Empowering Stock Analysis
Based on user reviews
Rating Distribution
EvanKesslerDev
9 days ago
I've been testing Stocknear on the Plus plan for about six weeks now, mainly for my side trading projects. The real-time dark pool trades and congressional portfolios are game-changers; honestly, they give insights TradingView just doesn't touch. Integrated the API into my Python scripts for bulk financial data pulls, saving me hours weekly. AI price predictions are decent, though sometimes off on volatile stocks. Credit limits can bite during heavy screening sessions. Still, great value for devs and traders chasing an edge.
Dr. William Bobos
Dr. William Bobos, with expertise in AI tools, has reviewed Stocknear for Data Analytics and rates it 4.0/5 based on 1 user review. The tool demonstrates particular strength for financial experts who need AI tools capabilities in their workflows.
Pricing: $5 – $360 / month(Updated February 2026)
Free tier (Basic $0/month), Plus and Pro subscription plans (monthly prices not specified on page)
Usage Model: API Calls, Pay-as-You-Go — ensuring you only pay for what you actually use.
With pricing from $5 – $360 / month, Stocknear enables financial experts to access data analytics features through flexible pricing tiers. The structure is designed to scale with your requirements, making it suitable for both small projects and enterprise-level data analytics needs. Evaluate the features and limits of each tier to find the best fit.
Stocknear is a subscription-based AI stock analysis platform providing real-time data for over 6,000 stocks, AI-powered price predictions, stock finder, screeners, earnings transcripts analysis, unique datasets like dark pool trades and congressional portfolios, fundamental data up to 20 years, news, community features, and a monthly portfolio tournament simulator.
Understanding the core functionality and approach of Stocknear.
Pay-as-you-go pricing means Stocknear costs scale with your actual usage. No wasted spend on unused seats or features you don't need yet. Integrations with Plugin/Integration keep work connected.
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SDKs (e.g., Python and JavaScript/TypeScript) help dev teams launch prototypes quickly.
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Analysts use Stocknear to assemble data, explore patterns, and publish findings faster. Analytics and reporting surface the metrics needed to act quickly.
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