Agentic AI

AI Agents can be effectively integrated into existing applications and operates autonomously, making decisions and pursuing goals, asking for human guidance when needed. 

Semantic Kernel enables seamless integration within .NET, Java, and Python apps, providing developers with a flexible framework for building intelligent features.

Utilizing the Semantic Kernel Process Framework, developers can define workflows and manage how AI components interact with each other and the application.

At a higher level it is used to orchestrate multi agent solutions provided Azure AI Foundry and executed by Azure AI Agent service.

Together, these technologies empower developers to create more responsive and intelligent applications tailored to user needs.

Copilot for Microsoft 365 is an innovative tool that helps you get more out of your Office applications. Copilot understands your requests and offers relevant suggestions, tips, and solutions. You can also customize Copilot to suit your individual needs and requirements.

Plugins are extensions that you can add to Copilot to interact with your existing services. For example, you can install a plugin that allows you to translate your documents into another language with a single click or list tasks assigned to you as a developer in Jira.

Microsoft Graph connectors provide another way to extend Copilot. With these connectors, you can grant Copilot access to data from various internal company data sources, which will then be taken into account when generating responses.

With Declarative & Custom Engine Agents, you can also deploy specialized agents whose expertise can be enhanced through easily uploadable data.

Enhance your team's collaboration and efficiency with the Teams AI library and Custom Engine Agents. These powerful tools automate tasks and provide intelligent insights tailored to your team's specific needs. Custom agents can be extended with skills to interact with your services and databases, ensuring seamless integration.

By utilizing these AI agents, you can enjoy benefits such as improved response times and streamlined workflows, making project management and communication more effective and efficient. Whether it's automating routine inquiries or facilitating complex data analysis and reporting, our solutions cover a wide range of use cases.

You can implement custom agents using Copilot Studio or the Teams Extension, leveraging .NET or TypeScript to create personalized solutions that fit perfectly with your existing workflows. This ensures a smooth transition and immediate productivity gains for your team.

GitHub Copilot acts as a virtual pair programmer, assisting developers by suggesting code snippets, writing documentation, and generating unit tests to enhance productivity.

Its highly customizable nature allows users to provide specific code generation instructions, tailoring suggestions to fit project needs.

In collaborative environments, Copilot can facilitate chat among participants, enabling real-time code discussions and brainstorming.

Developers can also add grounding information and context to improve the relevance of Copilot's suggestions, ensuring that the AI aligns closely with the project's goals.

GitHub Copilot Workspaces enhances collaboration by providing a shared environment where teams can seamlessly work on code together, leveraging AI-driven suggestions.

This tool is particularly beneficial for onboarding new developers, as it offers contextual assistance and guidance within the codebase.

Use cases include pair programming, code reviews, and brainstorming sessions, allowing teams to iterate quickly and efficiently.

Ultimately, Copilot Workspaces fosters a more productive and cohesive development experience, empowering teams to deliver high-quality software faster.

Azure AI Studio plays a pivotal role in the development and deployment of AI applications by providing a user-friendly platform for building, testing, and managing AI models.

It features robust content filters with customizable options, ensuring that generated outputs adhere to safety and compliance standards.

Safe execution of generated code is facilitated through Azure Container Apps, which support dynamic sessions to isolate workloads and enhance security.

Additionally, the platform offers cost control options, allowing organizations to monitor and optimize their AI resource usage effectively.