Alternatives
Products that do what APEX — Institutional Grade Due Diligence does
Free AI due dilligence - Goldman Sachs quality in 30 seconds
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Free Hedge Fund Systemic Risk Data & Financial Calculators
17d ago · hedgefundmonitor.com
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Share your LinkedIn. Receive a decision + reasoning in 24h.
Dec 2025
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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
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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
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Most mortgage processing delays aren’t due to risk — they’re due to manual workflows. We’ve been working on SimplAI, an AI-driven system designed for banking and financial services, starting with mortgage operations. The problem we kept seeing: 15–22 day processing timelines Heavy manual document handling (500+ pages per loan) Repetitive data entry + verification loops Underwriters spending hours on non-decision work So we built a set of AI agents that handle the operational layer: Document AI (IDP) → classifies + extracts data from loan docs in minutes Income analysis models → parse tax…
Mar 2026 · app.simplai.ai
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Apr 2026 · developer.stockfit.io
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Hey HN! I've always been fascinated by financial markets. This month, I decided to build a tool to help with the research of stocks and cryptocurrencies. I'm using YFinance as a data source because it's free and provides a wide range of reliable market data. For sentiment analysis, I'm leveraging Google Trends to gauge public interest and sentiment over time. The tool, named Zenith, is a command-line utility with four main features: Market Analysis: Provides insights like moving averages, RSI, and volatility for selected stocks or cryptocurrencies. Sentiment Analysis: Uses Google Trends to…
2024 · github.com
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Hey HN, I started my career as a finance manager, transitioned into product management, and now I’m building my own products. Back in my finance days, while managing a £6M budget, I uncovered a £15k leak hiding in plain sight: FX fees. Today, I see solo founders making the exact same mistake. I realised most founders are quietly losing 2-5% of their revenue to what I call the Lazy Tax: - Stripe's ~2% auto-conversion fee on inbound revenue, - plus their local bank's ~3% spread when paying for global SaaS tools (AWS, Claude, Ads). So I built FixMyFX to show founders their exact leak and how to…
Apr 2026 · fixmyfx.com
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Built a free open source agentic CLI tool for financial modeling & analysis. Hadn't played around with real equity valuation modeling for awhile and wanted to build tooling to get myself back into the game. Bull.sh lets you query & store 10-Qs, 10-K in a local vector store to chat with them, build investment thesis from scratch or build full framework models through the CLI to export into excel. It's open source, just requires your own Anthropic API key and (optionally) AlphaVantage Free API key if you want save some tokens from scraping. Feel free to play around with it. Some ideas I have…
Jan 2026 · github.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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I've developed a web app that organizes financial statements from SEC. There are similar products on the Internet, but all of them I found just "abstracts" raw information into something. For example, typical website has "Revenue" as a top-line metrics. In reality, that can be "Total Revenue", "Net Sales", "Operating Revenue", and so on. Those website can't cover exceptional values in same reason. I believe serious investors need raw financial statements aggregated because each number reflect the companies' financial performance. Major platforms like Bloomberg does that but too expensive for…
2024 · finboard.net
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