AICoinMetrics (aicoinmetrics.com) analyses any crypto coin with AI and renders the result as an investor-grade risk dashboard. Live data from market, on-chain and contract-security sources grounds every analysis, the AI writes the verdicts and rationale, but is never allowed to produce a market number itself. Sold as a metered subscription SaaS.
Challenges & Solutions
AI-fabricated numbers would make the product worthless
A crypto risk report that invents a price or a holder count is worse than no report. The core design risk of a generative dashboard is confident nonsense.
Grounded, schema-constrained generative UI
The AI emits a typed dashboard specification chosen from a fixed catalog of widgets, verdict, risk meter, valuation scenarios, security signals. Live market and contract-security data is bound server-side, so the model never supplies a number.
A full SaaS on a strict edge runtime
Metered billing, authentication and webhooks all had to run within the limits of an edge platform where standard server tooling doesn't simply work.
Edge-native billing and metering
Hosted checkout with webhook-driven entitlements, secure cookie sessions, and per-tier usage quotas enforced server-side, with a fair-use cap that bounds AI spend.
01. Design First
Before building, we wrote the data model, auth hardening, billing and generative-UI design docs, and locked the decisions.
02. Grounding Layer
We integrated market data, token-security signals, liquidity and sentiment sources as the factual base for every analysis.
03. Generative Dashboard
We built the schema-constrained AI pipeline and the trusted widget registry that renders it.
04. Metered SaaS
Subscription tiers, quotas and analysis history took it from tool to product, live on aicoinmetrics.com.
The rule that makes AICoinMetrics work: AI is great at judgement and terrible at facts, so the facts always come from the data layer, never from the model.
Matisse Callewaert
Co-founder & CTO, Strategoo
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