2nd OpenCoffee Cyprus 04/07/2012 - Fashinating
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This document discusses a new online shopping platform called Fashinating. [1] It aggregates fashion items from 60 online shops, both Greek and international. [2] Fashinating generates revenue through affiliate sales, plugins on fashion sites, and market research contracts with fashion houses. [3] The platform currently features over 130,000 items, receives 100,000 monthly visits, and has secured funding and partnerships to continue expanding its catalog of brands and shopping options.
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Salesforce Summer '25 Release Frenchgathering.pptx.pdf"Scaling in space and time with Temporal", Andriy Lupa.pdf
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Design patterns like Event Sourcing and Event Streaming have long become standards for building real-time analytics systems. However, when the system load becomes nonlinear with fast and often unpredictable spikes, it's crucial to respond quickly in order not to lose real-time operating itself.
In this talk, Ill share my experience implementing and using a tool like Temporal.io. We'll explore the evolution of our system for maintaining real-time report generation and discuss how we use Temporal both for short-lived pipelines and long-running background tasks.OpenACC and Open Hackathons Monthly Highlights June 2025
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The OpenACC organization focuses on enhancing parallel computing skills and advancing interoperability in scientific applications through hackathons and training. The upcoming 2025 Open Accelerated Computing Summit (OACS) aims to explore the convergence of AI and HPC in scientific computing and foster knowledge sharing. This year's OACS welcomes talk submissions from a variety of topics, from Using Standard Language Parallelism to Computer Vision Applications. The document also highlights several open hackathons, a call to apply for NVIDIA Academic Grant Program and resources for optimizing scientific applications using OpenACC directives.Security Tips for Enterprise Azure Solutions
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Delivering solutions to Azure may involve a variety of architecture patterns involving your applications, APIs data and associated Azure resources that comprise the solution. This session will use reference architectures to illustrate the security considerations to protect your Azure resources and data, how to achieve Zero Trust, and why it matters. Topics covered will include specific security recommendations for types Azure resources and related network security practices. The goal is to give you a breadth of understanding as to typical security requirements to meet compliance and security controls in an enterprise solution.Mastering AI Workflows with FME by Mark Doring
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Harness the full potential of AI with FME: From creating high-quality training data to optimizing models and utilizing results, FME supports every step of your AI workflow. Seamlessly integrate a wide range of models, including those for data enhancement, forecasting, image and object recognition, and large language models. Customize AI models to meet your exact needs with FMEs powerful tools for training, optimization, and seamless integrationOh, the Possibilities - Balancing Innovation and Risk with Generative AI.pdf
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Oh, the Possibilities - Balancing Innovation and Risk with Generative AISmarter Aviation Data Management: Lessons from Swedavia Airports and Sweco
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Managing airport and airspace data is no small task, especially when youre expected to deliver it in AIXM format without spending a fortune on specialized tools. But what if there was a smarter, more affordable way?
Join us for a behind-the-scenes look at how Sweco partnered with Swedavia, the Swedish airport operator, to solve this challenge using FME and Esri.
Learn how they built automated workflows to manage periodic updates, merge airspace data, and support data extracts all while meeting strict government reporting requirements to the Civil Aviation Administration of Sweden.
Even better? Swedavia built custom services and applications that use the FME Flow REST API to trigger jobs and retrieve results streamlining tasks like securing the quality of new surveyor data, creating permdelta and baseline representations in the AIS schema, and generating AIXM extracts from their AIS data.
To conclude, FME expert Dean Hintz will walk through a GeoBorders reading workflow and highlight recent enhancements to FMEs AIXM (Aeronautical Information Exchange Model) processing and interpretation capabilities.
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A presentation at Internetware 2025.Raman Bhaumik - Passionate Tech Enthusiast
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A Junior Software Developer with a flair for innovation, Raman Bhaumik excels in delivering scalable web solutions. With three years of experience and a solid foundation in Java, Python, JavaScript, and SQL, she has streamlined task tracking by 20% and improved application stability.Curietech AI in action - Accelerate MuleSoft development
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CurieTech AI in Action Accelerate MuleSoft Development
Overview:
This presentation demonstrates how CurieTech AIs purpose-built agents empower MuleSoft developers to create integration workflows faster, more accurately, and with less manual effort
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meetups.mulesoft.com
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Key Highlights:
Dedicated AI agents for every stage: Coding, Testing (MUnit), Documentation, Code Review, and Migration
curietech.ai
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curietech.ai
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medium.com
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DataWeave automation: Generate mappings from tables or samples95%+ complete within minutes
linkedin.com
+7
curietech.ai
+7
medium.com
+7
Integration flow generation: Auto-create Mule flows based on specificationsspeeds up boilerplate development
curietech.ai
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medium.com
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Efficient code reviews: Gain intelligent feedback on flows, patterns, and error handling
youtube.com
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curietech.ai
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curietech.ai
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Test & documentation automation: Auto-generate MUnit test cases, sample data, and detailed docs from code
curietech.ai
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curietech.ai
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medium.com
+5
Why Now?
Achieve 10 productivity gains, slashing development time from hours to minutes
curietech.ai
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curietech.ai
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medium.com
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Maintain high accuracy with code quality matching or exceeding manual efforts
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Ideal for developers, architects, and teams wanting to scale MuleSoft projects with AI efficiency
Conclusion:
CurieTech AI transforms MuleSoft development into an AI-accelerated workflowletting you focus on innovation, not repetition.Ad
2nd OpenCoffee Cyprus 04/07/2012 - Fashinating
- 1. A new way to shop MaryLou Tzempelikou Open Coffee Cyprus July 4th, 2012
- 2. Petros MaryLou Alex
- 3. Do you feel like that when you go shopping?
- 4. refer that? Do yo up
- 6. T need he
- 10. T Idea he
- 11. Sources of revenue 1. Affiliate Sales
- 12. Sources of revenue 2. Plugin on fashion sites
- 16. Sources of revenue 3. Market research for fashion houses
- 17. So far
- 18. ff the grid
- 19. Fashinating in numbers (today) 130.000 items from 60 eshops (40 Greek) 100.000 visits/month 95.000 euro funding 5.000+ fashion brands 250+ agreements with Greek & international eshops 6 co-branding solutions (Microsoft, Star.gr, Men s Health, Liberis etc) 5 contracts with fashion houses 3 versions (Greek, UK & international) 1 Patent pending (USA)
- 20. What have I learned (so far)? 凌留亮凌旅虜侶留 裡僚竜粒留溜留 僚侶亮劉侶 旅留凌竜旅虜侶留 離!!!!!!!!!! Feedback 留 溜凌 Stay focused! 旅 僚凌 裡僚隆留旅虜流 虜劉侶 留了 亮
- 22. Thank you! contact@fashinating.com Facebook.com/Fashinatingcom Twitter: @Fashinating Flickr: Fashinating YouTube: FashinatingChannel
Editor's Notes
- #2: Hi , I am the founder and CEO of Fashinating.com and I would like thank the organizers for the opportunity. Fashinating is, simply, a new way to shop fashion products Our users have added, to this date our users, over 5M products to their favorites.
- #3: We are a team of three founders with diverse backgrounds ranging from technology, to business and fashion. All team members were lucky to have worked on great organizations with international reach.
- #9: This is our solution. Fashinating brings thousands of fashion products from the best e-shops, in one place. The user views just 3 products, clicks on the products she likes, builds her profile and our algorithm presents her with more products according to her style. We are the only company in the world that uses this process and we have a pending US patent for it.
- #19: As I said earlier innovation requires experimentation. Our competitive advantage is the quality of our recommendations algorithm. On this graph you can see how many of our users like a product that we recommend them over time. What does this mean? It means that experimenting on the Greek market has given a mature product that is now ready to be exported to the world. This defiantly gives us a head start to any possible imitator abroad.