Chainbase services multiple user groups:
• Wallets & Exchanges — instant balance, token, and activity lookups; user portfolio aggregation.
• NFT Marketplaces — ownership history, trait aggregation, price calculations, floor analytics.
• DeFi dashboards & risk monitors — real-time position health and protocol exposures.
• Analytics/hedge funds — low-latency SQL for strategy backtests and signal production.
• AI agents & LLMs — feature-rich labeled datasets for decision-making and summarization.  
Real-world examples: a wallet could use Chainbase to show a user their multi-chain holdings in one UI with accurate history; a quant team could backtest a liquidation-strategy using Chainbase’s SQL API; an LLM agent could ingest labeled on-chain signals to surface insights like “this wallet is an OTC desk” or “this NFT collection shows increasing whale accumulation.” These are practical improvements over roll-your-own indexing.  
Chainbase’s emphasis on dataset labels and AI friendliness gives it an edge for teams building autonomous agents or trading bots. Instead of raw logs, the agent receives structured features that reduce preprocessing time and improve model performance — an attractive proposition for AI-driven Web3 products
