Kavout is a polished AI investing platform featuring its proprietary K-Score (1-9), 8 AI research agents, InvestGPT natural-language analysis, and coverage of 30+ global markets. StoQuant is an open-methodology quant platform that publishes all 149 features, shows the factor-level driver scorecard behind every Q-Score, and maintains an append-only walk-forward accuracy record you can verify in real time.
Kavout's K-Score is a proprietary machine learning equity rating from 1 to 9 that analyzes 200+ factors. The platform is well-designed and offers genuine value — its 8 AI research agents, InvestGPT natural-language analysis, and global market coverage across 30+ countries are impressive. But the K-Score itself is a black box: you see the number, not the factors that drove it, not the model architecture, and no independently verifiable out-of-sample track record. StoQuant takes the opposite approach. The Q-Score (0-100) is built from 149 published features across valuation, momentum, sentiment, analyst ratings, insider activity, ML signals, and Benjamin Graham intrinsic value. Every score comes with a driver scorecard showing which factors contributed and by how much. The entire prediction history is tracked in an append-only accuracy log on /proof — not a backtest from a cherry-picked period, but every single out-of-sample prediction since launch. For investors who need to understand and verify their edge before deploying capital, open methodology is not a nice-to-have — it is the only way to trust the signal.
| Feature | StoQuant | Kavout |
|---|---|---|
| Price | Free core tier; Power plan for full API + MCP access | Free (limited); Pro $16-20/mo, Premium $39/mo |
| Free tier limits | Full Q-Score, hidden gems, and public research pages | 10 research credits/month, limited market coverage |
| Stocks covered | 3,500+ US stocks scored weekly | 30+ global markets (stocks, ETFs, crypto, forex) |
| Core scoring / key differentiators | 149-feature ML ensemble with Venn-ABERS calibration | K-Score 1-9 from 200+ proprietary factors (black-box) |
| ML / walk-forward proof | Published daily on /proof | Backtested estimates shown; no published append-forward validation |
| AI-agent / MCP support | stoquant-mcp for Claude / AI agents | No |
| Portfolio optimization | Black-Litterman optimizer | Portfolio Toolbox (Premium tier) |
| Data sources | 14 alt-data feeds (insider, social, macro, SEC, app ranks) | 200+ factors: fundamentals, technicals, sentiment, insider, global data |
Kavout operates on a credit-based model: Free tier gives you 10 research credits per month, Pro gives 1,000, and Premium gives 3,000. Each deep AI research query consumes approximately 10 credits. If you actively research stocks, you will hit these limits. StoQuant gives you unlimited Q-Score lookups, Hidden Gems screening, and research page access for free. There are no credits to track, no per-query costs, no surprises. The only paid tier is the Power plan, which adds the MCP server, Black-Litterman portfolio optimizer, and API access — not the core scoring and screening you need for day-to-day research. For an investor who screens dozens of stocks weekly, the credit cost of Kavout adds up fast. StoQuant's unlimited free core is a significant practical advantage.
Kavout covers 30+ global markets including US, Canada, UK, Europe, Australia, Asia, and crypto/forex. This is a genuine strength for international investors. StoQuant focuses on US-listed stocks (3,500+ names scored weekly) with a particular emphasis on the $250M-$10B small-cap range where Benjamin Graham value methodology is most effective. If your portfolio requires international equity coverage or crypto exposure, Kavout is the better fit. If you focus on US small-cap value investing with transparent, verifiable signals, StoQuant's depth and open methodology are unmatched.
Explore the Q-Score methodology (stoquant.com/learn/q-score-methodology), walk-forward validation (stoquant.com/learn/walk-forward-validation), the Hidden Gems screener (stoquant.com/gems), and the proof dashboard (stoquant.com/proof).
Kavout offers broad global coverage and a polished AI agent experience, but its K-Score is a proprietary black box with no independently verifiable track record. StoQuant publishes everything — all 149 features, driver scorecards, and append-only walk-forward validation — so you can verify every claim. StoQuant is also free for core features, while Kavout uses a credit-based system with per-query costs.
No. Kavout's K-Score is a proprietary black-box rating. You see the 1-9 score without knowing which factors drove it. StoQuant's Q-Score shows a full driver scorecard revealing the contribution of each of the 9 dimensions (valuation, momentum, sentiment, ML, insider, etc.).
StoQuant currently focuses on US-listed stocks scored weekly across 3,500+ names. Kavout covers 30+ global markets including international equities, ETFs, crypto, and forex. If international coverage is critical to your strategy, Kavout is the stronger choice.
StoQuant is free for all core features — Q-Score, screens, research pages. Kavout's Free tier gives only 10 research credits/month; Pro ($16-20/mo) gives 1,000 credits and Premium ($39/mo) gives 3,000. For active researchers, StoQuant's unlimited free tier is significantly more cost-effective.
Kavout states that its K Score-9 portfolios outperform K Score-1 portfolios with an estimated 4.84% alpha overlay, but explicitly labels this an estimate. No independently audited append-forward walk-forward record is publicly available. StoQuant publishes daily append-forward validation metrics on /proof for every prediction.
Daily Q-Score changes, insider buy clusters, and ML forecast updates for the tickers you follow. Email only, no account needed. See a sample digest.