MAD for Localization.
HACKATHON

Build the next useful localization prototype in 48 hours. 
A practical online hackathon where localization professionals define real-world problems, and builders turn them into working prototypes.

Bring Your Own Tools (B-Y-O-T)

24–26 June

Individuals or teams

What happens

1
Real localization challenges announced by top-tier localization leaders
2
Three focused build days for rapid prototype development
3
Public showcase and optional virtual-stage pitch for the opportunity to win prizes

3 Days of Creation

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June 24 · 15:30 Paris
  • Challenges announced
  • Watch the conference broadcast live
  • Start building
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June 25 · 14:50 Paris
  • Build your prototype
  • Use any AI-assisted development tool
  • Connect with professionals on Slack
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June 26 · 16:00 Paris
  • Submission deadline
  • One link or file per team
  • Optional 2-min pitch

The Rules of the Localization Hackathon

Challenges of the Hackathon

“Mind the Context” (Quality Pipeline)

Context-aware translation remains a largely unsolved problem in our industry, and one that becomes increasingly important as more content is translated with AI. In this challenge, build an app that validates the translation in-context, on top of it being linguistically accurate. Pick your definition of context: developer notes, UI screenshots and HTML, dialogue characters and their personality descriptions, a video with frames taken every 2 seconds, images of products in an e-commerce catalog, PDF blueprints with formulas, or even an audio stream.

 

You can think of the quality pipeline as a quick and low-latency step that happens before translations go live, or as a post-publishing corrective process.

 

By Melanie Heighway

In a world where new models become available every two weeks, some companies have opted to use all of them for their workflows. Different languages, tasks and content types require optimal models for characteristics like cost, latency, expected quality. Selecting new models has become so routine that it needs to be automated. Build a “Translation provider selection engine” that helps select the best MT provider. Requirements: 

 

  • Flexible: various business rules can be applied for decision-making
  • Automated: humans should only be involved when required
  • Explainable: decisions are motivated
  •  

Suggested by Nicolas Jadot, Trendyol

Build an app that reviews and scores multilingual websites for linguistic quality, terminology consistency, cultural adaptation and other criteria. It would ingest HTML web pages, look at them holistically and generate a report or dashboard that helps content groups determine what to improve. 

 

Advanced:

  • Allow for the sync between the strings parsed from the website directly and strings residing in the translation memory, so that the app may find the exact position of the text within the TMX and fix it.
  • Allow human review for proposed changes and an approval process

Suggested by Hyunjoo Han, Autodesk

A localization team is called upon to support multiple requests from various teams. Some are classic requirements such as file translation; others are more complex engineering jobs and involve checks across various tools, alignment between team members, or putting in place an entirely new workflow. The ask: build a planner/ticketing system tailored for localization and operating via a Slack bot that may support both the loc team and the stakeholders, including the requesters and the management. 

 

Requirements:

  • Flexible: can support an increasing number of use cases/request types automatically
  • Human in the loop: knows when to loop in a team member
  • Ease of use: stakeholders can interact with it directly and get useful answers
  •  

Suggested by Giulia Tarditi, Revolut

Who's Building

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Product Designers

Create beautiful, intuitive localization tool UX with practical wireframes and user experiences

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Localization Pros

Translate real-world pain points into actionable technical requirements and workflow insights

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Developers

Build functional prototypes using modern frameworks, APIs, and AI integration techniques

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AI Enthusiasts

Experiment with LLM APIs, prompt engineering, and innovative automation for localization tasks

Registered Teams & Individuals

Be the First one to register to the Localization Hackathon

Teams
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Amazon team
Natasha Kurysheva
Dee Savage
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Custom.MT team
Elena Murgolo
Daria Ryabinina
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Matched team
Estefania Tamayo-Pineda
Gary Hess
Marta Callava
Individuals
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Christian Lang
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Suzanne O'Connor kenny
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Rong Hu
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Siyanda Siwela
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Manikandan Munusamy
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Dinislam Zinnurov
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and 10 more...

Build with Guidance

This isn’t just a code sprint — you’ll have access to experienced senior developers for mentorship, technical guidance, and best-practice recommendations throughout the build process.

Register Interest

We’ll match you with a team before the event starts.

It’s a perfect opportunity to network and build together.