Alternatives
Products that do what I built a website showing the likelihood of the AI bubble to pop does
I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
- 1WU
hey y'all -- can you please tell us if our job search tool sucks? :D we built it using an investor platform called Harmonic.ai to gather startup data, then contextualize it so that job seekers could find out about the most exciting startups hiring first (like if they just raised, growing headcount fast, have an ex-unicorn founder, etc). pretty sure we're the first platform doing anything like this. anyway, let me know what you think. really excited to launch this thing soon! getting feedback from the hn community first is really fun :)
2022 · joinmaasive.com
- 2AB
The AI Bubble Monitor is an analytical tool designed to track and visualize indicators of potential market bubbles in AI-related sectors. It aggregates multiple data sources and metrics to produce a composite "AI Bubble Score" that ranges from 0 to 100. The tool breaks down the overall score into five sub-indices: Valuation, Capital Flows, Adoption vs Fundamentals, Sentiment & Hype, and Systemic Risk. Each sub-index provides insight into different aspects of market behavior and potential overvaluation.
Nov 2025 · aibubblemonitor.com
- 3TC
Hello, I wanted to share with you all a interactive map of the economics and physics constraints of the AI buildout. It has macro drivers, industrial chokepoints, and where that shows up in markets. I've added 393 nodes and 562 edges to capture other supply / physics constraints as well. There's no sign up, and no pay wall, it's all free. Please let me know what you think!
Jun 2026 · atomprophet.io
- 4IB
A while back, I built a simple app to track stocks. It pulled market data and generated daily reports based on my risk tolerance. Basically a personal investment assistant. It worked well enough that I kept going. Now, the same framework helps me with real estate: comparing neighborhoods, checking flood risk, weather patterns, school zones, old vs. new builds, etc. It’s a messy, multi-variable decision—which turns out to be a great use case for AI agents. Instead of ChatGPT or Grok 4, I use mcp-agent, which lets me build a persistent, multi-agent system that pulls live data, remembers my…
2025 · github.com
- 5SO
Hey HN, I’m Dan. I’ve been working on forecasting for the last six years at Google, then Metaculus, and now at FutureSearch. For a long time, I thought prediction markets, “superforecasting”, and AI forecasting techniques had nothing to say about the stock market. Stock prices already reflect the collective wisdom of investors. The stock market is basically a prediction market already. Recently, though, AI forecasting has gotten competitive with human forecasters. And we’ve found a way of modeling long-term company outcomes that is amenable to our forecasting approach. Iteration by…
Nov 2025
- 6AP
I made a lightweight web game about compute CAPEX tradeoffs: https://darios-dilemma.up.railway.app/ No signup, runs on mobile/desktop. Loop per round: 1. choose compute capacity 2. forecast demand 3. allocate capacity between training and inference 4. random demand shock resolves outcome You can end profitable, cash constrained, or bankrupt depending on allocation + forecast error. Goal was to make the decision surface intuitive in 2–3 minutes per run. It’s a toy model and deliberately omits many real world factors. Note: this is based on what I learned after listening to…
Feb 2026 · darios-dilemma.up.railway.app
- 71R
Hi HN, We’re a small team working on 13Radar.com, which we launched about two weeks ago after 4 months of development. I’m the founder, and together with the team we’re building a platform that tracks hedge fund portfolios in real-time based on SEC Form 13F filings. AI has been a major helper in our workflow. For a single webpage, we often consult multiple AI systems in parallel, generating different versions and comparing them side by side before deciding on the final design or implementation. More than 60% of the research, design, and coding involved AI assistance. For UI design we used…
Nov 2025 · 13radar.com
- 8WB
Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…
2024 · dorik.com
- 9IP
To be specific, the content is generated by a GPT-2 based model. https://amzn.to/2TCc0v2 Let me know if you have any questions :-)
2020
- 10

- 11FF
I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
- 12

Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
- 13IB
I'm Canadian, live abroad, and my money is scattered across two countries, multiple currencies, banks, brokerages, real estate, and some private equity. No app could hold all of it, and none could answer a simple question like "what's my actual USD exposure?" Brisa pulls everything together (Plaid + manual accounts + real estate + PE, all multi-currency) and puts an AI on top that has my full financial picture in context. Instead of clicking through charts, I can just ask. Would appreciate any feedback!
Jul 2026 · demo.joinbrisa.com
- 14WT
I've been lurking on HN for years. You know the drill: interesting headline, 200+ comments, you dive in thinking "I'll just skim for 5 minutes"... and an hour later you're 36 chambers deep in a thread about memory allocation patterns in Postgres and you've completely forgotten what the original article was about. I don't just want a "summary" (which usually just shortens the noise). I want the meta-consensus: "What is the actual trade-off being debated? Who is winning the argument? Why does this matter?" So I built HNSignals. Think of it less like a "summarizer" and more like a Chief of…
Jan 2026 · hnsignals.com
- 15AA
looking for some feedbacks and areas for improvements
Sep 2025 · equity-analyzer.com
- 16IB
I posted this a few weeks ago and the server died under the traffic. Fixed that by adding an in-mem caching layer with Redis/valkey and added CloudFront caching for static content. Also upgraded the server. Also fixed the Firefox bugs, trying again. It's a research tool for US stocks. Financials for ~10k companies pulled from SEC filings. You can chart any metric across companies, filter news by ticker, ask questions in plain English and get a chart back. There's also SQL console against the whole database, which is the part I like to use together with the AI chat (generates an SQL…
Jun 2026 · terminal.tesseractanalytics.ai
- 17IC
For the last few months I have been analysing Peter Lynch’s books on stock picking and doing prompt engineering to check if AI could create useful stock analyses. To my surprise it started making reports that allow me to understand companies much faster with well cited sources. I hope you find it interesting and useful :) Perter Lynch’s books I analyzed: Learn to earn, One up on Wall Street, Beating the street
Jun 2026 · github.com
- 18

This project grew out of frustration of trying to find out the odds of a Hantavirus pandemic. When I went to search for it, I had to wade through sports gambling, and novelty markets that distracted me from just getting a really useful number with context to know if it was accurate. To solve this, my friend and I made mondael.com, which we're using to analyze, and visualize interesting prediction markets in the realm of: Geopolitics, Elections, Macro, Finance, Energy, and Science & Technology. The basic belief is that prediction markets can often move faster than news, but only if the data…
Jul 2026 · mondael.com
- 19
- 20WB
Hey HN: Kaveh here, founder of https://www.usage.ai/ We help companies drive down AWS, GCP, and Azure spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs rather than focusing on business problems. I have been building Usage AI for almost 4 years now (4 year anniversary in 1 month from now!) with an incredible group of founding people. We started as a product just to help lower AWS EC2 costs, and now we do all major AWS services (such as RDS, OpenSearch, ElastiCache, and Redshift with more on the way) and other…
2024
- 21IM
How it works (tech stack): -Built entirely with Lovabl.dev (no-code front-end + logic) -ChatGPT / Claude for research and inspiration -Powered by GPT-4 Vision to interpret charts visually -Hosted on Supabase for performance & caching It’s not meant to replace analysts — just to speed up how traders interpret data. I’m a designer exploring AI tools, and this is my first attempt to turn an idea into a functional product. Would love to know what you think.
Oct 2025 · quantify-ai.co
- 22

8 AIs debated investing. Now build yours in 5 questions.
Jul 2026 · ordinarymantrying.com
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