Success / Support Managers:

Sentiment analysis is an extremely useful tool in the customer service field as it allows businesses to improve their direct communications with customers. It can also help businesses prioritize their customer support issues by identifying and handling the most negative feedback first, which increases customer retention and satisfaction by providing quick answers.

  • HR Manager:

Sentiment analysis helps HR managers make decisions and organizational changes based on employee feedback and satisfaction to promote proactive action before any interview or conversation.

  • Employees:

Employee reports can help an employee objectively analyze their relationships with other colleagues within the organization, as well as their communication trends.

Sentiment Analysis info graphics
AI Sentiment Analysis Infographics

How does sentiment analysis work? 

AI sentiment analysis employs natural language processing and machine learning algorithms to classify text and audio pieces as positive, neutral, or negative.

  • Natural Language Processing:

NLP uses computer-based methods that analyze the human language used in communications. In order for machines to understand human text and speech, NLP techniques need to be put in place. This includes Tokenization, Stemming, and Part-of-Speech (POS) Tagging. After the natural language processing is completed, the text will be ready for the classification process of machine learning.

  • Machine Learning:

Using existing data, machines are trained to recognize patterns in new data sets to predict the sentiment behind a given text and automatically classify it as positive, negative, or neutral.

AGAT Software recently released its first AI sentiment analysis engine, to learn more about it, contact us today.