JAMAL

Jamal, your AI meeting assistant. It offers real-time-insights from project data, calendars, and agreements, clarifies points, fills gaps, and ensures focused, data-driven decisions for every meeting.

Comment

Inspiration

In modern project management, meetings often suffer from miscommunication, data gaps, and unclear decision-making. We were inspired to create Jamal to eliminate these inefficiencies by providing a proactive, data-driven assistant that enhances clarity, precision, and productivity during every meeting.

What it does

Jamal is an AI-powered meeting assistant that offers real-time, context-aware feedback during meetings. It draws from project materials, calendars, agreements, and codebases to: • Clarify points as they arise • Highlight missing information • Provide instant, data-driven insights • Proactively suggest actions or clarifications • Support decision-making with solid project-specific evidence

How we built it

We built Jamal using a combination of cutting-edge technologies designed for real-time, context-aware assistance: • Slack-integrated ElevenLabs Conversational AI powers Jamal’s natural language understanding, enabling it to engage in dynamic, human-like conversations during meetings and respond with contextually relevant insights.

Challenges we ran into

• Ensuring seamless integration with various third-party tools like ClickUp and calendar systems.
• Developing real-time processing that doesn’t lag or interrupt the natural flow of meetings.
• Balancing proactive interventions without disrupting the flow of discussion.
• Building a robust retrieval system for domain-specific knowledge across different data sources.

Accomplishments that we're proud of

• Successfully creating an assistant that can proactively clarify information and suggest actionable insights in real-time.
• Integrating multiple data sources to provide a holistic understanding of project status and requirements.
• Maintaining an intuitive user experience without disrupting the natural flow of discussions.

What we learned

• Real-time AI assistance requires not just speed but context-awareness and subtlety to be effective.
• Data integration across tools is essential for creating a seamless knowledge base.
• Proactive AI must balance being helpful and not overstepping, which requires thoughtful design and testing.

What's next for JAMAL

• Advanced predictive analytics to suggest future project risks or bottlenecks.
• Deeper integration with more project management tools (e.g., Jira, Trello).
• Voice command capabilities for hands-free interaction.
• Enhanced personalization based on individual team member preferences and roles.
• Developing an analytics dashboard to summarize meeting outcomes and track actionable decisions.

Built With

Share this project:

Updates