Rivalz is a layer 2 blockchain creating the World Abstraction Layer for AI and AI Agents. The Rivalz Network is a decentralized market of Data, AI, DePIN and Human resources. Rivalz bridges AI and Agents to the real world. In the Rivalz AI World Hackathon we invite you to build on top of 1.0 versions of our Data Storage/AI RAG solution (OCY DePIN) + our Agentic Data and AI Oracle Network (ADCS).
This hackathon invites new and existing projects to bring exciting AI project to life using our infrastructure via 3 main tracks: OCY, ADCS, AI Agents. And a special ai16z sub-track.
This is a global online hackathon where anyone can participate, additionally there will be a special offline track in Manila, Philippines with a separate prize pool.
After submission you'll be given a special link for private developer chat.
Apply to the offline track in Manila, Philippines by The Block - .
Total Prize Pool: $85,000. [50% USDT, 50% Rivalz Native Token $RIZ]
OCY - / - $20,000
This track will focus on Data Management and Usage for AI use cases.
ADCS - / - $20,000
This track will focus on creative DAPP or Agent design involving ADSC Oracles on-chain. Additionally, top creative Data and AI providers and Adapter creators will be rewarded.
AI Agents - - $45,000
General track for creation of AI Agents using OCY or ADCS. [$15,000]
Eliza Sub-tracks. For AI Agent developers using ai16z tech - Here you do not have to use any of our infra, although it will be a bonus if you do. For clarity: Rivalz is in no way associated with ai16z.
[$15,000] Most creative/valuable use-cases of long-term autonomous planning and execution, by AI Agents. Supply the Agent with any resources from access to services to money, and have them perform as long as possible towards the end goal.
[$15,000] Most creative/valuable use-cases of VMs or Web-access by AI Agents. AI Agent has full control over a virtual machine or just a web-browser.
Additional points for using Waking Up .
Week 1 (Nov 25 - 29):
Introduction to OCY and ADCS
Team formation
Weeks 2-3 (Dec 2 - Dec 13):
Partner Workshops
Business Talks
Weeks 4 (Dec 16 - Dec 20):
Check-in & Feedback
Weeks 7 (Deadline Dec 20th- 9 PM UTC):
Final Grant/Project Submission
The winner Announcement will take place within 2 weeks of the hackathon conclusion. Date TBA.
The GitHub repository, project description, and video presentation must all be submitted before the deadline. A link will be provided soon.
Participants must be 18+
The judging panel will primarily consist of the Rivalz Team, but we may also onboard additional judges during the hackathon. Stay tuned.
First part - Projects that have successfully submitted all the details will be screened. Top projects will be invited to second part.
Second part - Present your project on a video session with judges.
Projects will be selected based on merit of utility, creativity, depth of development, presentation.
Each track will have Gold, Silver, Bronze winners, with rewards worth 50%, 30%, 20% respectively of tracks reward pools.
Rewards will be allocated within 4 weeks of winners announcements.
Winners will be provided with additional support in Resources, Marketing, Funding, Business and more. All participants will have a fast track for our incubator program -. For existing projects in the AI/Agentic fields we suggest to apply now.
Description: Build an Agent that allows users to supply additional information for its knowledge base on-chain, with an open-source directory and time-stamps for different data added to the knowledge base. Additional points for AI-driven data categorisation.
Autonomous Research Agent
Description: Develop AI agents that autonomously retrieve, analyze, and summarize academic research or news articles on specific topics using OCY's RAG capabilities. Additional points, if your Agent understands what data it already has, doesn’t double store, categorises information found from a research point of view and does cycles of goal re-evaluation based on the knowledge found.
Evolving-RAG Agent
Description: Create and Agent that interact with users to requesting additional material. Then it adjusts its own knowledge through this material. Interesting possibilities can come from the side of directly allowing new information to twist the personality of the agent.
Description: Create agents that analyze user data, assess its value (e.g., insights from usage patterns or preferences), and automatically tokenize the data into tradable assets on Arbitrum or Base. Use Case: Enable users to monetize their data while maintaining ownership, creating a decentralized data marketplace.
Description: Create agents that manage decentralized data cooperatives, where contributors pool their data and earn collective rewards through smart contract-governed profit-sharing. Use Case: Empower communities to monetize shared data for social or economic benefits.
Side-note: Creative Data/AI Providers and unique Adapter creators will be rewarded separately.
Isolated agentic economies where each user controls their own Agent There is an extremely interesting use-case for agentic pvp, this could be in any vertical, but we will provide a few examples.
Isolated trading - There is a token, but only agents are allowed to trade it, say to participate each user needs to launch their own agent and add specification to how it acts. Then at certain event intervals agents access the oracle to make ai-driven decisions on how to act.
Isolated gamefi - Real users only setup the initial parameters of agents, then let them pvp with each other again requesting adcs for decision making.
Description: Agents provide real-time AI services (e.g., analytics, recommendations) on a subscription basis, with payments handled automatically via recurring Arbitrum/Base smart contracts. Use Case: Enterprises or individuals pay only for the AI insights they use, reducing upfront costs.
Description: Agents that mediate data sharing by encrypting and tokenizing user data, enabling secure and private transactions via Abritrum/Base smart contracts. Use Case: Protect user privacy while allowing controlled data sharing for AI applications.
Alternatively, you can create a tornado.cash type product by creating a mother agent SC and having users deploy their own pre-built SC as agents to where end state offload is managed by the mother agent and all TXs are handled by agents off-chain.
Description: Smart contract-powered bounties incentivize AI agents to retrieve and process data for specific research tasks. Rewards are issued when the task is verified as complete and valuable. Use Case: Universities, startups, or think tanks seeking decentralized AI research capabilities.
Any Agents using ADCS or OCY.
ai16z Eliza sub-tracks - We are specifically interested in Agents:
Utilizing more mediums, from full access to devices to Virtual Machines / to WebOS
Having larger degrees of freedom, think outside of the box
With long-term reasoning/planning/action
That leverages SWARMS, such as this
Most importantly, make something interesting and exciting.