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Databricks Building Intelligent Apps Hackathon

angelhackHosted on AngelHack

Fetched about 4 hours ago

Monday, April 6, 2026

to Monday, June 15, 2026

•

2 months long

Data ScienceMobile DevelopmentSocial Impact

Event Type

online

USD68,000

Prize Pool

Build Intelligent Apps with Data + AI Welcome to the Databricks Building Intelligent Apps Hackathon, in collaboration with AWS. This APJ-wide virtual hackathon invites app developers, data and AI engineers, analysts, and business users to team up and build intelligent applications on Databricks that solve real-world business problems. This year’s challenge is simple: go beyond dashboards and create apps that combine data, AI, analytics, and automation into experiences people can use every day. Using Databricks Apps, Genie, Lakebase, and Agent Bricks, teams will design and prototype intelligent solutions that deliver insights, automate workflows, and create new user experiences. 🛠️ Your Toolkit for Innovation: Databricks Apps– Build and deploy intelligent applications for real business use cases. Genie – Enable natural language interactions and conversational analytics. Lakebase– Support app and agent experiences with operational data and memory. Agent Bricks– Create intelligent assistants and agent-driven workflows. Prizes 🏆 US$68,000 in total prizes

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct