Ramses â Product Design
The core value props (dynamic fees, MEV capture, xRAM/hyperRAM) are clear, but brand metadata and the top-level IA feel inconsistent and leave the onboarding path under-instrumented.
1. Brand Positioning & Self-Description
From a positioning standpoint, the page tries to sell Ramses V3 (HyperEVM) as a âpro-grade liquidity engineâ rather than a generic swap UI.
- The hero messaging leads with outcomes: âDeep Liquidity. Multiple chains.â This is a market claim that they compete on liquidity quality + multi-chain reach, not just fees.
- The narrative quickly pivots to mechanism differentiation:
- Onchain dynamic fee algorithm (real-time fee adjustment based on volatility).
- MEV capture via permissioned arbitrage pipelines.
- Cross-venue arbitrage across HyperCore/HyperEVM/Arbitrum/lending.
- Tokenomics education is a major part of the story: xRAM (flexible alternative to ve(3,3) lockups) and hyperRAM (HyperEVM-specific evolution). This is a deliberate decision to position the DEX as a system (trading + incentives + governance-like voting), not only a swap product.
However, the title tag showing âVercel Security Checkpointâ breaks trust and weakens brand clarity. For a DEX, metadata hygiene is part of credibilityâthis mismatch makes the product feel unfinished even if the app is strong.
2. Navigation Architecture & Product Pillars
Top-level navigation is compact and reveals clear PM prioritization:
- Trade (primary utility)
- Liquidity (second pillar; supply-side growth)
- Stats (proof + transparency)
- Start App + Connect Wallet (action CTAs)
This IA implies the product is designed around a classic DEX loop:
1) users trade, 2) some become LPs, 3) stats validate legitimacy.
Whatâs notable is whatâs not surfaced in nav despite heavy homepage emphasis:
- xRAM / hyperRAM appears as content blocks, but thereâs no obvious top-level Stake / Vote / Earn pillar in the global navigation. If xRAM is central to sustainability and participation, it should likely be a first-class node.
- âMultiple chainsâ and âcross-venue arbitrageâ are big claims, but thereâs no visible Bridge or Networks entry point. Users may be left guessing how to actually access those chains.
Overall, the IA is clean and low-cognitive-load, but it currently treats tokenomics and multi-chain capability as marketing copy rather than navigable product modules.
3. User Flow & Conversion Strategy
The conversion strategy is straightforward: drive users from landing page to app usage with minimal friction.
- Primary CTAs are âStart Appâ and âConnect Walletâ. This sets the expectation that the key action is immediate, wallet-gated interaction.
- The homepage supports this with trust + performance proof points:
- TVL displayed prominently (quick legitimacy check).
- audits spend ($2M+) and volume (though the number formatting feels inconsistent and may confuse).
- Secondary CTAs support education and retention: âRead Documentationâ, âLearn More about Ramsesâ, plus explainer sections for xRAM and hyperRAM.
User journey implied by the layout:
1) user sees deep liquidity claim â 2) sees TVL proof â 3) clicks Start App â 4) connects wallet â 5) trades / adds liquidity.
Whatâs missing from a best-in-class onboarding flow:
- No visible chain readiness check (HyperEVM-specific network prompts, bridging guidance).
- No guided first action (e.g., âSwap ETH â USDC in 30sâ or âAdd liquidity and earn dynamic feesâ).
- xRAM messaging says âStake, Vote, Earn,â but the flow doesnât clearly route users into that loop after they trade.
4. Ecosystem & Community Footprint
The ecosystem signals are present but feel partially integrated into the product surface.
- Documentation is explicitly promoted near the top, which is a good sign for protocol maturity and developer/advanced user support.
- The product narrative emphasizes tokenomics systems (xRAM/hyperRAM) and MEV/internal arbitrage pipelines, which implies deeper infra and (likely) governance dynamicsâyet the page doesnât clearly expose governance entry points (vote pages, forums, proposals).
From an ecosystem design perspective, the current surface area looks optimized for:
- Traders (Trade)
- LPs (Liquidity)
- Analysts (Stats)
But it under-exposes:
- Builders (SDKs, subgraphs/indexing, integration guides beyond generic docs)
- Community participation loops (stake/vote incentives as a persistent module)
- Growth programs (grants, integrations, partner pages) that would support the âmultiple chains / cross-venueâ claim.
If the goal is to be the liquidity layer across venues, the product should treat ecosystem links as part of the IA (not just informational content), because integrations are a core distribution channel in DeFi.
5. Product Design Assessment
What I think the PM/design team got right:
- Clear product pillars for a DEX MVP: Trade, Liquidity, Stats. This keeps decision-making simple and avoids feature bloat.
- Differentiation is mechanism-led (dynamic fees, MEV capture). Thatâs smart: these are defensible features vs. âlow feesâ marketing.
- Tokenomics education is not buried. xRAM/hyperRAM are treated as core to the story, which helps long-term retention if the incentives are strong.
What Iâd change or tighten:
- Fix brand metadata immediately (the âVercel Security Checkpointâ title). It undermines trust and shareability (tabs, previews, SEO, link unfurls).
- Promote xRAM/hyperRAM to a first-class nav item (e.g., Stake / Vote / Rewards). Right now the product says âparticipate fairly,â but the IA doesnât operationalize it.
- Add network/chain onboarding for HyperEVM: detect chain, explain bridging, and provide a one-click âswitch networkâ flow.
- Improve metrics clarity (volume formatting, time window). Stats should answer: âIs this liquid and safe today?â
Compared to best-in-class DEXes, the foundation is solid, but it needs tighter end-to-end journeys: landing â trade â LP â stake/vote â return habit loop.