The DAMM x Engineering HUB Hackathon brings developers and data scientists together at Pier 01 Barcelona to tackle real-world industrial and commercial challenges using AI and Data Science.

🎯 The Challenges
  • LineWise (Operations): Optimize production line sequencing and OEE at the El Prat factory.

  • MarketPulse UK (International): Forecast international sales and simulate promotional impacts for the UK market.

  • SmartBuy (Purchasing): Build a market intelligence tool using external signals to guide raw material buying decisions.

⏰ Event Schedule
  • Saturday, May 23

  • 09:00 β€“ Challenge Presentation & Breakfast πŸ₯

  • 11:00 β€“ Hacking Begins πŸ’»

  • 13:00 & 15:00 β€“ AI Collective Tech Talks 🧠

  • 21:00 β€“ Dinner (Deleito Burgers) πŸ”

  • 00:00 β€“ Beer-Pong

  • Sunday, May 24

  • 09:30 β€“ Breakfast & Final Pitch Prep πŸš€

  • 11:00 - Submissions Deadline
  • 11:30 β€“ Project Demos & Presentations πŸ“Š

  • 13:45 β€“ Jury Deliberation βš–οΈ

  • 14:00 – Closing Ceremony & Awards πŸ†

Requirements

What to Build

A functional, end-to-end working data or AI prototype that solves one of the three Damm track challenges (LineWise, MarketPulse UK, or SmartBuy) with an interactive simulation UI.

What to Submit

A public code repository with clear execution instructions, a brief project description answering the submission form, and a link to a working demo or presentation video.

Hackathon Sponsors

Prizes

€3,100+ in prizes
+ other prizes
Best Cala Use
1 winner

200 $ in Cala credits for the best use of Cala

Winner MarketPulse Challenge
€700 in cash
1 winner

Winner LineWise Challenge
€700 in cash
1 winner

Winner SmartBuy Challenge
€700 in cash
1 winner

Overall DAMM x EHUB winner
€1,000 in cash
1 winner

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

LΓ­dia OcaΓ±a

LΓ­dia OcaΓ±a

Judging Criteria

  • Functional Execution
    Projects are evaluated on having a real, executable, end-to-end working flow over a broad but superficial concept.
  • Data-Driven Explainability
    Solutions must clearly justify their output: the tool needs to explain why a deviation occurred or why a specific recommendation is made using data, not just intuition.
  • Actionability & Simulation
    The project must allow user interaction to simulate real-world changes (e.g., urgent demand, promotions, market shifts) and output clear, decision-ready actions (e.g., specific line sequences, commercial levers, buy/hedge signals).
  • Data Integration & Innovation
    Evaluation of how effectively teams incorporate external data sources (e.g., news, macro signals, weather, scraping) and leverage modern tech like Generative AI to solve the problem.

Questions? Email the hackathon manager

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