If You’re Not Using AI in Your Crypto Research, You’re Missing Out on Alpha

If You’re Not Using AI in Your Crypto Research, You’re Missing Out on Alpha

In today’s fast-evolving crypto landscape, the edge isn’t just in price charts—it’s in uncovering undervalued protocols and spotting fundamental growth before the market catches on. In this post, I’ll share how I personally use AI tools to unearth those opportunities—and how you can too.

Why Traditional Research Isn’t Enough

Most crypto research still relies on:

• scanning news headlines and Twitter threads

• eyeballing token prices and chart patterns

• mining dashboards for selectable metrics

These methods have value—but they’re reactive. They reveal what the market already knows (or is in the process of realizing). To get ahead, you need to dig into fundamental data behind the scenes—and you need to do it fast.

Large language models (LLMs) like ChatGPT, Claude and others are great at language tasks: drafting, summarizing, coding. But when it comes to live crypto data, daily protocol metrics, on-chain flows and deriving investment insights—they fall short. Many have data cut-offs, lack depth in structured on-chain datasets, or require tedious manual filter work.

How I’m Using AI to Get Ahead in Crypto: LlamaAI Walkthrough

Enter LlamaAI: The AI Tool Built for Crypto Protocol Analytics

That’s where LlamaAI comes in. Developed by DeFi Llama, it gives you a natural language interface that’s directly connected to a heavy-duty dataset of on-chain, DeFi, and protocol metrics. DeFi Llama+2Crypto Briefing+2

Here’s why it stands out:

• It taps into DeFi Llama’s full dataset: protocols, chains, TVL, revenue, fees, open interest. DeFi Llama+1

• You can ask plain-English prompts like: “Which protocols have growing revenue but falling token price?” and get results + charts + tables. DeFi Llama+1

• It automates chart creation, data exports, filtering across categories and tokens—saving you hours of manual work. DeFi Llama+1

How I Use It to Find Alpha (and How You Can)

Here’s a breakdown of my workflow, and how you might apply it in your own research process:

1. Define the “Undervalued” Signal

I start by asking: Which protocols are showing fundamental strength (growing TVL & revenue) while their token price lags or falls?
With LlamaAI I’ll type something like:

“Find protocols with 30-day revenue growth > x%, TVL growth > y%, but token price decline > z%.”
The tool pulls the exact list, generates a ranked table, includes links and charts. This way I spot opportunities before the market fully re-rates them.

2. Chart & Visualize

Next I ask for visualizations:

• scatterplot of “TVL vs revenue” for top N protocols

• time-series of token deposits into DeFi for a given ecosystem (e.g., “BTC deposited into DeFi over past 365 days”)

• stacked bar charts comparing revenue/TVL across protocols

These charts help me see efficiency, momentum, and imbalance (e.g., high revenue, low market-cap = potential alpha).

3. Filter for Efficiency & Stability

Another key angle: which protocols generate the most revenue per unit of TVL?
A protocol might have huge TVL, but if its revenue is weak, the underlying business might be inefficient. So I’ll ask LlamaAI:

“Which protocols had >$1 m revenue in past 30 days and highest revenue/TVL ratio?”

That helps me identify lean, high-velocity protocols—often the hidden gems.

4. Monitor Behavior & Trend Shifts

Finally, I set up recurring prompts or checks:

• “Which chains/categories show rising innovation ratio (e.g., original protocol TVL / forked protocol TVL)?”

• “Which protocols have the most stable revenue over the past 180 days (lowest coefficient of variation)?”

These filters help avoid volatile “boom-and-bust” plays and lean into sustainable growth.

Why This Matters for Crypto Investors

• Speed counts: The market moves fast. If you’re still manually digging data, you’re already behind.

• Fundamentals matter: In crypto, narrative + token price often move ahead of fundamentals—but the real alpha happens when fundamentals catch up first.

• Differentiation: Everyone sees token price spikes; fewer dig into protocol-level metrics deeply. That’s where your edge lies.

• Visual & actionable: Charts make it easy to build theses, share with teams, or track in dashboards.

Important Disclaimers & Best Practices

• This is not investment advice. Use the tool as research and always perform your own due diligence.

• Even powerful AI tools can make mistakes (“hallucinations”) or mis-interpret data—so cross-check key insights. DL News+1

• Metrics like TVL, revenue, fee structures evolve—so always understand context (tokenomics, protocol risks, regulatory exposure).

• Treat the charts and lists as idea generators, not trade triggers.

Conclusion: Don’t Be Left Behind

If you’re still using spreadsheets and dashboards alone for crypto protocol research, you’re missing out. Tools like LlamaAI are enabling the next wave of alpha: searching for growth in real data, not just price spikes.

By marrying natural-language AI + in-depth on-chain datasets, you can find undervalued protocols before they become mainstream, build stronger investment theses, and move faster than the crowd.

If this resonates—and you’d like a step-by-step tutorial, prompt-library, or even narrative-driven case-study of using LlamaAI for a lesser known protocol—I’d be happy to build that out.

Let me know if you’d like me to tailor this post further (e.g., add sections on meme-coins, or how to integrate AI findings into your portfolio strategy).