# Product Roadmap Real-time, agent-native data infrastructure — from proving the mechanism to powering every AI vertical. This roadmap tracks shipped milestones and planned milestones. Green-check items are complete. Everything else is still in progress or upcoming. *** #### Phase 0: Foundation & Proving the Mechanism **Status:** Complete\ **Timing:** Q4 2025 Built and shipped the protocol, launched the token, and proved that Reppo's prediction-market incentive mechanism works on mainnet. * [x] Designed Datanet architecture — stake-assured prediction markets, commit-reveal voting, 48-hour epoch-based curation cycles * [x] Shipped core protocol with live Datanets, $REPPO staking, and on-chain emission distribution * [x] Token launch and mainnet deployment — staking, voting power, and base governance live * [x] Proved the incentive mechanism works — live network stats at reppostats.com * [x] Onboarded first cohort of publishers and voters across multiple data verticals * [x] Validated core economic loop — publishing fees, voter rewards, and Datanet owner revenue capture working end-to-end *** #### Phase 1: Open the Floodgates **Status:** Building now\ **Timing:** Q1–Q2 2026\ **Progress:** 8 of 12 milestones complete The mechanism is proven. Now it's permissionless. Anyone can launch a Datanet, own it as an NFT, set their own economics, and start earning. * [x] Ship permissionless Datanet creation with NFT-based ownership * [x] Upgraded voting mechanics — net voting (positive/negative), linear decay rewarding early conviction * [x] Open emission seeding — any token can fund a Datanet's incentive pool (15% tax on non-REPPO creates structural buy pressure) * [x] Bribing mechanism — external capital can back Datanets in exchange for fee share * [x] Launch Data Exchange — the marketplace where AI teams subscribe to continuously updating curated datasets * [x] MiCA-compliant whitepaper published * [x] 50M+ $REPPO locked across the network * [x] 9 Datanets live across multiple data verticals * [ ] 500M $REPPO locked across the network * [ ] 15+ Datanets live — expanding domain coverage * [ ] Datanet staking mechanism — stake $REPPO on individual Datanets to earn a share of their fees * [ ] Centralized exchange listings — expanding $REPPO access and liquidity *** #### Phase 2: Scale the Economy **Status:** Upcoming\ **Timing:** Q3–Q4 2026 Grow from dozens of Datanets to hundreds. Prove that the data exchange model generates real, recurring revenue at scale. * [ ] 100+ active Datanets across 5+ verticals — finance, healthcare, robotics, code, enterprise knowledge * [ ] Network EVOF above 70% — quantitative proof that market-curated data outperforms legacy annotation * [ ] 1,000+ agentic subscribers consuming live data feeds through Data Exchange * [ ] Cross-Datanet composability — combine curated datasets across domains for multimodal training pipelines * [ ] $1M+ in cumulative subscription revenue flowing through the protocol *** #### Phase 3: Real-Time Infrastructure for Autonomous AI **Status:** Upcoming\ **Timing:** 2027 and beyond Annotation shops collect, label, and ship — sequentially. Reppo does it simultaneously. Data flows in, gets curated by staked voters, and updates live datasets every epoch with zero lag. Phase 3 adds inference so agents can discover data, provision compute, and train — all inside one protocol built for machines that can't wait. * [ ] 1,000+ active Datanets across every AI vertical * [ ] Inference on the Data Exchange — agents discover, provision, and train without leaving the protocol * [ ] Infrastructure Exchange — compute, storage, and data unified under one token * [ ] Zero-lag pipelines powering autonomous agents with continuously updating reward signals * [ ] Network EVOF consistently above 90% * [ ] $10M+ in cumulative protocol revenue — real demand, not speculation * [ ] Fully autonomous governance — community-led upgrades, fee policy, and emission schedules --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://reppo-labs-xyz.gitbook.io/reppo-labs/roadmap/product-roadmap.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.