🏆 Content Bounty: GraphRAG Inference Hackathon by TigerGraph

​TigerGraph is running the GraphRAG Inference Hackathon: a beginner-friendly online coding challenge where teams of 1-5 build a system that proves graph databases make LLMs cheaper and faster, with real benchmark numbers.

​The hackathon prize pool is $600 USD and the content bounty you're reading right now is separate, running alongside it.

Short Description: Create a short video explaining why GraphRAG makes LLMs faster, cheaper, and smarter and drive registrations for the GraphRAG Inference Hackathon by TigerGraph on Unstop.

Be creative, make the tech feel exciting and accessible, and build enough hype that viewers feel like they're missing out if they don't register.

Prizes (Content Bounty)

​Rank
🥇 1st: $40
🥈 2nd: $25
🥉 3rd: $15
🏆4th: $10
🏆5th: $10

Submission deadline: May 4, 2026

Deliverables

• ​One original short-form video (Instagram Reel or X video)

• ​Duration: Under 90 seconds

• ​Must mention or show TigerGraph / GraphRAG

• ​Include CTA to register: [Unstop link]

• ​Tag @TigerGraph and @thebuilder_base in your caption/tweet
  
  Resources

• ​Hackathon page: https://unstop.com/hackathons/graphrag-inference-hackathon-by-tigergraph-tigergraph-1678762

• ​TigerGraph GraphRAG docs: /tigergraph/graphrag

• ​TigerGraph: tigergraph.com

• ​Brand assets: https://drive.google.com/drive/folders/1Vi11tVCIpZ7degAmYZ3m-8eOvWvIpLkz
  
  Key Angles to Cover (Pick any of 2)

  • ​1. Set the context first: what even is GraphRAG? Most people have heard of RAG. Few know what's broken about it. Start here. Vector search finds similar text it dumps the whole neighborhood into context hoping the LLM figures it out. GraphRAG follows actual relationships in a knowledge graph it knows exactly which node to go to. Then bridge to why TigerGraph built this natively and why the hackathon is where you prove it with numbers.
    

  • ​2. Your RAG is wasting money Every complex query on standard RAG burns tokens it doesn't need to. At consumer scale that's annoying. At enterprise scale that's millions. GraphRAG is surgical feeds the LLM only the connected, relevant context. Show the difference. Make the cost angle visceral.

​Tone & Style

• ​Fast-paced, confident, curious

• ​Dev-Twitter / builder energy

• ​Hinglish, English, or regional language whatever feels natural to you

• ​Meme-aware but technically grounded

• ​Show, don't lecture

​Important Language Rules

• ​Do NOT use: gambling, betting, guaranteed returns, get rich

• ​Use instead: build, benchmark, inference, pipeline, tokens, latency, graph traversal, submission, deploy\

​Eligibility Requirements

• ​Must follow @TigerGraph and @thebuilder_base on X and/or Instagram

• ​Content must be original, human-made, and posted from your own account.

• ​Must have an active presence on X or Instagram