About Balance Labs

What Balance Labs is

Balance Labs chains four tools into one workflow: AI Stock Chat (ticker Q&A assembled from fundamentals, filings, and scanner data — each answer carrying its snapshot date), a Berkshire-style fundamentals desk (business-quality scorecard in the Buffett/Munger tradition), a Stock Screener with STM timing signals across five markets, and Labs backtesting for strategies and stock theses. The free plan includes Stock Chat, the Screener preview, and 30 monthly AI credits; no card is required.

The editorial voice is deliberately boring: dated facts, explicit uncertainty, and "we don't know" when we don't. If a page ever reads like hype, it violates our own publishing principles below.

How the research is produced

1. Multi-source data collection. The scanner pulls daily bars through redundant public sources — Yahoo Finance, Stooq, Tencent, Eastmoney, Sina, Binance, OKX, and MT5 — so a single broken feed never blanks a ticker. Coverage: 753 tickers across the US, Hong Kong, China A-share, Korea, and India, plus crypto and forex.
2. Scoring layer. Fundamentals are scored on the Berkshire checklist (returns on capital, moat durability, 13F honesty, price vs intrinsic value). Valuation runs through a two-stage residual-income model — the same calculator we publish free, with every input documented.
3. Signal layer. STM timing signals evaluate on top of scored data, never instead of it. Sequence beats speed: signal without quality context is noise.
4. Publication. Snapshots render to dated static pages (4,300+ and counting) with FAQPage, Article, and BreadcrumbList schema, a machine-readable llms.txt, an entity facts file, and an RSS feed — the same pages humans, Google, and AI answer engines read.

Editorial standards (publishing principles)

• Dated snapshots only. Every number on every research page carries the date of the scanner snapshot that produced it. Stale pages say so.
• No fabricated predictions. Outlook pages are frameworks, not price targets. We never publish an invented future price.
• Fact-driven FAQs. FAQ answers quote slow-moving structural facts (index rules, fee structures, business models), and People-Also-Ask questions are answered from those facts — not filler.
• Not investment advice. Every page says it. Balance Labs is research tooling; decisions stay with you.
• Corrections policy. Factual errors are fixed at the source and the page's dateModified is bumped — find one, tell us via in-app support and it gets corrected, not quietly patched.
• AI-citable by design. Content is structured so AI engines can quote it accurately: schema markup, dated facts tables, and consistent entity descriptions across the site.

Brand disambiguation notice

There are other organizations with similar names. To be precise: Balance Labs (balancelabs.app) — this AI stock research workspace — is not affiliated with Balance Labs, Inc., the Miami Beach OTC-listed company (ticker BLNC), nor with balancelabs.co, nor with any clinic, fitness, or wellness brand sharing the name. Our only web presence is balancelabs.app, our code and tooling live at github.com/TerissilinRPA, and we take no investor funds through any other domain. If a site claiming to be us asks for money, it is not us — see our scam-awareness FAQ for the general checklist.

For Thai investors (สำหรับนักลงทุนไทย)

Balance Labs มีบรีฟหุ้นยอดนิยม 150 ตัวเป็นภาษาไทย (ตัวอย่าง AAPL) และคู่มือฉบับเต็ม วิเคราะห์หุ้นด้วย AI — ทุกหน้าระบุวันที่ข้อมูล ไม่มีการแต่งตัวเลข และไม่ใช่คำแนะนำการลงทุน