Goldirham Insight
AI-era investment research with source-labeled market data
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Goldirham Insight is an educational research and demonstration platform covering 234 assets across the AI build-out, growth funds, and crypto. It combines a broader reference catalog with 26 scored research assets, and every price and chart states whether it comes from a market feed or a simulation.
[!IMPORTANT]
This is an educational project, not financial advice. See the disclaimer.
Contents
Features
| Feature | Description |
|---|
| Research desk | Search by company or ticker, filter by theme or Tier 1, and rank by upside, safety, or AI exposure. Assets listed in more than one theme appear under each. |
| Custom blend | Weight the three scores from 0 to 5 to rank scored assets your way. Catalog entries awaiting scores appear after scored assets and show no invented blend. |
| Shareable views | The URL stores search, filters, ranking, and blend weights, so reloads, shared links, and the Back button restore the same results. |
| Asset comparison | Compare up to three assets side by side on scores, thesis, risks, and review status at /compare. |
| Asset pages | Research assets show their thesis, scores, and tier. New catalog entries show reference details and pending assessments. Every page includes a research record, source-labeled quote, and chart. |
| Asset logos | Local company, fund, and crypto marks on cards, search results, asset pages, comparisons, and share previews, with source URLs recorded for every asset. |
| Share previews | Generated link previews for the site, every asset, and every comparison. They show scores and review status, never prices. |
| Live desk | A market quote band where observed prices flash when they move, a feed of the day's largest moves, a featured-asset specimen panel, a framework scorecard, and header search (press /) that opens any asset's research directly. |
| Watchlist | Save assets in the browser and filter the desk to them. Nothing is sent anywhere and there is no sync, but a reader can export the list as a file and import it on another device, where it is merged with what is already saved. |
| Live quotes filter | Show only assets whose current quote comes from a market feed. |
| Feed status | /status lists each quote's source, age, and why it is simulated. A closed market's last price, including on scheduled NYSE holidays and 1:00 pm early closes, is not treated as a fault. |
|
Scoring model
The 26 scored research assets use the same three factors, each rated from 0 to 10. The 208 new catalog entries show Scores pending research until an assessment is recorded. Score rankings place those entries after scored assets.
| Factor | Question | Considers |
|---|
| Upside | What could go right? | Return potential if the thesis plays out, and the catalysts that could get it there |
| Safety | What could go wrong? | Balance-sheet strength, business-model resilience, and drawdown behavior |
| AI exposure | How deep is the connection? | How structurally tied the asset is to the AI build-out |
Scores are editorial opinions. An asset is shown as Reviewed only when its record includes a named reviewer, an actual review date, supporting sources, and a rationale for all three scores. Every other asset is labeled Not reviewed. No authors, dates, or citations are invented.
Coverage
| Category | Assets | Focus |
|---|
| AI Utilities | 53 | Power producers, utilities, grid equipment, and data-center infrastructure |
| AI Companies | 53 | AI platforms, GPUs, foundries, memory, networking, and software |
| Mega Stocks | 51 | Global large-cap companies and existing research selections |
| AI & Growth ETFs | 52 | Growth, technology, chips, AI, robotics, and infrastructure funds |
| Crypto | 51 | Digital assets from the filtered reference list and existing research |
234 distinct symbols across 5 categories. Category counts overlap because assets can appear in more than one theme. All 234 have local brand logos in public/logos/, with provenance recorded in sources.json.
This is the beginning of the README. Read the rest at the original. Read the full README ↗
