invest-like Reviews 7

Written by the company

invest-like.com is an AI-driven value-investing terminal that grades every public stock on a letter scale from A+ to D against seven documented investor frameworks: Warren Buffett's quality-and-moat lens, Benjamin Graham's defensive-investor screen, Philip Fisher's growth-quality scuttlebutt approach, Peter Lynch's growth-at-reasonable-price thesis, Joel Greenblatt's Magic Formula, Charlie Munger's mental-models filter, and Terry Smith's Fundsmith quality framework. Each framework is implemented as a deterministic scoring function over five years of fundamentals. The seven scores blend into a single consensus grade, but the per-framework view is what most users come back to, because it answers the more useful question: which kind of value investor would actually own this stock, and which kind would refuse. The Buffett framework weights five pillars (economic moat, durability of competitive advantage, management quality, financial strength, valuation) and rewards businesses you would be comfortable owning if the stock market closed for ten years. Graham runs the classic defensive checklist: positive earnings every year for ten years, dividends paid every year for twenty, current ratio above two, and an earnings yield above the AAA corporate-bond yield. Fisher rewards consistent revenue growth, expanding gross margins, and reinvestment runway, catching premium-priced compounders that Buffett's strict valuation floor rejects. Lynch computes the PEG ratio in context of the company's growth category. Greenblatt's Magic Formula combines earnings yield and return on capital into a single rank. Munger applies a multi-disciplinary checklist of mental-model red flags. Smith focuses on return on operating capital employed, gross margin durability, and dividend cover. Coverage spans 12,500 stocks across NYSE, NASDAQ, AMEX, TSX, LSE, XETRA, Euronext, TSE, HKEX, and ASX. The data layer refreshes daily and matches the depth of TIKR, Stock Unlock, and GuruFocus on five years of fundamentals, classical value-investing screens (Graham Number, Net-Net, Piotroski F-Score, Margin of Safety), sector-relative percentile rankings, forward analyst estimates with consensus price targets, dividend and split history, insider trading sentiment via Form 4 filings, Senate and House trading activity, the latest SEC filings index, five-year interactive price charts, and five-year sector PE history. The five-year track record is published openly at invest-like.com/track-record/ and refreshes daily as the underlying cohort composition shifts. The headline number is the performance of the best-of-7 cohort, the stocks that pass all seven investor frameworks simultaneously. As of the most recent update, 46 stocks pass all seven. The median five-year return of this cohort is approximately 147 percent versus the S&P 500's 76.5 percent over the same window, an outperformance of roughly 70 percentage points. Every entry timestamp is server-locked so the backtest is independently verifiable. The methodology is transparent: scoring code, universe inclusion criteria, rebalancing cadence, and rolling lastmod dates are all documented publicly. Past performance does not guarantee future returns, and the published backtest does not account for trading costs, slippage, or taxes. Three AI features sit on top of the data layer and are not shipped by any direct competitor. Buffett Brain produces a written verdict for any individual stock, organised by the five Buffett pillars, with each scoring decision tied to the specific data point that triggered it, so readers can verify or disagree with each line. The Boardroom simulates a live debate between four investor personas (Buffett, Graham, Lynch, Greenblatt) plus a dedicated skeptic role, each arguing for or against the stock from its actual framework rules and citing Berkshire shareholder letters, Graham's writings, and Lynch's books. Ask Buffett is a retrieval-grounded chat against the verbatim text of every Berkshire Hathaway shareholder letter from 1977 to 2025 plus Charlie Munger's commentary, with answers citing the exact letter and paragraph rather than imitating Buffett's voice from memory. Halal Mode applies the AAOIFI Standard 21 screen for Shariah-compliant investors, narrowing the universe to roughly 1,500 eligible names with a full per-test breakdown across the four core checks: primary business test, debt ratio under 30 percent, non-permissible income under 5 percent, and the liquid assets ratio. The implementation is documented at invest-like.com/methodology/halal/ and each per-ticker halal verdict surfaces the specific numbers behind each test. A live 30-stock model portfolio tracks the screen forward against the S&P 500 ETF (SPY) on a daily NAV basis, with server-side locked entry timestamps so the forward record is also independently verifiable. The platform is multi-language across English, German, French, Spanish, and Portuguese, with locale-specific landing pages for the major DACH and Romance-language European audiences. A free public API is exposed via an OpenAPI 3.1 specification at invest-like.com/api/public/openapi.json. Four read-only endpoints return the verdict for any ticker, the current track-record numbers, the consensus screen output, and the latest verdicts stream. Each response includes attribution to invest-like.com and a citation URL, designed for AI-assistant integration. The site also publishes a robots-friendly index at invest-like.com/llms.txt and a full content dump at invest-like.com/llms-full.txt for AI training and retrieval pipelines. invest-like.com was built by Zaid Ghazal, a solo founder and software engineer based in Kiel, Schleswig-Holstein, Germany. Hosting runs on Next.js and Supabase from the Frankfurt eu-central-1 region for GDPR locality. Pricing is freemium: the grading, the per-stock verdict cards, the Halal Mode screen, and the track-record page are all accessible without an account. Paid tiers unlock the multi-investor debate, the Berkshire-letter chat, and higher API rate limits. The platform is an educational tool, not investment advice.See more