{"id":30560,"date":"2025-11-17T00:29:15","date_gmt":"2025-11-17T08:29:15","guid":{"rendered":"https:\/\/www.pingcap.com\/?p=30560"},"modified":"2025-11-19T07:24:25","modified_gmt":"2025-11-19T15:24:25","slug":"tidb-agentx-hackathon-2025-recap","status":"publish","type":"post","link":"https:\/\/www.pingcap.com\/ko\/blog\/tidb-agentx-hackathon-2025-recap\/","title":{"rendered":"TiDB AgentX Hackathon 2025 Recap: Double the Submissions, Real-World AI on Display"},"content":{"rendered":"

The results are in, and they are spectacular. When we challenged the community to move beyond simple RAG demos, we never imagined the sheer ingenuity we’d see. With 219 incredible submissions, the AgentX Hackathon 2025 proved one thing: the era of sophisticated, multi-step AI agents is here<\/strong>.<\/p>\n\n\n\n

<\/span>A New Chapter for TiDB Hackathons<\/span><\/h2>\n\n\n\n

Last year’s hackathon<\/a> introduced developers to vector search<\/a> on TiDB Cloud Serverless<\/a> (now called TiDB Cloud Starter). This year, we challenged participants to build systems that think, decide, and act across multiple steps. The theme “Forge Agentic AI for Real-World Impact” pushed developers to orchestrate complex workflows combining vector search, full-text search<\/a>, Model Context Protocol<\/a>, LLM reasoning<\/a>, and external integrations.<\/p>\n\n\n\n

The shift from single-step retrieval to multi-agent coordination represents a fundamental evolution in how developers approach AI applications.<\/p>\n\n\n\n

<\/span>Celebrating Our Winners<\/span><\/h2>\n\n\n\n

We had a ton of amazing projects, but these five really stood out. The judges picked them because they didn’t just build something cool, they actually solved real problems. Let me show you what made them special.<\/p>\n\n\n\n

\ud83e\udd47 First Place: PetFit AI<\/h3>\n\n\n
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Born from a personal crisis when a young cat broke his leg with no vet available, PetFit AI transforms pet healthcare through multi-agent orchestration. The system ingests real-time collar data via Kafka, stores it in TiDB with TTL configuration, and deploys specialized agents for symptom analysis, audio interpretation, skin disease detection, and vitals monitoring. The central orchestrator coordinates these agents to provide comprehensive pet health insights, demonstrating exactly what we envisioned for agentic AI.<\/p>\n\n\n\n

\ud83e\udd48 Second Place: EduPath<\/h3>\n\n\n
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A law student turned CS applicant who spent thousands on consultants built the solution he wished existed. EduPath uses TiDB vector search across 100 universities to match students with target, reach, and safe schools through natural conversation. The AI extracts profile data seamlessly, generates personalized timelines, and democratizes expensive graduate school guidance. This solution proves agentic AI can make professional services accessible to everyone.<\/p>\n\n\n\n

\ud83e\udd49 Third Place: AutoIR<\/h3>\n\n\n
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AutoIR turns noisy AWS logs into explainable incident reports. The system embeds CloudWatch logs, performs semantic search in TiDB, and uses an LLM orchestrator with safety guardrails (SELECT-only queries, enforced LIMITs) to generate incident summaries with evidence. With sub-2-second end-to-end performance and production-grade deduplication logic, AutoIR showcases how careful architecture makes agentic systems reliable.<\/p>\n\n\n\n

Additional Winners<\/h3>\n\n\n\n

\ud83c\udfc5 4th Place – Heydesk<\/strong>: A solo developer built both a customer support platform and the first .NET SDK for TiDB Vector Search, TiDB Vector & .NET, demonstrating remarkable technical ambition.<\/p>\n\n\n\n

\ud83c\udfc5 5th Place – AI Member of Parliament<\/strong>: Event-driven agentic system for civic engagement, automating case handling workflows inspired by Singapore’s Meet-the-People Sessions.<\/p>\n\n\n\n

\ud83c\udf1f Best Social Good – FamCare<\/strong>: Healthcare management for aging families, combining vector search for medical documents with external APIs (OpenFDA, RxTerms) for comprehensive care coordination.<\/p>\n\n\n\n

\ud83c\udfc6 Best Open Source – ElitOrcAI<\/strong>: Clinical decision support chaining medical image analysis, vector similarity search, and structured diagnostic guidance for healthcare professionals.<\/p>\n\n\n\n

<\/span>Three Key Trends That Defined the Winners<\/span><\/h2>\n\n\n\n

Three key patterns emerged across the 219 submissions:<\/p>\n\n\n\n