Building a better tomorrow with AI: Takeaways from the Forge the Future hackathon

A strong grasp of the challenge and a well-matched tech stack played to each problem's needs. These teams didn’t just use powerful tools — they made them work together. Their winning solutions combined the strengths of multiple platforms, showing how well-aligned tech choices can lead to smarter outcomes. 

Their submissions were assessed by a panel of judges comprising:

• Shay Banon, Founder and CTO, Elastic
• Hock Chuan Lim, Deputy Director, Product Management, AI Products, xDigital, HTX (Home Team Science & Technology Agency)
• Laurence Liew, Director AI Innovation, AI Singapore
• Anil Nallamotu, Head of Global Strategic Partners Solution Architecture, APJ, AWS

Let’s take a closer look at how each of the top three teams turned their big ideas and smart tools into standout solutions.

Team Buckle Up 4 AI developed the Financial Insights Accelerator, a powerful tool designed to transform complex financial data into actionable insights. Powered by Elasticsearch RAG, Claude 3.7, DeepSeek R1, and Grok 3 (codename Goose), this tool redefines earnings analysis by highlighting key information, enabling deeper follow-up and helping teams make quicker, smarter decisions. Using Elastic’s recent earnings call transcripts and publicly available data, Team Buckle Up 4 AI showcased a demo of their generative AI solution replying to queries about Elastic’s financial performance.

Team Squareshift introduced an AI-powered health companion designed to make medical decision-making clearer and more proactive. Using Elasticsearch and Amazon Bedrock, the tool analyzes uploaded health reports, connects them with historical patterns, predicts potential risks, and highlights key trends. Users can visualize results, share insights with doctors, and take early action — all with the goal of living healthier and staying one step ahead.

Built by the Singtel Code Crew, Dr. HowsER is an AI-powered at-home emergency care companion designed to deliver personalized health recommendations and actionable advice. Mimicking the flow of a natural doctor-patient conversation, the system integrates IoT data, Elasticsearch, and Amazon Bedrock to provide real-time insights. By offering timely, tailored responses, Dr. HowsER helps users navigate health concerns confidently — reducing the anxiety that often comes with self-diagnosis.

GenAI will remain a prominent topic in Singapore as organizations transition from pilot projects to real-world technology applications. The country has expressed its goal to become a Smart Nation and lead innovation in AI. In the 2025 budget, the government committed up to S$150 million for a new Enterprise Compute Initiative to help companies adopt artificial intelligence and to provide access to artificial intelligence tools and computing power. There will also be a S$3 billion top-up to the National Productivity Fund that is expected to help Singapore compete in new frontier areas, including artificial intelligence and quantum computing. 

As innovation continues, search will be essential for powering GenAI with accurate, relevant data at the right time. Advanced search capabilities like vector search can deliver results based on the underlying meaning of the query, which can include images, video, audio, or text instead of keywords. Other techniques like retrieval augmented generation (RAG) enable organizations to search proprietary data sources and provide context that grounds general output from large language models (LLMs) for more accurate, real-time responses. With LLMs being AI models trained on massive amounts of data to enable them to understand and generate natural language responses, RAG enhances the accuracy and reliability of such models with information retrieved from relevant data sources that are outside their training data sources. 

When equipped with these search capabilities, organizations can make full use of their proprietary, highly contextual data, unlocking GenAI’s potential. 

Learn more about how AI fuels innovation at Elastic.

The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.

In this blog post, we may have used or referred to third party generative AI tools, which are owned and operated by their respective owners. Elastic does not have any control over the third party tools and we have no responsibility or liability for their content, operation or use, nor for any loss or damage that may arise from your use of such tools. Please exercise caution when using AI tools with personal, sensitive or confidential information. Any data you submit may be used for AI training or other purposes. There is no guarantee that information you provide will be kept secure or confidential. You should familiarize yourself with the privacy practices and terms of use of any generative AI tools prior to use. 

Elastic, Elasticsearch, ESRE, Elasticsearch Relevance Engine and associated marks are trademarks, logos or registered trademarks of Elasticsearch N.V. in the United States and other countries. All other company and product names are trademarks, logos or registered trademarks of their respective owners.