The financial world is undergoing a profound transformation, driven by the explosive growth of artificial intelligence (AI). With AI investments reaching $142.3 billion in 2023, and the market projected to hit $200 billion by 2025, businesses are racing to incorporate AI into their core strategies. For 83% of companies, AI has become a top priority, reshaping how decisions are made and creating new opportunities for innovation, particularly in the financial sector, where machine learning now powers 62% of AI initiatives.
Startups are using AI to change the way people think about investing and open up more financial options than before. These forward-thinking businesses use machine learning algorithms to evaluate enormous datasets and provide individualised investment recommendations based on each client’s risk tolerance and objectives. By forecasting market trends, optimising portfolios, and automating trading procedures, AI-driven platforms enable users to make well-informed decisions. Furthermore, natural language processing is being used to develop user-friendly chatbots and virtual advisers that provide interesting and approachable financial advice.

Kavout (Seattle, Washington)
Founder: Alex Lu
How They Use AI
- K Score Predictive Rating: Kavout’s AI-powered K Score analyzes over 200 factors to provide highly accurate equity ratings, guiding investors with actionable buy/sell signals.
- Cutting-Edge Machine Learning Models: Kavout uses advanced AI models, including deep learning and Bayesian techniques, to uncover hidden patterns in financial markets, enhancing strategy and performance.
- Alternative Data Insights: The company processes vast amounts of traditional and alternative data, extracting key insights from sources like social media and news, providing deeper market understanding.
- Custom AI Solutions with KaaS: Kavout’s Kai as a Service (KaaS) allows clients to access pre-built models and develop customized AI solutions for tailored investment strategies.
- Risk Mitigation and Alpha Generation: Kavout’s AI tools generate signals to increase alpha while reducing risk exposure, helping investors manage volatility and protect against downside.
Alphasense (New York, NY)
Founder: Jack Kokko
How They Use AI
- AI-Driven Expert Insights for Investment: AlphaSense uses AI to analyze and summarize expert call transcripts, helping investors quickly surface relevant insights and make faster, more informed investment decisions.
- Advanced Search for Deeper Analysis: With Smart Synonyms™ and sentiment analysis, AlphaSense expands search capabilities beyond exact matches, uncovering hidden insights and market sentiment that are crucial for strategic investment analysis.
- Generative AI for Efficient Summarization: AlphaSense’s Smart Summaries leverage AI to provide concise, actionable summaries from millions of expert transcripts, enabling investors to efficiently capture key market trends and SWOT analyses.
- Real-Time AI Chat for Investment Queries: The AI-powered AskTegus platform allows investors to ask real-time questions and get instant insights from a large transcript library, accelerating research and decision-making in dynamic markets.
- Personalized AI-Driven Alerts: Machine learning curates and delivers personalized insights and alerts on new expert transcripts, helping investors stay ahead of market trends and shifts, making AlphaSense an essential tool for proactive investment strategies.
Numerai (San Francisco, California)
Founder: Richard Craib
How They Use AI
- Crowdsourced AI Models: Numerai provides encrypted financial data to a global network of data scientists, who use machine learning to build predictive models for stock market movements.
- AI-Driven Stock Predictions: Numerai turns stock market prediction into a data science problem, allowing participants to focus solely on model-building using AI without needing financial expertise.
- Blockchain and Incentives: Data scientists stake Numeraire (NMR) tokens on their models, incentivizing accuracy through rewards for well-performing predictions and penalties for underperformance.
- Collective Intelligence for Trading: Numerai aggregates AI-driven models from thousands of data scientists to create a collective, more accurate investment strategy for stock trading.
- Outperformance Potential: Numerai’s AI-powered approach reportedly generated a 20% return during a financial downturn, showcasing its potential to outperform traditional hedge funds.
IntoTheBlock (USA)
Founders: Jesús Rodriguez, Alfredo Terrero, and Leonard Boord
How They Use AI
- AI-Driven Crypto Market Insights: IntoTheBlock uses AI to analyze both on-chain and off-chain data, offering investors comprehensive insights into the cryptocurrency market.
- Predictive Analytics for Crypto: The platform employs machine learning models to forecast crypto asset prices and market trends, helping investors make data-driven decisions.
- Risk Assessment and Portfolio Optimization: AI algorithms evaluate cryptocurrency risks and optimize portfolios based on individual risk tolerance and investment goals.
- Sentiment and On-Chain Analysis: IntoTheBlock’s AI tools analyze social media, news, and blockchain data to gauge market sentiment and derive insights on wallet behaviors and transaction patterns.
- AI-Powered Trading Signals and DeFi Analytics: The platform generates trading signals for crypto entry and exit points, while also providing AI-driven insights into decentralized finance (DeFi) protocols, liquidity, and yields.
Trade Ideas (Encinitas, California)
Founder: Daniel Mirkin
How They Use AI
- Real-Time Market Scanning: Trade Ideas uses AI algorithms to continuously scan the market, offering real-time insights for trading opportunities.
- AI-Driven Trade Suggestions: The platform’s AI system, “Holly,” generates trade ideas by analyzing market data and applying various strategies and risk parameters.
- Automated Trading and Risk Management: Trade Ideas supports AI-assisted automated trading and uses AI to monitor and manage positions, providing real-time risk assessments.
- Strategy Testing and Performance Analytics: The platform offers AI-powered strategy testing and performance analysis, helping users refine and optimize their trading strategies.
- Personalized Insights and Sentiment Analysis: Trade Ideas’ AI learns from user trading patterns to provide tailored recommendations and incorporates market sentiment analysis into its trading suggestions.
Tickeron
Founder: Sergey Savastiouk
How They Use AI
- AI-Powered Trading Bots: Tickeron’s AI robots generate real-time trading signals, execute trades, and provide alerts based on one-minute delayed data, offering a hands-free trading experience.
- AI Trend Predictions and Pattern Recognition: Tickeron uses machine learning to analyze market trends, predict entry/exit prices, and identify profitable chart patterns with confidence levels, assisting traders in making data-driven decisions.
- AI Stock Screener and Real-Time Analysis: The AI stock screener analyzes stocks, providing real-time entry/exit price suggestions and expert market analysis to help investors pick the right trades.
- AI-Driven Portfolios: Tickeron uses AI to manage active stock and ETF portfolios, mimicking hedge fund strategies, and also helps create AI-based model portfolios optimized for asset allocation.
- Educational and Marketplace Tools: Tickeron offers AI-powered educational resources, including 1-on-1 lessons, and a marketplace for sharing and reviewing AI-generated trade ideas and strategies.
Accern
Founder: Kumesh Aroomoogan, Anshul Vikram Pandey
How They Use AI
- Natural Language Processing (NLP) for Financial Data: Accern utilizes AI-powered NLP to analyze unstructured text from sources like news, social media, and financial filings, enabling the extraction of relevant financial insights at scale.
- Automated Research and Analysis: The platform automates the identification of actionable insights from vast amounts of unstructured data, minimizing human error and allowing analysts to focus on higher-value tasks.
- Sentiment and Relevance Analysis: Accern’s AI conducts sentiment analysis on financial news and social media to gauge market sentiment around companies, assessing the relevance of information to specific investment goals.
- Event Detection and Impact Analysis: The platform identifies significant events (e.g., mergers, interest rate changes) and analyzes past impacts on portfolios to predict potential future effects on investments.
- No-Code AI Platform and Real-Time Insights: Accern offers a no-code platform for financial professionals to quickly build custom AI models tailored to investment strategies, providing real-time analysis and alerts for timely decision-making.
Vice
Founder: Samir Vasavada, Runik Mehrotra
How They Use AI
- Personalized Portfolio Construction: Vise utilizes AI to create customized portfolios tailored to each client’s financial goals, risk tolerance, and preferences, including specific needs like ESG values and concentrated positions.
- Automated Tax Optimization: The platform employs AI for daily tax-loss harvesting, minimizing tax liabilities for clients and enhancing overall portfolio performance.
- Intelligent Rebalancing: Vise’s AI algorithms automatically maintain and rebalance portfolios, ensuring alignment with the client’s investment strategy and goals.
- AI-Powered Insights: Advisors receive instant AI-generated insights that aid in understanding and explaining investment decisions, allowing for quick responses to client inquiries.
- Scalable Customization and Efficient Management: Vise leverages AI to facilitate highly customized portfolio management at scale, automating time-consuming tasks so advisors can focus on client relationships and complex financial planning.