StockSignal24 · AI Stock Intelligence Platform
StockSignal24 —
From Figma to
Full-Stack SaaS
Designing and building an AI-powered stock research platform from scratch — condensing 130+ data points into one actionable signal that any investor can understand and act on.
Retail investors were drowning in data — and starving for insight.
Professional traders have Bloomberg terminals. Everyone else has 12 browser tabs, three subscriptions, and no single source of truth. StockSignal24's brief was to change that: build a platform that gives retail investors the same analytical depth — without the complexity or the cost.
Data scattered across a dozen tools
Retail investors were juggling Yahoo Finance, TradingView, Finviz, and SEC filings just to evaluate a single stock. No single tool gave them everything — so research took hours instead of minutes.
AI outputs without explainability
Existing "AI stock pickers" gave a verdict but not a reason. Investors couldn't trust a black-box recommendation — they needed to see the factor scores driving the call.
Technical charts alienated beginners
RSI, MACD, and Bollinger Bands are powerful — but meaningless to most retail investors. The platform needed to translate technical signals into plain English anyone could act on.
No freemium entry point
Competing platforms required a subscription before showing any value. The product needed a generous free tier that let users experience the core AI feature before committing to Pro.
Global audience, single codebase
The platform needed to serve investors in the US, India, and Southeast Asia — with payment infrastructure (Razorpay) and market data pipelines that worked reliably across regions.
Production-ready from day one
No room for a rough MVP. The platform launched publicly with full SEO, structured data, sitemap generation, A/B-testable content, and an admin dashboard — not bolted on later.
Design-first. Ship complete.
Every screen in Figma before a single component was coded. Every feature shipped production-ready — not as an MVP to fix later. Four phases, zero shortcuts.
Product definition & UX strategy
- Defined three distinct user personas: the self-directed investor (research speed), the active trader (signal quality), and the beginner (accessibility)
- Mapped a freemium conversion funnel — which features live on free, which gate to Pro, and where the upgrade prompt appears in the user journey
- Designed the AI score architecture: value, momentum, quality, and growth factors feeding into a single 0-100 signal with narrative explanation
- Wireframed 22 screens in Figma before a single line of code was written — stakeholder sign-off at every stage
Design system & UI
- Built a dark-first design system with consistent token system — colors, type scale, spacing, and component library in Figma
- Designed the AI Analysis card as the hero UI — score, recommendation, factor breakdown, and plain-English summary in one scannable view
- Created 16 distinct feature surfaces: charts, news feed, peer comparison, dividend analysis, risk dashboard, market movers, portfolio, and more
- Accessibility-first from the start: contrast ratios, keyboard navigation, and readable typography for all user levels
Full-stack development
- React 18 + TypeScript + Vite frontend — component-driven architecture with strict separation of UI, data, and business logic
- Supabase backend: Postgres database, Edge Functions for AI analysis pipelines, Row Level Security for user data isolation
- Integrated FMP (Financial Modeling Prep) API for 130+ live data points — real-time quotes, financials, technicals, dividends, and news
- OpenAI integration for the AI narrative layer — structured prompts that synthesise factor scores into plain-English buy/hold/sell reports
- Razorpay payment integration for Pro subscriptions and pay-per-use AI credits
Launch infrastructure & SEO
- Dynamic sitemap generation covering 8,000+ stock pages — each stock URL indexed with schema markup and meta optimisation
- Blog CMS built in-product for organic content — no external CMS dependency, fully admin-managed
- Admin dashboard for subscription management, credit allocation, user analytics, and A/B content testing
- Core Web Vitals monitoring, error logging, and performance budgets enforced from launch day
A complete SaaS — designed, built, and launched.
AI stock analysis engine
130+ data points synthesised into a single 0-100 score with plain-English narrative — powered by OpenAI with structured factor scoring for full transparency.
16 core product features
From real-time charts with 20+ technical indicators to peer comparison, dividend analysis, risk scoring, market movers, and portfolio tracking.
Freemium subscription model
Free tier (2 AI analyses/day), Pro tier ($29/month, unlimited), and pay-per-use AI credits — all managed through Razorpay with automated billing.
Full-stack Supabase backend
Postgres database with Row Level Security, Edge Functions for data pipelines, and real-time subscription handling — zero external backend dependencies.
8,000+ SEO-optimised stock pages
Programmatic SEO for every US-listed stock — dynamic sitemap, structured data, and per-stock meta optimisation for organic discovery at scale.
In-product blog CMS & admin dashboard
A full editorial CMS for the team to publish market content, plus an admin layer for user management, credit allocation, and subscription oversight.
Professional-grade research. Accessible to everyone.
StockSignal24 launched with every feature production-ready — no rough edges, no 'coming soon' sections. The platform serves three distinct investor types from a single codebase, with a freemium model that converts free users into Pro subscribers through genuine product value.
The programmatic SEO layer means every US stock has its own discoverable page — giving the platform a long-tail organic surface that grows without any additional content effort.
Investors who previously pulled PE ratios, RSI, and earnings dates from three different sites now get everything in one AI-synthesised report.
Every recommendation shows the factor scores behind it — value, momentum, quality, growth — so investors understand the signal, not just the verdict.
Plain-English chart explanations and a jargon-free AI summary mean first-time investors and CFA candidates use the same tool differently — and both get value.
"I used to spend Sunday nights manually pulling PE ratios, RSI, and earnings dates from three different sites. StockSignal24 condenses all of that into one score I can actually act on. My research time dropped from 2 hours to 15 minutes."
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