Market thesis
Why early on-chain intelligence is becoming a core edge for crypto-native capital.
Review the thesis, system design, token utility, and execution plan that shape the Valerian ecosystem.
Why early on-chain intelligence is becoming a core edge for crypto-native capital.
How discovery, analytics, scoring, and operator workflows fit into one platform.
The role of staking, premium access, and governance in the network design.
Milestones that move the platform from launch experience to institutional product depth.
VALDATA is structured to support distribution, user activation, participation incentives, and operating capacity from day one. The model places 60% of total supply into sale while keeping focused allocations for development, marketing, airdrops, treasury, and staking.
100B
VALDATA
Public sale
60,000,000,000 VALDATA are allocated to sale, creating broad initial distribution and a commercially strong launch profile on BSC.
Project
Valerian Data
Network
BSC
Symbol
VALDATA
Total supply
100,000,000,000
Supply for sale
60,000,000,000
VALDATA
The allocation balances commercial reach, user retention, and execution capacity without overloading internal buckets.
Public sale
60%
Sale
Core distribution reserved for launch and broad market participation.
Developers
Allocated to product delivery, maintenance, and technical execution.
Marketing
Reserved for brand growth, campaigns, and ecosystem visibility.
Airdrop
Focused on activation, community acquisition, and early user growth.
Treasury
Supports strategic reserves, operations, and ecosystem flexibility.
Staking
Dedicated to incentive design and long-term participation.
Valerian sequences data foundations, alpha models, product launch, monetization, multi-chain expansion, advanced AI, and institutional delivery, with critical platform work running in parallel.
Data & Infrastructure
Implement the incremental contract detection pipeline on BSC.
Develop the early token detection engine.
Build the historical token feature store.
Implement the automated labeling system for risk, liquidity, and growth.
Normalize data for a multi-chain architecture.
Implement data versioning and auditability.
Initial Analytics
Implement the alpha analytics and machine learning model.
Develop the alpha portfolio simulation model for 6 cryptoassets.
Implement the backtesting engine with walk-forward validation.
Define robust evaluation metrics without overfitting.
Publish the alpha portfolio model for 6 cryptoassets.
Functional Launch
Launch the Valerian platform as a functional MVP.
Develop the executive dashboard for predictions, rankings, and signals.
Implement the authentication system for login and user management.
Implement access control for free vs premium tiers.
Integrate legal disclaimers and terms of use.
Design the utility of the VALDATA token within the ecosystem.
Implement the SaaS subscription system.
Integrate Web3 payments with wallet connect and web3 payments.
Launch the VALDATA token presale.
Implement the tracking model for the ETH network.
Integrate new networks including Polygon, Arbitrum, and other relevant chains.
Develop the unified multi-chain engine.
Normalize and consolidate cross-chain data.
AI / ML / DL
Develop the alpha portfolio model for 20 cryptoassets.
Implement ML, DL, and AI models for forecasting 26 assets.
Develop ensemble models and meta-models.
Implement meta-labeling and advanced classification models.
Model volatility and market regimes.
Implement automatic model recalibration.
Scale monitoring coverage to 90% of relevant blockchain networks.
Implement real-time processing with per-minute streaming.
Develop the early alert system.
Implement a global ranking of investment opportunities.
Integrate traditional assets including equities, commodities, and indices.
Develop multi-asset predictive models.
Implement cross-market correlation analysis.
Develop hybrid strategies across crypto and traditional assets.
Develop advanced market metrics.
Implement advanced model statistics for enterprise mode.
Develop the commercial API for third parties.
Implement white-label dashboards.
Integrate with institutional clients including funds, exchanges, and companies.
Runs in parallel
These milestones are not sequential and progress throughout the roadmap.
Implement MLOps for training and automatic retraining.
Monitor model drift and performance.
Optimize system latency and performance.
Implement advanced security and access control.
Drive community strategy across Telegram, X, and adoption channels.
Implement logging and traceability.
Maintain global legal and regulatory compliance.