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Official Partner
Agenda I Europe Tech Hackathon
Thursday I Kick-off, Ideation, Team building
16:00: Official Kick-off I Hackathon Introduction
17:15: Workshops I tailored to each challenge with our incredible mentors
18:00: Begin hacking I mentoring sessions
Find and book your mentors via our website or Slack - available until 21:00
18:30 Delicious finger food
Work Open End: Feel free to overnight at the venue
Friday I Full Day Working
8.00 Space opens I 9.00 Breakfast
10.00 to 14.00 Mentoring from 15+ Mentors
11.00 to 14.00 Lunch I Foyer 2 (other entrance)
14.00 to 18.00 HR Corner - Programm here
19.00 Pizza Party
Open End Working
Saturday I Finalize your Project & Pitch
10.00 to 12.00 Pitch Training I Pre-Selection of pitching projects
13.30 to 15.30 Pitch Session I Start 14.00 Pitching
Jury Gernot Singer (Investor), Michael Kolb (Vorstand Acredia Versicherung), Alexander Penev (CEO Bytesource), Jan Juriga (Wirtschaftsagentur Wien), Josip Grubesic (Google), Kati Schneeberger (BEJ)
16.00 Award Ceremony & Media corner
17.00 End & Afterparty at Festivallounge Karlsplatz
What is a hackathon?
A hackathon is a collaborative event where programmers, designers, and entrepreneurs come together to develop software or hardware projects, often within a tight timeframe, to solve specific challenges or create innovative solutions.
The Europe Tech Hackathon, organized by Sustainista, stands out as the premier event by emphasizing sustainability in tech, attracting top-tier talent passionate about creating impactful, eco-conscious technologies.
This hackathon offers a unique platform for cross-disciplinary collaboration, access to cutting-edge resources, and mentorship from industry leaders, fostering an environment where groundbreaking green solutions are born.
Don’t hesitate. Click here to register for the Europe Tech Hackathon! Spots are limited!
The Challenges
Challenge 1: Combating Political Fake News with AI
In the digital age, political misinformation and fake news have become rampant, influencing public opinion and potentially swaying election outcomes. The challenge is to develop an AI-powered solution to detect and mitigate the spread of fake news related to politics.
Challenge 2 : Uncovering New Business Horizons with AI
Unlocking new business opportunities amid economic fluctuations remains a formidable challenge for trade credit insurance entities like Acredia Versicherung GmbH. The objective is to harness AI's power to identify potential new clients through the analysis of current news and events, enabling risk-aware decision-making and exploration of business avenues.
Challenge 3: ESG Insight AI Accelerator including mobility recommendations
The goal is to develop an AI-based software that automates the analysis of annual financial statements, extracting and evaluating ESG data to provide a clearer picture of corporate sustainability, with a particular focus on the European context. Moreover, sustainable and smart mobility solutions should be proposed to the analyzed companies.
The Challenges in detail
Don’t hesitate. Click here to register for the Europe Tech Hackathon! Spots are limited!
Challenge 1: Combating Political Fake News with AI
Title: AI Warriors Against Political Misinformation
Background: In the digital age, political misinformation and fake news have become rampant, influencing public opinion and potentially swaying election outcomes. The challenge is to develop an AI-powered solution to detect and mitigate the spread of fake news related to politics.
Goal: Create an innovative AI model that identifies, analyzes, and classifies political news content as legitimate or fake with high accuracy. The solution should incorporate real-time detection capabilities and be scalable across various digital platforms.
Challenge Statement: Participants are tasked with developing an AI system capable of discerning the veracity of political news stories, tweets, and other forms of digital content. The system should help social media platforms, news agencies, and end-users proactively combat the dissemination of false information.
Data Set: Participants will be provided with a dataset that includes a range of political news articles, social media posts, and fact-check verifications from reliable sources to train their models.
Expected Deliverables:
An AI algorithm/model for detecting fake political news.
A proof-of-concept application demonstrating the model's capabilities.
Documentation outlining the approach, methodologies, and technologies used.
An analysis of the model's accuracy, including testing results with precision, recall, and confusion matrix metrics.
A presentation or pitch explaining the solution's functionality and potential impact.
Criteria for Evaluation:
Accuracy and reliability of the fake news detection model.
Innovation in approach and use of AI techniques (e.g., NLP, machine learning, deep learning).
Quality of the user interface and experience for the proof-of-concept application (if applicable).
Scalability and integration potential with existing digital platforms.
Depth of analysis and insights gathered from the model’s performance.
Quality and clarity of documentation and presentation.
Resources: Participants will have access to:
A curated dataset with labeled examples of political fake and real news.
A set of APIs for integration with social media platforms for real-time data fetching (where applicable).
Computing resources such as cloud credits for training complex models.
Challenge 2 : Uncovering New Business Horizons with AI
Title: AI Trailblazers for Business Opportunity Insights
Background: Unlocking new business opportunities amid economic fluctuations remains a formidable challenge for trade credit insurance entities like Acredia Versicherung GmbH. The objective is to harness AI's power to identify potential new clients through the analysis of current news and events, enabling risk-aware decision-making and exploration of business avenues.
Goal: Develop an AI-driven analytics tool tailored for Acredia Versicherung GmbH that pinpoints potential new business customers requiring trade credit insurance based on the analysis of news feeds, market trends, and economic indicators within Austria, Slovenia, and Croatia.
Challenge Statement: Participants are tasked with creating a sophisticated AI application that crawls, interprets, and extracts actionable business insights from the deluge of news and financial data. This application should lead to identifying companies likely to benefit from Acredia's services, specifically targeting commercial clients and public-law institutions operating on open account principles.
Data Set: Participants will use a collection of data sources, including news articles, financial reports, and industry-specific databases, to train and validate their models.
Expected Deliverables:
An AI algorithm/model that screens news and financial data to identify potential Acredia clients.
A user-friendly dashboard prototype offering real-time analytics to assist marketing and sales teams in strategic decision-making.
Documentation detailing algorithmic approach, data handling, user interface design, and integration with existing systems.
A presentation illustrating the tool’s function, compliance with data protection laws, and value addition to Acredia’s business model.
Criteria for Evaluation:
Relevance and effectiveness of the AI model in identifying potential leads for Acredia.
Applied sophistication in NLP and machine learning to distill insights from extensive datasets.
Practicality and accessibility of the dashboard for non-technical users.
Ability to integrate seamlessly with Acredia's IT infrastructure while adhering to high data protection and privacy standards.
Thoroughness of the documentation and clarity in the final presentation connecting application benefits to Acredia’s operational goals.
Resources: Participants will have access to:
A compilation of datasets relevant to Acredia’s target demographics and service scope.
Tools and frameworks for AI development, including NLP and machine learning libraries.
Access to Acredia’s IT infrastructure for integration testing (subject to restrictions).
Prizes:
1st Place: Contract opportunity to deploy the solution within Acredia, a monetary reward, and showcase at industry events.
Challenge 3: ESG Insight AI Accelerator including mobility recommendations
Background: In the face of climate change and the increasing demand for corporate accountability, efficiently evaluating the sustainability information disclosed in annual reports is becoming an urgent need. The challenge is to create an AI-supported tool that can parse through complex data and pinpoint ESG metrics, particularly greenhouse gas emissions, in order to highlight unsustainable practices and enhance the decision-making process for investors and policymakers.
Objective: The goal is to develop an AI-based software that automates the analysis of annual financial statements, extracting and evaluating ESG data to provide a clearer picture of corporate sustainability, with a particular focus on the European context. Moreover, sustainable and smart mobility solutions should be proposed to the analyzed companies.
Challenge Statement: Participants are challenged to conceive an AI system that not only extracts precise ESG-related data but also verifies and evaluates it against sustainability benchmarks. The system should feature an intuitive user interface allowing diverse user groups to efficiently categorize and assess ESG criteria, with the long-term adaptability to handle growing data volumes.
Data Set: Participants will work with a collection of sample annual reports, ESG reports, and relevant CSV files containing sustainability data from European companies.
Expected Deliverables:
A working prototype for analyzing financial statements and identifying key ESG metrics.
Documentation of AI and ML methodologies, algorithmic processes, and technological implementation details.
A functional user interface designed for diverse target audience needs.
A scalability and development roadmap, offering a vision for further software advancement.
A pitch presentation outlining potential applications, long-term vision, and the tool’s contribution to sustainable business practices.
Criteria for Evaluation:
The accuracy and precision of ESG data extraction, with a focus on greenhouse gas emissions.
The robustness of data verification and sustainability evaluation mechanism implemented.
The usability and functionality of the user interface for different stakeholders.
The ability of the software tool to manage large data sets and incorporate new data effectively.
Consideration of ethical data use and compliance with European data protection standards.
The depth of documentation and clarity of the pitch, including demonstration of potential use cases for the software.
Resources: Participants will have access to:
A curated set of financial and ESG reports from European companies in various industry sectors.
A software development kit (SDK) with AI and ML frameworks tailored for data analysis.
A virtual environment replicating European data protection compliance requirements.