Team Tasks AI

Team Tasks AI is a web app that lets teams track tasks, check in via text or voice, and get AI-generated summaries using Azure AI, boosting productivity with smart insights and automation.

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The Inspiration

The inspiration for Team Tasks AI stemmed from the need to address a common pain point in distributed teams: obtaining timely project and task updates from team members working across different time zones with varying availability for daily update meetings. We sought to create a solution that eliminates the logistical challenges of scheduling synchronous check-ins, enabling seamless collaboration and communication regardless of geographic or temporal barriers.

What it does

Developed for the Azure AI Developer Hackathon, Team Tasks AI is a collaborative task management web application designed to streamline team workflows. By integrating AI-powered check-ins and intelligent summaries, the platform empowers teams to efficiently assign, track, and manage tasks. The application leverages Azure’s cutting-edge AI capabilities to provide real-time insights, automate status updates, and generate concise summaries, ensuring that all team members stay aligned and informed—regardless of their location or schedule.

How we built it

Team Tasks AI was built using a modern tech stack tailored to scalability and performance. We utilized Azure services, including Azure Cosmos DB for robust data storage, Azure Functions for serverless task processing, and Azure AI Foundry to infuse intelligent automation into the application. The front-end was developed with a responsive web framework, while GitHub Copilot accelerated our coding process by providing real-time suggestions and streamlining development. Collaborative version control was managed through GitHub, enabling our distributed team to work cohesively despite time zone differences.

Challenges we ran into

One of the primary challenges we encountered was coordinating effectively among team members spread across multiple time zones, each with conflicting schedules for daily update meetings. This mirrored the very problem we aimed to solve, making it a real-world test of our concept. One of the key challenges we faced was optimizing our interactions with the GPT model. We engaged in ongoing discussions about the best approach to send requests, aiming to balance functionality with efficiency. A significant focus was reducing the number of tokens consumed per chat and report generation, which required us to experiment with various strategies, refine our prompts, and adapt our implementation—all while ensuring the AI features remained effective and valuable for users. Additionally, integrating Azure’s advanced services into a cohesive application presented a learning curve, requiring us to quickly adapt to new tools and troubleshoot unexpected technical hurdles under tight deadlines.

Accomplishments that we're proud of

While Team Tasks AI is still a work in progress, we take great pride in the significant strides we’ve made during this hackathon. Our team successfully learned to design and develop an end-to-end product with the potential to serve the public, gaining hands-on experience in every stage of the process—from ideation to implementation. Equally important, we’re proud of how we grew as a cohesive unit, mastering the art of delegation and collaboration to leverage each member’s strengths effectively, even under challenging circumstances.

What we learned

Throughout this project, our team gained valuable insights into leveraging emerging technologies to solve real-world problems. We adapted to new frameworks with the assistance of GitHub Copilot, which enhanced our coding efficiency and introduced us to innovative development workflows. Additionally, hands-on experience with Azure services—such as Azure Cosmos DB, Azure Functions, and AI Foundry—deepened our understanding of cloud-based AI solutions and their practical applications in task management.

What's next for Team Tasks AI

Looking ahead, our team is committed to refining and expanding Team Tasks AI. Future enhancements will focus on improving AI-driven insights, such as predictive task prioritization and personalized recommendations for team members. We plan to incorporate user feedback to enhance usability, add mobile compatibility, and explore integrations with popular collaboration tools. Our goal is to evolve Team Tasks AI into a robust, market-ready solution that empowers teams worldwide to work smarter and more efficiently.

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