With rapid growth of AI sector, the need for efficient and intelligent tools has never been more evident. Here where solutions like Microsoft 365 Copilot, feature that integrates with your Microsoft 365 applications to offer advanced assistance enter into the game. Whether you're drafting a business proposal in Word, composing emails in Outlook, creating a presentation in PowerPoint, or summarizing a meeting in Teams, Copilot is designed to work alongside you, making your everyday tasks more efficient.
Much alike Unique FinanceGPT, Copilot is powered by Large Language Models hosted on Microsoft's Azure Cloud. It understands language and context while respecting your privacy and data permissions.
Read on to discover everything you need about Microsoft 365 Copilot and why Unique FinanceGPT can become a game-changer for your business.
What is Microsoft 365 Copilot?
Microsoft 365 Copilot is designed to work alongside you in various Microsoft 365 applications like Word, Outlook, PowerPoint, and Teams.
- In Word, it can write an entirely new document, such as a business proposal, using content from your existing files.
- In Outlook, it can compose email replies based on the content you select.
- In PowerPoint, it can transform written content into visually appealing presentations.
- In Teams, it can generate meeting summaries and discussed follow-up actions.
How Does It Work?
Large Language Models (LLMs) are trained on massive amounts of public data to understand language, context, and meaning. You interact with these LLMs using a "prompt," which could be a statement or a question.The LLM generates a response based on its training and the context provided by the prompt.
Core Components
- Large Language Models (LLMs): These are hosted in the Microsoft Cloud via the Azure OpenAI service. Microsoft 365 Copilot uses its own private instances of these large language models, not the public OpenAI service that powers ChatGPT.
- Orchestration Engine: This is a powerful engine that orchestrates the interaction between different components of the system. It plays a crucial role in managing the interactions between the user, the LLMs, and the organizational data.
- Microsoft Search: This is used for information retrieval to feed prompts to the LLMs. For example, the information provided in a prompt is used to help generate an answer. Microsoft Search helps in retrieving the necessary information from the user's data to construct these prompts.
- Microsoft Graph: This includes additional information about the relationships and activities over your organization's data. The Copilot system respects per-user access permissions to any content and Graph information it retrieves. This is crucial for ensuring that Copilot only generates responses based on information that the user has permission to access.
Together, these components enable Microsoft 365 Copilot to interact intelligently with the user, generate informed responses, and respect the user's privacy and data access permissions.
Privacy and Security
Data Access and Permissions
Microsoft 365 Copilot respects per-user access permissions for any content and Graph information it retrieves. This means that Copilot will only generate responses based on information that the user has permission to access.
Temporary Context
When interacting with the Large Language Models (LLMs), the full conversation gets sent with each subsequent prompt to provide context. However, this context is temporary. The chat history is wiped clean with each new conversation, ensuring that the LLM does not retain any user-specific information.
No Retraining on User Data
The LLMs do not use the knowledge gained from your conversations and interactions to train the model. This means that your specific queries and data are not used to improve or modify the LLMs.
Transparency
Copilot cites each source of information it used to generate a response. This allows the user to easily validate the response and understand where the information is coming from.
Enterprise Data
When generating informed responses, the enterprise data used is only present as part of a prompt to the large language model. These prompts are not retained by the LLMs nor used to train them.
By adhering to these principles, Microsoft 365 Copilot aims to provide a secure and private user experience.
Copilot Examples
- In Teams, if a user asks about activities related to a project, Copilot searches the Microsoft Graph for relevant activities and emails, ensuring it respects the user's permissions. It then formulates a natural, easy-to-follow, and concise response.
- In Word, Copilot can help generate a draft contract by using content from OneNote or other documents that you have access to. It combines this with the LLM's understanding of how a contract document is structured to generate an entirely new contract.
Unique FinanceGPT Applications
While Copilot’s applicability spreads across multiple industries and use cases at the same time, Unique has gathered an extensive knowledge of addressing the needs of the financial sector with its Unique FinanceGPT platform. The advantages of using Unique lie in its vertical AI solutions.
Here’s what it means:
- Vertical Al solutions are tailored to meet the unique needs and challenges of specific industries, providing specialized functionality.
- They incorporate extensive industry expertise to deliver targeted solutions that address specific industry requirements effectively.
- They often employ algorithms and models specifically designed for the particular industry or use case they serve.
- They offer companies instant value by providing a plug-and-play solution that is specifically prebuilt for their business.
- They are designed with adherence to industry specific regulations and compliance standards, ensuring proper governance and data protection.
Unique is currently working with some of the largest banks in Switzerland, including Pictet and LGT, among others, and our solution focuses specifically on the challenges relationship managers and client advisors encounter every day.
Our number one priority is to make your life easier by reducing administrative tasks and increasing your efficiency. In the financial world, it means more time spent with clients rather than on filling out your CRM or preparing documents and proposals.
Unique FinanceGPT in Action
Unique offers an end-to-end experience that covers a wide range of applications. Let’s follow Sara’s workflow with Unique FinanceGPT, for example:
Starting from meeting preparations and finishing with personalized proposals for a client, Sara saves time at every step of the way. For most of her tasks, she can make use of key Unique FinanceGPT features:
- Client meeting recording;
- Meeting summary;
- Unique Chat with uploaded company documents.
For more general tasks, like preparing a presentation for a client, Sara can use the Microsoft 365 Copilot plugin.
Together, Unique and Copilot make for a great user experience, simplifying even the most challenging and time-consuming tasks.
How Unique FinanceGPT works?
Unique uses a variety of AI solutions to perform various tasks, from text summarisation to extracting insights and “chatting” with your internal documents.
To be able to work with big corporate clients like banks and insurances, we continuously strive to enhance and polish our security and compliance measures. We’ve also introduced a compliance layer, with the help of which we aim to make it easy for the user to follow GDPR-principles by employing built-in privacy by design and privacy by default mechanism in all our processes (e.g. automatic watermarking of AI-generated content). We control all information that is sent and received by Large Language Models (like GPT models offered by Microsoft) and make sure to filter out all personal identifiable data by means of pseudonymization.
In addition, we have several opt-outs in place to make sure no data is stored by OpenAI and the prompts are not checked for harmful content. Therefore, our users are strongly recommended to follow responsible prompting guidelines.
Why Unique FinanceGPT?
By leveraging Unique, a company saves a lot of time on creating, installing and hosting complicated systems, as we offer a pre-built, customizable and highly secure solution that is ready to be implemented.
As a general rule, we advise our clients against training their own models. Feeding sensitive company information to further develop AI’s capabilities can be risky. Instead, we offer RAG (Retrieval-Augmented Generation), the concept, which involves using pre-trained models like GPT-3.5 or Llama to generate text based on prompts and existing sources uploaded to the platform.we advise our clients against training their own models. To find out more about the large language models we use, read our recent article.
With Unique, you supercharge your business without using any additional resources as the solution is industry-specific and focuses on challenges you need to solve in the first place.