Build something Singapore actually needs

The Databricks AI Social Impact (DAISI) Challenge is a national student challenge for Singapore's Institutes of Higher Learning. Student teams take on real societal problems using Singapore's national open data, build free on Databricks, get mentored by Databricks engineers, and pitch to Databricks APJ leadership.

Nine problem statements across three tracks. Every one is grounded in open government datasets from data.gov.sg, SingStat and the agencies, with no login and no cost. Teams take one problem end to end: ingestion, data engineering, machine learning and a live dashboard demo.

Why join

Work on problems that matter: ageing, climate resilience, housing, mobility and community.
Learn a platform used by thousands of companies worldwide, at no cost.
Get a Databricks engineer as a mentor for the two-week build sprint.
Compete for a prize pool worth up to US$24,500.
The top team presents at the launch of the new Databricks Singapore office.

What it costs Nothing. Every team builds on Databricks Free Edition. No credit card, no cluster setup, no infrastructure to manage. Notebooks, SQL warehouses, dashboards, Genie, Lakeflow, Unity Catalog and MLflow are all included.

The three tracks

Track A — Healthy Nation: Caring for an Ageing Singapore
A1 SilverWatch (social isolation risk)
A2 DengueRadar (outbreak forecasting)
A3 HealthPulse (community healthcare demand)
Track B — Green & Resilient City: Climate Action for Singapore
B1 HeatGuard (urban heat risk)
B2 FloodSense (flash flood prediction)
B3 ZeroWaste Navigator (circular economy)
Track C — Liveable & Inclusive City: Housing, Mobility & Community
C1 FlatFair (HDB resale affordability)
C2 MoveEasy (mobility accessibility)
C3 KopilamAI (hawker culture and food access)

Full briefs, datasets and expected demo outputs are in the Participant Guide: https://daisi.online/guide

Requirements

What to Build

Build a working data and AI solution on Databricks Free Edition that addresses one of the nine problem statements across our three tracks:

Track A — Healthy Nation: caring for a super-aged Singapore
Track B — Liveable Nation: sustainability, mobility and the urban environment
Track C — Inclusive Nation: opportunity, affordability and social mobility

Your project must use Singapore national open data (Data.gov.sg, SingStat, LTA DataMall, NEA, HDB, URA and similar public sources) and must be built on the Databricks platform. Judges look for a real, runnable pipeline — not slideware.

A strong submission typically shows:

Data engineering — ingestion and transformation of at least one public dataset into a clean, governed table (Lakeflow, Delta, Unity Catalog)
Analytics or AI — a model, forecast, risk score, agent or natural-language layer that produces a genuine insight (MLflow, Foundation Model APIs, Genie)
A usable output — a dashboard, app or interface a non-technical stakeholder (a social worker, planner or policy officer) could actually use
Social impact — a clear explanation of who benefits and how

Teams of 1 to 4 students from Singapore Institutes of Higher Learning.

What to Submit

Round 1 — Idea submission (closes 6 Oct 2026, 11:59 PM SGT)

A 1-page concept note or 3-slide pitch deck (PDF) covering: the problem statement you chose, your proposed solution, the datasets you will use, and your intended Databricks architecture
Team name and full member list (name, institution, course, year, email)

Round 2 — Final submission (shortlisted top 10 teams, due before Demo Day on 27 Oct 2026)

Demo video — 3 minutes maximum, uploaded to YouTube or Vimeo as a public or unlisted link, showing your solution working
Databricks notebook or repo link — your code, exported notebooks or a public GitHub repository
Written project description on Devpost — problem, approach, architecture, datasets used, results and impact
Pitch deck — up to 10 slides (PDF)
Screenshots of your dashboard, app or Genie space
A short "what's next" note on how the solution could be scaled or deployed

All submissions must be in English. Late submissions are not accepted.

Hackathon Sponsors

Prizes

1 non-cash prize

US$24,500 Total prize value

3 winners

Credits, training and certification across the top 3 teams

Judges

Cecily Ng
Vice President and General Manager, ASEAN & Greater China Region, Databricks

Nicholas “Nick” Eayrs
Vice President, Field Engineering APJ, Databricks

Natsuki Morzaria
Sales Development Manager — Big Data, AI & Machine Learning / Data Intelligence Platform

Judging Criteria

Problem fit & social impact
Clearly addresses the chosen problem; real, describable benefit
Solution quality & originality
Thoughtful approach, not a generic dashboard
Data & technical feasibility
Named open datasets; credible Databricks architecture; buildable in two weeks
Clarity of submission
Concise, well-structured concept note