Alternatives
Products that do what Neverbell, an AI agent that analyzes markets and executes trades does
Hi HN, we're developing Neverbell, an AI agent that combines market analysis with trade execution. One of our beta testers said to Neverbell: “Protect my downside, but don’t be too conservative.” Volatility increased a few days later, and the agent decreased their exposure. Our tester wasn’t happy. The interesting part for us was that both interpretations were reasonable. The agent gave more weight to “protect my downside.” The user thought that “don't be too conservative” was more important. It changed the way we built Neverbell. Now, if the agent sees any instructions that conflict, it…
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We’re thrilled to announce the launch of our AI-powered stock market analyst chatbot, designed to help you analyze stocks and gain valuable market insights with ease. Our intuitive conversational chat interface makes it simple for anyone to get started. Why You’ll Love It: Our AI Analyst uses a long-term value-growth investing strategy, similar to those employed by legendary investors like Warren Buffett, Mohnish Pabrai, Phil Town and Charlie Munger. It’s built to provide you with thorough, data-driven analysis to help you make informed investment decisions. Key Features: - Comprehensive…
2024 · decodeinvesting.com
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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
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We created autonomous AI Agents that monitor the stock market for you while you go about your day. How it works: Tell our AI Assistant what you want to monitor, and it creates a project for our team of autonomous AI Agents. You'll get notifications (email + app) when significant events matching your criteria are detected. For short-term projects, you'll be notified when your analysis is ready. Behind the scenes: When you give the AI Assistant a request to monitor an entity (like a stock or group of stocks), an AI Project Manager plans the project and breaks the project down into manageable…
2024 · decodeinvesting.com
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Hey HN, For the past few years, I've been obsessed with trying to get AI to produce accurate trading signals. The main challenges I found with AI trading models are lack of consistency, context window bottlenecks, hard to backtest, and high cost. Asking ChatGPT "Should I buy Bitcoin today?" doesn't work well because the LLM doesnt have a set trading strategy to opperate from. In addition, the small context window makes it challenging to fit enough historical data into. Not to mention it gets very expensive as well. My solution is a hybrid approach. Instead of having the LLM make direct…
2025 · trend.fi
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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
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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
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Aug 2026 · quantsignals.xyz
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I built this simulator to study how simple trading agents interacting with an order book can create emergent patterns—volatility, clustering, even chaos—without any external shocks. It’s meant as both a research toy and teaching tool. You can run different strategies, adjust configs, and watch dynamics evolve. Curious to hear feedback from the HN crowd on features/dynamics you’d like to see added.
2025 · aitradingsim.com
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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
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