Mercuri Finance

Challenge

The product had to communicate concentrated-liquidity coordination, autonomous vault behavior, and non-custodial trust boundaries clearly enough for users to understand the model, while the team also needed stronger internal systems to support execution speed.

What we shipped

We supported the public web experience across the main site and app surface, helped implement parts of the AI system, and worked on agentic workflows using Claude and OpenAI to automate operations, marketing, outreach, and engineering support work.

Outcome

Mercuri now has a more coherent public-facing presence plus stronger internal leverage from AI-enabled workflows, connecting product positioning, interface exploration, protocol explanation, and day-to-day execution into a tighter operating system.

Selected product surfaces

A snapshot of the Mercuri system across the website and app.

Autonomous Liquidity Agents

Smart vault management, without giving up custody Enable Smart Mode to automate range selection, rebalancing, and fee harvesting. Agents optimize for in-range time and yield while withdrawals remain owner-only.

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Build on Mercuri

Integrate vaults, positions, and analytics Use Mercuri’s developer tooling to read vault state, track positions, and integrate vault flows into your app. Designed for fast integration across supported chains.

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Public framing mattered as much as the interface

Mercuri sits in a technically demanding space. The product has to make sense to users exploring autonomous liquidity vaults while still respecting the real complexity behind concentrated liquidity, delegation, and deterministic safety boundaries.

• The public site needed to explain the product without collapsing into generic crypto language.
• The app surface needed to feel real and navigable, not just conceptual.
• The technical narrative had to support trust by explaining the system model clearly.
• The team also needed internal leverage so execution work could move faster without relying only on manual coordination.

We supported the AI system as well as the surface

The work was not limited to presentation. We also supported implementation of Mercuri’s AI system, helping connect the public product direction to real system behavior and workflow support behind the scenes.

That meant the project could evolve as more than a marketing shell or a protocol document. The AI layer, public UX, and technical explanation were shaped as parts of the same product story.

We helped build the public product system

This was not just a matter of pointing users toward a few endpoints. We helped build and shape the public system around Mercuri: the marketing site, the app experience, the protocol narrative, and the connective tissue that made them feel like one product rather than disconnected artifacts.

• The main website carried the positioning, product explanation, and trust framing.
• The app surface gave users a concrete way to explore the product experience.
• The white paper formalized the protocol model and reinforced the technical story.

Agentic workflows created internal leverage

Alongside the public product work, we helped automate parts of Mercuri’s operations, marketing, outreach, and engineering workflows using skills and agentic workflow patterns built on Claude and OpenAI.

• Operational support workflows that reduced repeated manual coordination.
• Marketing and outreach flows that made content and follow-up work more systematic.
• Engineering support loops that helped the team move faster with reusable skills and agentic patterns.

Why the product story works better publicly

The public material now has a clearer through-line: Mercuri presents itself as a coordination layer for concentrated liquidity, with autonomous vault behavior and a non-custodial model that users can inspect through both the product interface and the protocol documentation. Internally, the team also has stronger AI-assisted leverage around execution work.

Concentrated liquidity requires continuous monitoring, frequent repositioning, precise mathematical reasoning, and responsiveness to changing volatility and gas conditions.Mercuri white paper, February 15, 2026

Discuss a similar product

If you are building a technically dense product and need the public surface, AI system implementation, and internal agentic workflows to reinforce each other, we can help shape the right first slice.