Nuclear industry and mapping data is severely fragmented across global facilities, making it difficult to conciliate operational, commercial, political, and geophysical information without manual cross-referencing.
Nuclear industry and mapping data is fragmented, making it hard to conciliate operational, commercial, political, and geophysical information across global facilities.
Show HN: Reactor Atlas
Missing the Australian research reactor OPAL in Lucas Heights...
commentNice site, looks like you had a bit of fun putting it together. Missing the Australian research reactor OPAL in Lucas Heights, Sydney - https://www.ansto.gov.au/education/nuclear-facts (https://www.ansto.gov.au/education/nuclear-facts) Note that while you do have the no longer operating Fukushima Daiichi plant, you don't have the ceased functioning easter egg natural nuclear fission reactors, such as the one in Oklo, Gabon. It seems related to address nuclear waste also - the filthy sites related to early nuclear weapons development, the surface blast sites during the testing years, current and proposed repository locations, various open pools of low level radioactive waste from mining, rare earth processing, etc. And, if you're going "full stack" - nuclear sources - Olympic Dam (sitting tight with large reserves), former African sites, Kazakhstan supplying the US and elsewhere, automated uranium mining in Canada, etc.
...the map-globe navigation feels confusing and unintuitive compared to a more conventional 2D map UI.
commentCool project! However, the map-globe navigation feels confusing and unintuitive compared to a more conventional 2D map UI. Also the clustering algorithm makes labels “jump” in a jarring way during zooming. I’d tune it somehow so that it feels better to the users.
Professionals and researchers tracking comprehensive global nuclear facilities, waste sites, and mining sources who struggle with fragmented data sources.
Users explicitly highlight fragmented information ecosystems, missing facility data categories, and confusing 3D globe UI navigation.
Purpose-built 2D mapping UI paired with complete, verified global nuclear infrastructure coverage from reactors to waste sites.
A centralized intelligence platform that aggregates operational, commercial, and geophysical data on global nuclear facilities into a clean, intuitive 2D mapping interface with complete data coverage.
Research and energy institutions spend hours manually aggregating fragmented data; $99/mo represents a fraction of an analyst's hourly cost to eliminate data collection friction.
“Unified global nuclear facility mapping and intelligence in one clean interface.”
A centralized intelligence platform that aggregates operational, commercial, and geophysical data on global nuclear facilities into a clean, intuitive 2D mapping interface with complete data coverage.
Target specialized energy, nuclear research forums, and academic subreddits (r/nuclear, r/geography)
Sourcing and verifying niche facilities like research reactors, waste sites, and uranium sources globally is resource-intensive.
The specialized audience of nuclear researchers and energy professionals is relatively narrow, requiring higher pricing tiers to scale.
Rendering global facility clusters smoothly without label jumping requires robust frontend optimization.
Run an Investment Memo to get a structured Go / No-Go verdict, competitor landscape, unit economics, and a 90-day validation roadmap for this opportunity.
Generate an investment memoThis idea scores in the upper-middle range of opportunities surfaced by MonetScope, with a validation sub-score of 7/10 against 3 independently sourced evidence signals. A "promising" rating usually indicates a real pain has been detected and discussed in the open, but the pipeline did not find enough signal to flag it as urgent or high-frequency. These opportunities can still produce excellent businesses — they often correspond to "boring" problems that established players have ignored — but the founder should expect a longer customer-development cycle to confirm willingness to pay.
It sits at the intersection of "analytics", "data-management", "energy", which makes it relevant to a specific subset of founders rather than a generic horizontal opportunity. SaaS opportunities at this stage tend to win on the strength of their initial wedge — a single workflow that the target user runs every week, where the existing solution is either spreadsheets, a clunky incumbent feature, or a manual process they hate. The build cost is moderate; the distribution cost is everything. The MonetScope pipeline surfaces this category alongside other saas signals, which is why it appears here rather than in a generic "trending ideas" feed.
Scores are derived from real forum discussions across Reddit, Hacker News and X, weighted by evidence volume and signal quality. How scoring works
MonetScope does not generate ideas from a language model's imagination. Every opportunity on this site is anchored to specific source posts and comments from real public discussions — typically on Reddit, Hacker News, or X — where actual users describe the pain in their own words. The AI's role is structuring, scoring, and grouping those signals into a navigable opportunity, not inventing the problem.
MonetScope's spider pipeline runs continuously and surfaces opportunities as new evidence accumulates. The "Updated" date in the header reflects the most recent re-scoring of this specific opportunity. Most saas opportunities visible in the public catalog draw from discussions in the last 30-60 days; older signals are de-prioritized because user pain shifts faster than most founders assume.
Overall score is a composite across six dimensions — pain, urgency, willingness to pay, market size, defensibility, and execution ease — designed to give a single number for triage. Validation score is narrower: it asks "how cleanly does the same signal repeat across independent sources?" An opportunity can score high on overall but lower on validation when one or two large discussions dominate the evidence; conversely, validation can be high on a smaller-overall idea where the signal is consistent but the addressable market is modest.
