# LYS Labs Docs

## LYS Labs Docs

- [Introduction](https://docs.lyslabs.ai/introduction.md): Last updated April 2025. Our stack is continuously expanding - follow us on Twitter or join our community on Discord to keep up with the latest.
- [The Platform](https://docs.lyslabs.ai/the-platform.md): LYS is more than just a data feed or analytics dashboard - it’s a composable, real-time data infrastructure stack. This section breaks down the functional layers of the LYS system - from how raw block
- [Architecture](https://docs.lyslabs.ai/architecture.md)
- [APIs and Streams](https://docs.lyslabs.ai/apis-and-streams.md): Find out how to get access to supersonic data.
- [Structured Data](https://docs.lyslabs.ai/structured-data.md)
- [WebSocket API Reference](https://docs.lyslabs.ai/structured-data/websocket-api-reference.md): Real-time streaming API for Solana transactions
- [Decoders](https://docs.lyslabs.ai/decoders.md)
- [Boop.fun](https://docs.lyslabs.ai/decoders/boop.fun.md): This document describes the output structure for the Boop Fun decoder functions. The decoder handles two main event types: INITIALIZE and SWAP.
- [LaunchLab](https://docs.lyslabs.ai/decoders/launchlab.md): This document describes the output structure for the LaunchLab decoder functions. The decoder handles three main event types: SWAP, CREATE, and MIGRATE\_CPMM.
- [Meteora DAMM V2](https://docs.lyslabs.ai/decoders/meteora-damm-v2.md)
- [Meteora DAMM](https://docs.lyslabs.ai/decoders/meteora-damm.md)
- [Meteora DBC](https://docs.lyslabs.ai/decoders/meteora-dbc.md)
- [Meteora DLMM](https://docs.lyslabs.ai/decoders/meteora-dlmm.md)
- [Pump Swap](https://docs.lyslabs.ai/decoders/pump-swap.md): This document describes the output structure for the Pump Fun AMM decoder functions. The decoder handles four main event types: CREATE\_POOL, SWAP (with buy/sell variants), DEPOSIT, and WITHDRAW.
- [Pump Fun](https://docs.lyslabs.ai/decoders/pump-fun.md): This document describes the output structure for the Pump Fun decoder functions. The decoder handles four main event types: SWAP, COMPLETE, CREATE, and MIGRATE.
- [Raydium AMM](https://docs.lyslabs.ai/decoders/raydium-amm.md): This document describes the output structure for the Raydium AMM decoder functions. The decoder handles four main event types: INITIALIZE2, SWAP, ADD\_LIQUIDITY, and WITHDRAW\_PNL.
- [Raydium CLMM](https://docs.lyslabs.ai/decoders/raydium-clmm.md)
- [Raydium CPMM](https://docs.lyslabs.ai/decoders/raydium-cpmm.md): This document describes the output structure for the Raydium CPMM decoder functions. The decoder handles four main event types: INITIALIZE, SWAP\_BASE\_INPUT, DEPOSIT, and WITHDRAW.
- [SPL Token Transfers](https://docs.lyslabs.ai/decoders/spl-token-transfers.md): This document describes the output structure for the SPL Token decoder functions. The decoder handles five main event types: TRANSFER, MINT, BURN, INITIALIZE\_ACCOUNT, and CLOSE\_ACCOUNT.
- [Contextualized Data](https://docs.lyslabs.ai/contextualized-data.md)
- [Real-time aggregations](https://docs.lyslabs.ai/contextualized-data/real-time-aggregations.md): Real-time aggregations are calculated on every new block, enabling decision-making within milliseconds. These are designed for HFT, alerts, and automated execution.
- [WebSocket API Reference](https://docs.lyslabs.ai/contextualized-data/real-time-aggregations/websocket-api-reference.md): Real-time streaming data for Solana transactions and aggregated statistics with low latency and high throughput.
- [Token Snapshot](https://docs.lyslabs.ai/contextualized-data/real-time-aggregations/token-snapshot.md): Field Reference
- [Historical aggregations](https://docs.lyslabs.ai/contextualized-data/historical-aggregations.md): Historical aggregations are computed across days, weeks, and months - ideal for PnL analysis, smart wallet tracking, market research, and portfolio insights.
- [Aggregation Infrastructure](https://docs.lyslabs.ai/contextualized-data/aggregation-infrastructure.md)
- [On Demand Data](https://docs.lyslabs.ai/on-demand-data.md): Tailored blockchain analytics, and metrics built for your exact business needs. Delivered in real time, fully structured, and ready for integration.
- [Case Study: Solexys](https://docs.lyslabs.ai/case-study-solexys.md): A Research Agent Powered by LYS Labs data
- [Contact](https://docs.lyslabs.ai/contact.md): This page contains all relevant ways to get in touch with the LYS Labs team, access community channels, and view official policies or documentation.
- [Builders Program](https://docs.lyslabs.ai/builders-program.md): Signal your interest in participating in the LYS Labs Builders Program.


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