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For all its talk of transparency, DeFi still hides in plain sight. Data is public, but understanding it takes serious work.

The data is public, but it’s not accessible. It’s scattered across 400+ chains, kept within 6,000+ protocols, and buried under layers of complex smart contracts.

Getting a simple, accurate answer to a complex question has been nearly impossible. Users either get rigid dashboards that can’t answer their specific question, or they turn to new AI models that confidently “hallucinate” answers based on six-month-old, scraped data.

In an industry where millions move in seconds and trade volumes reach up to $200 billion, “stale” and “wrong” are fatal flaws.

But what if users could have a conversation with the entire on-chain market? What if they could simply ask, in plain English, “Which protocols have the most stable revenue streams?” or “Chart the total value lost to hacks versus capital raised,” and get an accurate, live-data chart in seconds?

LlamaAI is the analyst that makes this possible. Built by the team at DefiLlama, It is a fundamental redesign of how onchain intelligence is accessed.

The AI Insight Gap

The problem has been a two-front failure, leaving an over $3.80 trillion market to operate with compromised tools.

Large language models are impressive at writing and reasoning. But when it comes to finance, they’re unreliable. They operate on static data from an old snapshot of the internet. They can’t access what’s happening right now. Worse, they are prone to “hallucinations,” “making up” facts, figures, and even protocols that don’t exist. You can’t trust them for financial analysis.

On the other side, rigid data platforms. Tools like the Bloomberg Terminal can cost up to $25,000 per user per year. They are accurate but limited.

Users get pre-set charts for TVL, volume, and fees, but what if they want to ask a new question? What if they want to find the “capital efficiency” of a chain by dividing its total fees by its TVL? They would have to export multiple CSVs and spend hours in a spreadsheet.

LlamaAI: An Analyst, Not an Oracle

LlamaAI closes this gap. The concept is revolutionary in its simplicity: LlamaAI is the first LLM directly connected to DefiLlama’s complete and live database.

When users ask LlamaAI a question, it doesn’t “guess” the answer. It translates their natural-language prompt into a structured query. It then runs that query directly against DefiLlama’s entire dataset, the most comprehensive in the world, covering more than 6,000 protocols and 400+ chains.

The result is returned to you as a ranked table, a custom chart, or a precise analysis. It’s a calculation and AI’s flexibility combined with the precision of verifiable SQL, with zero hallucinations.

Prompt in Action: Finding True Capital Efficiency

Let’s see it at work. A common, but shallow, metric in DeFi is Total Value Locked (TVL). It’s a measure of hype. A much better question is: “Which chains are the most efficient with their capital?”

We can ask LlamaAI: “Which chains have the highest innovation ratio (original protocol TVL / forked protocol TVL)?”

• The Idea: We want to find ecosystems that are building new, original products.
• The Execution: LlamaAI parses this, identifying “chains,” “TVL,” and the concepts of “original” vs. “forked” protocols. It queries its database, sums the TVL for both categories on every chain, and calculates the ratio.
• The Finding: In seconds, LlamaAI generates a ranked table. This insight shows you which ecosystems are driven by genuine innovation and which are just echo chambers.

Prompt in Action: Correlating Risk and Reward

Let’s try something more complex. A cross-metric analysis that would normally take a research desk a week to compile.

We ask: “Create a chart of total capital raised vs total value lost to hacks by year.”

• The Idea: We want to visually correlate the industry’s funding booms with its security failures. Are we getting better at security as more money flows in?
• The Execution: LlamaAI uses two datasets: DefiLlama’s “Raises” and “Hacks” databases. It aggregates both metrics by year and plots them on a dual-axis chart.
• The Finding: It might show, for example, that as VC funding peaked, hacks followed suit, revealing that security practices lagged far behind capital deployment. This is a verifiable fact, generated in a moment.

Institutional-Grade Insight for Everyone

For the end-user, the experience is effortless because pre-made dashboards no longer limit them. They have an on-demand on-chain analyst at your fingertips. More than 19,800 pools, 1,300 protocols, 900 exchanges, and their support metrics can be tracked with LlamaAI. It unifies the analytic workflow, allowing a user to analyse many different charts and datasets from DefiLlama in a single session without ever leaving the interface.

The goal is all about democratising data. For years, the team has remained fiercely neutral, refusing to charge for listings or accept pay-to-play data.

LlamaAI extends that philosophy. It takes the kind of custom analysis previously available only to high-end quant funds and research desks, and makes it accessible to everyone. Retail traders and developers now have the same power to query the market, find alpha, and manage risk.

The Bottom Line: From Static Data to Live Intelligence

LlamaAI changes how we interact with onchain data. For AI, it solves the “truth” problem, grounding a flexible LLM in a verifiable database. For DeFi, it solves the “access” problem, making the transparent ledger truly readable for the first time.

The barrier to entry for deep on-chain analysis is no longer about the ability to code or build complex data pipelines. When a user asks a good question about any data, they will get an excellent answer to it.

LlamaAI represents the moment DeFi analytics grows up, moving from static, delayed reports to a live and intelligent relationship with the market. LlamaAI is available now to all DefiLlama Pro subscribers.