Sei

Sei is a Layer 1 blockchain built specifically to serve trading applications, embedding an on-chain order book and a parallelized execution engine directly into the base protocol. Where most blockchains are built as general-purpose platforms that leave trading infrastructure to developers, Sei takes the opposite approach: make the chain itself act like a trading venue.

Background

Most blockchains treat financial exchange as an application-level concern. Developers building a decentralized exchange on Ethereum or a similar chain must construct order-matching logic in smart contracts, work around global sequential transaction processing, and absorb unpredictable gas costs. The result is often slow order finality, front-running opportunities, and a poor experience compared to centralized alternatives.

Sei’s thesis is that trading deserves a dedicated execution environment at the protocol layer. By building order-matching natively into the chain rather than delegating it to application smart contracts, Sei aims to eliminate several layers of overhead while providing shared infrastructure that every application on the network can use without rebuilding it from scratch.

This positioning places Sei in a competitive landscape alongside other performance-oriented chains — but with a narrower, more explicit focus. Rather than competing on every dimension, the team chose to optimize deeply for one use case: high-throughput, low-latency exchange of digital assets.

History

Sei was founded by Jay Jog and Jeff Feng, both with backgrounds in technology and finance. The project raised funding from a range of venture capital firms before its public launch.

The mainnet launched in August 2023 after an earlier testnet phase that attracted a community of developers building trading applications. The launch was notable for the speed of early ecosystem growth, driven partly by an airdrop of SEI tokens to early users and testnet participants — a common mechanism in the Cosmos ecosystem for bootstrapping community ownership.

In early 2024, the team announced a significant architectural upgrade often referred to as Sei v2. This upgrade introduced EVM compatibility, meaning that Ethereum smart contracts could run on Sei without modification. This was a meaningful expansion of scope: rather than requiring developers to write in Cosmos-native languages, Sei could now attract the much larger pool of EVM developers and allow existing Ethereum applications to deploy on Sei’s faster infrastructure. The upgrade also deepened the parallelization model, moving Sei closer to a fully parallel execution environment.

The network’s progress illustrates a pattern common to newer Layer 1 blockchains — rapid protocol iteration in the first two years as teams respond to developer feedback and competitive pressure.

Technology

Built on Cosmos, Optimized for Speed

Sei is built on the Cosmos SDK, the same modular framework underlying Cosmos and a number of other application-specific blockchains. This means Sei inherits Cosmos’s Delegated Proof of Stake consensus mechanism and its Inter-Blockchain Communication (IBC) protocol for cross-chain messaging. IBC allows Sei to transfer assets to and from other Cosmos-ecosystem chains, giving it access to liquidity that would otherwise require bridges.

Consensus on Sei uses the Tendermint BFT algorithm, which reaches finality in a single round — unlike chains that require multiple confirmations before a transaction is considered irreversible. This single-slot finality is important for trading because it means that once a trade executes, neither party needs to wait for further confirmations before treating the result as settled.

The Twin Turbo Consensus and Parallel Execution

Two architectural choices define Sei’s performance profile.

First, Sei processes transactions in parallel wherever dependencies allow. Most blockchains process transactions sequentially — one after another — which creates a throughput ceiling regardless of how fast the underlying hardware is. Sei analyzes transactions in each block to identify which ones touch independent state and can safely execute at the same time. Transactions that share state (for example, two trades affecting the same liquidity pool) are still processed in order, but the majority of independent operations run concurrently. This is similar in spirit to the approach taken by Solana, though implemented differently at the engineering level.

Second, Sei introduced a mechanism it calls “Twin Turbo Consensus,” which optimizes how blocks are proposed and how transactions are ordered within them. By front-loading certain coordination work before the formal consensus round begins, the chain reduces the latency between a transaction being submitted and appearing in a finalized block.

The Native Order Book

The most distinctive feature is the native order book module, which lives at the chain level rather than inside a smart contract. Applications can plug into this module to benefit from order matching without needing to implement it themselves. This shared infrastructure reduces code duplication, lowers the gas cost of matching operations, and enables a more consistent experience across trading applications built on the network.

The native order book makes Sei unusual: most blockchains are indifferent to what applications build on them. Sei’s protocol is opinionated — it has a point of view about what the primary use case is and encodes that view in the base layer.

EVM Compatibility

With the v2 upgrade, Sei added a parallel EVM execution environment alongside its native Cosmos execution layer. This means the chain can run both Cosmos-native smart contracts (written in Rust using CosmWasm) and Ethereum-compatible contracts (written in Solidity). The two environments can interoperate, allowing developers to mix tooling from both ecosystems. For a deeper look at how the EVM works, see the EVM explainer.

Tokenomics

SEI has a fixed maximum supply of ten billion tokens, a hard cap that will not be exceeded through inflation once fully distributed. This is a meaningful design choice compared to networks with uncapped emissions, where token supply expands indefinitely.

At mainnet launch, a portion of the supply was distributed through the genesis airdrop and ecosystem incentive programs. The remainder is subject to vesting schedules across team, investor, and foundation allocations. Vesting schedules — where tokens unlock gradually over months or years — matter because large unlocks can create selling pressure. Understanding vesting and token unlocks is worthwhile for anyone assessing any project’s long-term supply dynamics.

SEI serves several functions within the network. Token holders can stake their SEI by delegating to validators, earning a share of network transaction fees in return. Validators must maintain sufficient stake to participate in consensus, aligning their economic interests with honest behavior. Transaction fees on the network are denominated in SEI, meaning that demand for block space — from traders, developers, and applications — translates into demand for the token.

The network can also adjust its emission rate and fee parameters through on-chain governance, where SEI holders vote on protocol changes. This connects to the broader governance and DAO structures common across the crypto ecosystem.

One area worth watching is how fee revenue scales relative to token emissions. A network that generates meaningful fee income can sustain itself even as inflation winds down; one that relies primarily on token emissions to incentivize participation faces a structural challenge as supply approaches its cap.

In summary

Sei occupies a specific corner of the Layer 1 landscape: a chain built with trading in mind from the ground up, rather than adapted to it after the fact. Its native order book, parallel execution, and Cosmos-based finality address real bottlenecks that traders encounter on general-purpose chains. The v2 EVM upgrade broadened its developer base considerably. Whether the trading-specific thesis translates into durable network effects depends on whether applications — and ultimately users — concentrate there over time. As with any emerging network, the gap between technical capability and actual adoption is where the real uncertainty lives.