Galaxy: How Titan Restructures Solana’s Price Discovery Mechanism

I. The Evolution of Solana's Trading Infrastructure

Over the past two years, Solana's market structure has undergone a dramatic transformation, driven by a surge in retail trading activity and the unique demands of high-frequency on-chain trading. This evolution began with traditional order book exchanges like Serum and Phoenix, where market makers actively provide liquidity, resulting in tighter spreads than passive automated market makers (AMMs) using standard xy=k bonding curves. Initially, these platforms dominated price discovery, particularly during the meme coin craze of early 2024, when Phoenix handled a significant amount of high-volume trade flow. However, these platforms have consistently lagged behind centralized exchange order books, both historically and currently. On-chain trading infrastructure has faced significant challenges. During peak congestion from March to May 2024, Solana became virtually unavailable for market makers: traders were sending thousands of trades per second, but only two or three were successfully uploaded to the blockchain. Updating order book quotes consumed hundreds of thousands of computational units (CMUs)—Solana's unit of computational power—making trade scheduling significantly more challenging. More critically, the public availability of quotes on exchanges like Phoenix made market makers vulnerable to sophisticated arbitrageurs. Even with significant retail trading volume, toxic order flow eroded market making profits. 2. The Rise of Proprietary AMMs In the fall of 2024, this pressure gave rise to "proprietary AMMs," or "dark pool AMMs." These protocols represent a fundamental shift in how professional market makers provide liquidity on Solana: Unlike traditional AMMs, proprietary AMMs do not release their source code or matching logic publicly. Instead, they integrate directly with routing protocols like Jupiter, maintaining strict confidentiality over their pricing algorithms. Proprietary AMMs utilize a preference curve mechanism, allowing them to update liquidity across multiple markets with a simple parameter adjustment, without having to deal with complex order book structures. This efficiency allows them to offer tighter spreads while also circumventing harmful order flow by preventing arbitrageurs from interacting directly with the contract. This creates a cat-and-mouse game in which sophisticated traders attempt to disguise themselves as harmless order flow and obtain these better quotes through aggregators. The traditional order book model is fundamentally broken on Solana, a feature of DeFi composability, not a bug. The core issue lies in the economics of state management: maintaining a full order book on-chain requires updating multiple price tiers with every market fluctuation. Combined with Solana's priority fees and Jito tips, each update can consume hundreds of thousands of computational units, making it economically unfeasible for market makers to maintain competitive quotes across dozens of price tiers. Traditional order books aggregate disparate orders into a unified structure, allowing takers to obtain the best price through an auction mechanism. On Solana, however, aggregators become synthetic order books, and proprietary AMMs act as smart order submitters—modifying a single parameter can update the entire pricing curve. This model relies entirely on DeFi's composability: smart contracts can interact atomically within a single trade, something impossible in the closed systems of traditional finance or CEX environments with opaque matching engines. Instead of maintaining costly state at multiple independent price levels (each of which requires independent updates), proprietary AMMs leverage oracle-based pricing curves—a single transaction updates all quotes, equivalent to submitting 100 orders simultaneously on a traditional order book. This composable architecture disassembles and reconstructs the order book into a distributed price discovery mechanism: the aggregator acts as the matching engine, the proprietary AMM provides liquidity, and mathematical optimizations ensure optimal execution while maintaining atomic composability.

Data source: Galaxy | Data as of September 25, 2025

3. The fragmented market urgently needs high-quality aggregation services

Today's Solana trading landscape is highly fragmented: with over 10,000 liquidity pools, multiple proprietary AMMs with their own proprietary pricing logic, and different quotes from traditional DEXs, efficient aggregation services have become the key to achieving competitive transaction execution. In this fragmented environment, price discovery cannot be efficient without a sophisticated routing algorithm capable of navigating complex liquidity networks. On Solana, both elastic and inelastic users ultimately rely on aggregators to obtain the best prices—aggregators currently handle 81% of the network's DEX trading volume. This stands in stark contrast to Ethereum, where only 20% of Ethereum trades flow through aggregators. Solana's dominant position in aggregated trade flow provides a strong impetus for continued innovation in routing technology. Fourth, Titan's Mathematical Advantages This is where Titan comes in. While most aggregators use classic path-finding algorithms like Bellman-Ford, Titan leverages pure mathematical optimization techniques to achieve superior trade execution. The core difference between the two lies in precision: Path-finding algorithms "chunk" liquidity (e.g., discrete proportions like 10% or 20%), resulting in efficiency losses when trading across platforms. Titan's convex optimization approach, on the other hand, precisely allocates any proportion of trading volume to multiple liquidity pools, extracting maximum value from fragmented liquidity with machine-level precision. This isn't simply an incremental improvement. Mathematical optimization methods enable Titan to incorporate more liquidity pools into its routing calculations, finding optimal paths that are inaccessible to classical algorithms. In practical terms, this means users consistently receive better quotes: when exchanging asset Y for asset X, they receive significantly more. V. Titan's Incremental Improvement Economics Let's examine the compounding effect of Titan's proven execution improvements. If a trader exchanges $1,000 per trade and saves an average of 21 basis points (0.21%) per trade through Titan, the long-term value is significant: For an active trader executing 10 trades per day, Titan's premium routing could save $7,665 per year through linear accrual alone. If these savings are reinvested and compounded, the annual return increases to $10,384, a 35% improvement over the linear return alone. Titan's execution advantage is even more meaningful for algorithmic trading strategies, which dominate Solana's trading volume. Wallets like Phantom charge fees based on user trading profits, so Titan's consistent outperformance translates directly into user returns. For example, through Titan's optimized routing, each trade earns an additional 0.5 SOL (increasing from 99.5 SOL to 100 SOL). Compounded over thousands of trades, this will lead to actual portfolio growth that is positively correlated with trade frequency and scale. VI. Future Outlook: Evolution of Market Structure Looking ahead, we believe the following trends will shape Solana's market structure: As aggregators compete for market share, competition for zero-commission trading will intensify. The traditional finance fee-for-order flow (PFOF) market provides a strong example of sustainable monetization: In May 2024 alone, US retail brokerages generated $461 million in order flow revenue, with Robinhood generating over $100 million per month. This model works because market makers value harmless retail order flow. Unlike the standardized National Best Bid and Offer (NBBO) in traditional markets, Solana’s PFOF model is more granular: DEXs and market makers can tier order flow by wallet address or execution complexity. Titan’s development path mirrors that of Interactive Brokers: it began as a technology-first execution platform and then expanded into a full-service broker. Similar to Interactive Brokers, Titan can monetize in multiple ways: charging execution fees to established traders, generating revenue through order flow collaboration, and providing high-end services to institutional clients. A key differentiator lies in Solana's fragmented market structure, which further emphasizes the value of high-quality routing technology. As more established trading institutions launch proprietary AMMs, the fragmentation of liquidity providers will continue. Teams like Wintermute and Wincent, along with emerging players, are continuously upgrading their algorithms, driving an arms race in execution quality. While this benefits users through tighter spreads, it also places greater demands on the sophistication of aggregation services. Through upgrades like Alpenglow, Solana's trade finality times will be shortened, reducing slippage and enabling more accurate quotes. With shorter block times and more efficient finality, aggregators can reduce the "cushion for adverse price fluctuations" in their quotes, thereby offering tighter spreads. While the RFQ system introduces latency, it ensures that trades are executed at the quoted price. This trade-off between speed and certainty allows for differentiated services for different user groups. VII. Titan's Strategic Positioning We believe Titan is uniquely positioned to capture value within this evolving landscape. Beyond the technical advantages of mathematical optimization, the platform can generate revenue through multiple channels: wallet integrations, premium products for sophisticated traders, and order internalization opportunities as trading volume grows. Even more compelling is its incentive alignment: Titan only charges fees when it outperforms its competitors, directly tying protocol success to user value. With its proven win rate advantage and growing adoption among mainstream wallets, Titan represents a fundamental advancement in on-chain price discovery. As Solana's infrastructure matures and institutional adoption accelerates, market demands for execution quality will continue to rise. Platforms that can consistently create value for users in an increasingly complex environment are expected to gain an advantage in the market.