I built a context-aware AI for crypto portfolios. Here's why generic crypto AI is broken

Most crypto AI features follow the same pattern: a GPT wrapper that knows nothing about your actual portfolio. You ask "should I rebalance?" and get a 400-word essay about diversification theory. Useful to nobody.

I've been building HODLTrack for the past several months — a crypto portfolio tracker with real-time P&L, cost basis tracking, and price alerts. When I added AI, I wanted it to actually read your portfolio before answering. Not generic advice. Specific answers.

What we built

The AI Co-Pilot reads your live holdings — every position, quantity, cost basis, unrealized gain/loss, and allocation percentage — and passes that as context before any response is generated. The result is analysis that sounds less like a Wikipedia article and more like talking to someone who actually looked at your spreadsheet.

Some prompts we built quick-start buttons for, pulled directly from what users were asking:

"Analyze my risk profile — concentration, volatility, top concerns"
"What if I double my Bitcoin position? Show the allocation impact"
"Which positions are at a loss? Find tax-loss harvesting opportunities"
"Stress test my portfolio at −40% BTC"
"How does my portfolio compare to just holding Bitcoin?"
The responses are specific. If your BTC is 58% of your portfolio, the risk analysis tells you that a 30% BTC drawdown alone reduces your total portfolio by 17% — not "Bitcoin is volatile, consider diversifying."

Where we are with growth

Honest numbers: 3 signups total. 0 MRR. The product has been live for a few months.

What's actually moving: content. We've published 54 blog posts — mainly crypto tax guides by country (Germany, Canada, Australia, Singapore, Baltic states, UK, US) and product explainers. Traffic hit 146 unique IPs in a single day last week, up 204% from the day before. Mostly Google and Twitter.

The theory: people searching "crypto tax Germany 2026" or "Canada CRA crypto rules" have a specific problem. The solution to that problem is a portfolio tracker with accurate cost basis. We capture them at the research phase and try to convert them into users.

It's a long game. The AI Co-Pilot post I just published is the first product-focused piece in the mix — the idea being that people who land on the tax content and then see "oh, there's an AI that reads your portfolio and spots tax-loss opportunities" might convert better than people landing on a landing page cold.

The conversion problem

69 pricing page views last week. 0 signups since June 10.

I added two things yesterday to close this gap:

A "Try the demo first — no signup needed" strip on the pricing page for logged-out visitors
Redirect /dashboard → /demo instead of /sign-in for logged-out users (67 people hit /dashboard last week and got a login wall — now they get the live product)
I don't know yet if this moves the needle. The traffic is there. The exit point seems to be between "interested" and "willing to create an account."

What I'd love feedback on

Has anyone found a content → conversion flow that actually works for a crypto/fintech tool? The blog drives traffic but the funnel from "read a tax guide" to "sign up for a portfolio tracker" has real friction. Curious how others have handled the gap between educational content and product signups.

Also open to feedback on the AI Co-Pilot concept — is context-aware portfolio AI something you'd pay for, or does it feel like a nice-to-have?

Full post on how the Co-Pilot works: hodltrack.app/blog/hodltrack-ai-copilot-guide-crypto-portfolio-analysis

Live demo (no account needed): hodltrack.app/demo

#buildinpublic #saas #fintech #ai #crypto #contentmarketing