databricks

Databricks Got Enterprise Teams Across APJ Building Intelligent Apps

966

participants

Databricks hackathon

industry

Technology

SERVICES

Hackathon

Outcome

Product Adoption

Databricks, along with AWS, partnered with AngelHack to run the Building Intelligent Apps with Data + AI Hackathon, a virtual program in APAC, with the goal of product adoption. The team looked for cross-functional enterprise teams building applications people could use daily, centred on four new products: Databricks Apps for deployment, Genie for plain-language querying, Lakebase for app memory, and Agent Bricks for agent workflows.

Registration opened on 6 April 2026 and winners were announced on 17 June, giving the hackathon a nine-week build window across five markets. Databricks brought the platform, the customer relationships and the technical bench. What they needed was a way to reach builders inside their own accounts, in three languages, without any single market slipping behind the others.

The Challenges: Targeted Audience, Three Languages, One Timeline

This hackathon recruited from inside enterprise accounts rather than the open developer market, which changed almost every operational assumption. Databricks shared three constraints with us at the design stage:

Eligibility ruled out most standard recruitment channels.
Participants needed a corporate email address, students and consultants and Databricks partners were excluded, and each member of a two to four person team had to qualify independently.

🗣️ Three language tracks required localization efforts.
English, Japanese and Korean each needed their own registration path, rules documentation, support channel and community outreach, with accurate translations to hold up as competition terms.

🕐 Five markets ran on one clock.
The English track alone covered ANZ, ASEAN and India, each with different developer communities and working hours, and every market had to hit the same registration close, submission deadline and judging window.

Getting all three right at once required a large amount of planning and coordination, so the program was built around that.

The Operational Work Behind an APJ-Wide Hackathon

How we designed and operated the program end-to-end, from recruitment through to the winners’ announcement.

Targeted Account Outreach

AngelHack ran outbound campaigns into Databricks’ named accounts and tapped local developer platforms across ANZ, ASEAN, India, Japan and Korea, reaching builders outside the usual channels.

Three-Track Localisation

AngelHack translated hackathon assets, site copy and rules documentation into Japanese and Korean, built market-specific registration pages, and ran localised outreach through developer communities.

Technical Enablement

Workshops covered Databricks Apps, Genie, Lakebase and Agent Bricks in practical terms, office hours with Databricks solution architects ran throughout the build period, and eligible teams received USD 700 in Express credits, so cost wasn’t a barrier to building.

Weekly Operating Rhythm

Weekly calls carried progress reporting, program highlights and named next actions for all five markets on a single agenda, which is how five timelines stayed as one.

Submission Management & Judging Facilitation

Five criteria carried equal 20% weighting across business applicability, creativity, user experience, technical capability and data storytelling. Databricks’ technical panel reviewed every submission first, then the top five teams per language track advanced to executive judging.

databricks quote

Impact: 80 Working Apps from Inside the Enterprise

Nine weeks later, Databricks had hundreds of enterprise teams building on its newest tooling and a portfolio of working prototypes to prove it.

  • 966 participants, against a target of 500
  • 80 completed submissions

Six teams won, two from each language track, with use cases spanning climate risk, housing, solar forecasting and emergency care.

Databricks Got Enterprise Teams Across APJ Building Intelligent Apps

🇬🇧 English Track

1st place (Social Impact): EcoResilience by Cartology team
A disaster risk platform for Australian SMEs, scoring supply chain exposure by postcode and generating pre-filled government grant applications through a conversational agent.

2nd place (Social Impact): Housing Assistant, Kāinga by ZURU team
A housing affordability platform for Aotearoa New Zealand, unifying six open government datasets to serve both renters searching in plain English and council analysts tracking affordability trends.

🇯🇵 Japan Track

1st place (Social Impact): SunCast by NGK team
A forecasting and advisory application for Japanese solar operators, re-forecasting output against submitted plans and pricing each corrective action before gate close.

2nd place (Social Impact): 海峡 (Kaikyō) by Sony team
A maritime chokepoint monitor for energy traders, detecting anomalies in major straits and simulating the downstream impact on Japan if a closure runs long.

🇰🇷 Korean Track

1st place (Business Impact): BAAMM (Business Accelerating AI Messaging Machine) by Korea Credit Data team
A personalised message marketing platform matching customer personas to campaign angles before send, filtering unsuitable campaigns out ahead of dispatch.

2nd place (Social Impact): Todak Todak by SK Shieldus team
A real-time paediatric emergency service showing guardians which hospitals have a specialist and an available bed at that moment.

The Value That Carried Past the Hackathon

519 new enterprise accounts stayed in the APJ pipeline after the hackathon, each one attached to a team that had already deployed on the platform. Six winning teams hold Data + AI Summit 2027 passes and USD 3,000 each in training coupons, keeping active users on Databricks through the following year.

AngelHack was a genuine partner in delivering our 4th Annual APJ hackathon, and their marketing support was where they added the most value. They ran targeted outreach into our key accounts and tapped into local developer platforms across ANZ, ASEAN, India, Japan and Korea, extending our reach into audiences we don’t always get in front of. Running the program across three language tracks meant translating assets and copies into Japanese and Korean at real scale, and their teams carried a significant share of that load with us.

june tan

June Tan,
Senior Marketing Manager APJ, Databricks

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