Global Stock Market Data. More than 150 pricing sources, including biggest world stock exchanges. Pay only for the stock exchanges, parameters or regions you need. Flexible in customizing our product to the customer's needs. Free test access as long as you need for integration. Reliable sources: stock exchanges and market participants. The cost depends on the amount of required parameters and re-distribution right.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Context

The algorithmic trading space is buzzing with new strategies. Companies have spent billions in infrastructures and R&D to be able to jump ahead of the competition and beat the market. Still, it is well acknowledged that the buy & hold strategy is able to outperform many of the algorithmic strategies, especially in the long-run. However, finding value in stocks is an art that very few mastered, can a computer do that?

Content

This Data repo contains two datasets:

1. Example_2019_price_var.csv. I built this dataset thanks to Financial Modeling Prep API and to pandas_datareader. Each row is a stock from the technology sector of the US stock market (that is available from the aforementioned API, which is free and highly recommended). The column contains the percent price variation of each stock for the year 2019. In other words, it collects the percent price variation of each stock from the first trading day on Jan 2019 to the last trading day of Dec 2019. To compute this price variation I decided to consider the Adjusted Close Price.

2. Example_DATASET.csv. I built this dataset thanks to Financial Modeling Prep API. Each row is a stock from the technology sector of the US stock market (that is available from the aforementioned API). Each column is a financial indicator that can be found in the 2018 10-K filings of each company. There are no Nans or empty cells. Furthermore, the last column is the CLASS of each stock, where:

   1. class = 1 if the price of the stock increases during 2019
   2. class = 0 if the price of the stock decreases during 2019

In other words, the last column is used to classify each stock in buy-worthy or not, and this relationship is what should allow a machine learning model to learn to recognize stocks that will increase their value from those that won't.

NOTE: the number of stocks does not match between the two datasets because the API did not have all the required financial indicators for some stocks. It is possible to remove from Example_2019_price_var.csv those rows that do not appear in Example_DATASET.csv.

Inspiration

I built this dataset during the 2019 winter holidays period, because I wanted to answer a simple question: is it possible to have a machine learning model learn the differences between stocks that perform well and those that don't, and then leverage this knowledge in order to predict which stock will be worth buying? Moreover, is it possible to achieve this simply by looking at financial indicators found in the 10-K filings?

The best choice for those looking for license-free US market data for commercial use is US Equities Basic, which includes data display, redistribution, professional trading, and more.

US Equities Basic is based upon a derived IEX feed. The volume coverage is 3-5% of the total trading volume in North America, which helps entities mitigate license expenses and start with real-time data.

US Equities Basic provides raw quotes, trades, aggregated time series (OHLCV), and snapshots. Both REST API and WebSocket API are available.

End-of-day price information disseminated after 12:00 AM EST does not require licensing in the United States by law. This applies to all exchanges, even those not included in the US Equities Basic. Finazon combines all price information after every trading day, meaning that while markets are open, real-time prices are available from a subset of exchanges, and when markets close, data is synced and contains 100% of US volume. All historical prices are adjusted for corporate actions and splits.

Tip: Individuals with non-professional usage are not required to get exchange licenses for real-time data and, hence, are better off with the US Equities Max dataset.

Twelve Data is a technology-driven company that provides financial market data, financial tools, and dedicated solutions. Large audiences - from individuals to financial institutions - use our products to stay ahead of the competition and success.

At Twelve Data we feel responsible for where the markets are going and how people are able to explore them. Coming from different technological backgrounds, we see how the world is lacking the unique and simple place where financial data can be accessed by anyone, at any time. This is what distinguishes us from others, we do not only supply the financial data but instead, we want you to benefit from it, by using the convenient format, tools, and special solutions.

We believe that the human factor is still a very important aspect of our work and therefore our ethics guides us on how to treat people, with convenient and understandable resources. This includes world-class documentation, human support, and dedicated solutions.

This dataset offers both live (delayed) prices and End Of Day time series on equity options

1/ Live (delayed) prices for options on European stocks and indices including: Reference spot price, bid/ask screen price, fair value price (based on surface calibration), implicit volatility, forward Greeks : delta, vega Canari.dev computes AI-generated forecast signals indicating which option is over/underpriced, based on the holders strategy (buy and hold until maturity, 1 hour to 2 days holding horizon...). From these signals is derived a "Canari price" which is also available in this live tables.
Visit our website (canari.dev ) for more details about our forecast signals.

The delay ranges from 15 to 40 minutes depending on underlyings.

2/ Historical time series: Implied vol Realized vol Smile Forward
See a full API presentation here : https://youtu.be/qitPO-SFmY4 .

These data are also readily accessible in Excel thanks the provided Add-in available on Github: https://github.com/canari-dev/Excel-macro-to-consume-Canari-API

If you need help, contact us at: contact@canari.dev

User Guide: You can get a preview of the API by typing "data.canari.dev" in your web browser. This will show you a free version of this API with limited data.

Here are examples of possible syntaxes:

For live options prices: data.canari.dev/OPT/DAI data.canari.dev/OPT/OESX/0923 The "csv" suffix to get a csv rather than html formating, for example: data.canari.dev/OPT/DB1/1223/csv For historical parameters: Implied vol : data.canari.dev/IV/BMW

data.canari.dev/IV/ALV/1224

data.canari.dev/IV/DTE/1224/csv

Realized vol (intraday, maturity expressed as EWM, span in business days): data.canari.dev/RV/IFX ... Implied dividend flow: data.canari.dev/DIV/IBE ... Smile (vol spread between ATM strike and 90% strike, normalized to 1Y with factor 1/√T): data.canari.dev/SMI/DTE ... Forward: data.canari.dev/FWD/BNP ...

List of available underlyings: Code Name OESX Eurostoxx50 ODAX DAX OSMI SMI (Swiss index) OESB Eurostoxx Banks OVS2 VSTOXX ITK AB Inbev ABBN ABB ASM ASML ADS Adidas AIR Air Liquide EAD Airbus ALV Allianz AXA Axa BAS BASF BBVD BBVA BMW BMW BNP BNP BAY Bayer DBK Deutsche Bank DB1 Deutsche Boerse DPW Deutsche Post DTE Deutsche Telekom EOA E.ON ENL5 Enel INN ING IBE Iberdrola IFX Infineon IES5 Intesa Sanpaolo PPX Kering LOR L Oreal MOH LVMH LIN Linde DAI Mercedes-Benz MUV2 Munich Re NESN Nestle NOVN Novartis PHI1 Philips REP Repsol ROG Roche SAP SAP SNW Sanofi BSD2 Santander SND Schneider SIE Siemens SGE Société Générale SREN Swiss Re TNE5 Telefonica TOTB TotalEnergies UBSN UBS CRI5 Unicredito SQU Vinci VO3 Volkswagen ANN Vonovia ZURN Zurich Insurance Group

Twelve Data is a technology-driven company that provides financial market data, financial tools, and dedicated solutions. Large audiences - from individuals to financial institutions - use our products to stay ahead of the competition and success.

At Twelve Data we feel responsible for where the markets are going and how people are able to explore them. Coming from different technological backgrounds, we see how the world is lacking the unique and simple place where financial data can be accessed by anyone, at any time. This is what distinguishes us from others, we do not only supply the financial data but instead, we want you to benefit from it, by using the convenient format, tools, and special solutions.

We believe that the human factor is still a very important aspect of our work and therefore our ethics guides us on how to treat people, with convenient and understandable resources. This includes world-class documentation, human support, and dedicated solutions.

Free-Cash-Flow-To-Equity Time Series for Api Group Corp. APi Group Corporation provides safety and specialty services worldwide. The company offers end-to-end integrated occupancy systems, such as fire protection services; heating, ventilation, and air conditioning solutions; and entry systems, elevators, and escalators, including design, installation, inspection, and service of these integrated systems. It also provides various infrastructure and specialized industrial plant services comprising maintenance and repair of underground electric, gas, water, sewer, and telecommunications infrastructure; engineering and design, fabrication, installation, maintenance service and repair, retrofitting and upgrading, pipeline infrastructure, access and road construction, supporting facilities, and integrity management and maintenance. The company serves commercial, education, healthcare, high tech, industrial, and special-hazard settings, as well as private and public utilities, communications, healthcare, education, transportation, manufacturing, industrial plants and governmental agencies. The company was formerly known as J2 Acquisition Limited and changed its name to APi Group Corporation in October 2019. APi Group Corporation was founded in 1926 and is headquartered in New Brighton, Minnesota.

Our dynamic data offering is designed to provide a comprehensive view of over 108,000 publicly listed companies across the globe. This service is an essential tool for financial analysts, investors, corporate strategists, and market researchers, offering versatile data delivery options.

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Enhance investment strategies with diverse and up-to-date data. Conduct in-depth market research and competitive analysis. Facilitate strategic planning and risk assessment with varied data access methods. Support academic research with a reliable data source. Ideal for:

Investment and Financial Firms Market Analysts and Economists Corporate Strategy and Business Development Teams Academic Researchers in Finance and Economics

Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.

Key Features of Success.ai's Company Financial Data:

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Why Choose Success.ai for Company Financial Data?

Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.

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Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.

Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.

Comprehensive Use Cases for Financial Data:

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Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.

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What Sets Success.ai Apart?

Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.

Ethical Practices: Our data collection and processing methods are fully comp...

Access the American Petroleum Institute's (API) Weekly Statistical Bulletin (WSB), providing essential data for the US and regional petroleum markets.

PowerMap U.S. is an innovative trading solutions, specializing in order flow analytics on U.S. Stock market. With its AI-inferred proprietary algorithm trained on market data, TradePulse predicts stock flow on using trade volume and buy intensity providing an additional key metric for decision-making while providing catalogue of alternative dataset on its platform.

Key Features: 💠 AI-driven order flow prediction based on trade volume and buy-side intensity 💠 Proprietary algorithms trained on historical and real-time U.S. equity data 💠 Real-time analytics across major U.S. exchanges (NYSE, NASDAQ, etc.) 💠 Integrated dashboard with visual flow indicators and trend detection 💠 Access to alternative datasets curated for quantitative and discretionary strategies 💠 Customizable signals aligned with trading styles (momentum, mean-reversion, etc.) 💠 Scalable infrastructure suitable for institutional-grade workflows

Primary Use Cases: 🔹 U.S.-focused hedge funds leveraging inferred flow data for intraday alpha 🔹 Quantitative traders integrating buy-side pressure metrics into models 🔹 Execution teams identifying optimal entry/exit points through real-time flow signals 🔹 Asset managers enhancing conviction through AI-derived trade behavior insights 🔹 Research analysts and PMs utilizing alternative datasets for cross-validation of ideas

Contact us for a real time order flow data in different markets. Stay ahead with TradePulse's order flow insights.

The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.

Snapshot img

Financial Planning Software Market Size 2024-2028

The financial planning software market size is forecast to increase by USD 8.67 billion at a CAGR of 23.55% between 2023 and 2028.

The market is experiencing significant growth, driven by the increasing complexity of financial management and the integration of artificial intelligence (AI) technology. As businesses continue to manage increasingly intricate financial operations, the demand for advanced planning tools is on the rise. Moreover, AI's ability to analyze vast amounts of data and provide actionable insights is revolutionizing financial planning, enabling more accurate forecasting and efficient resource allocation. However, market expansion is not without challenges. Regulatory hurdles impact adoption, as financial institutions grapple with compliance requirements and data privacy and security concerns. The sensitive nature of financial data necessitates robust security measures, and breaches can result in severe consequences.
Supply chain inconsistencies also temper growth potential, as businesses require reliable and continuous access to software solutions to remain competitive. Companies seeking to capitalize on market opportunities must navigate these challenges effectively, investing in robust security frameworks and maintaining strong supplier relationships to ensure uninterrupted access to cutting-edge financial planning software.

What will be the Size of the Financial Planning Software Market during the forecast period?

Request Free Sample

In the dynamic market, asset allocation and retirement planning remain key focus areas for both personal and institutional investors. Financial technology has disrupted traditional financial services, giving rise to online financial planning, personal finance apps, and digital banking solutions. These tools offer real-time financial insights, goal setting capabilities, and API integrations for seamless data exchange. Financial strategies are increasingly data-driven, with financial analysis, forecasting, and modeling software enabling informed decision-making. Wealth management and portfolio management software cater to high net worth individuals, while financial consulting services provide expert advice on complex financial matters. Financial regulations continue to shape the market, with a growing emphasis on data security and open banking.
Digital financial services, including investment planning and tax planning software, offer accessible financial solutions for individuals and businesses. Financial education tools and coaching services promote financial literacy, empowering users to make informed financial decisions. Risk management software and budgeting apps help users manage their financial risks and expenses, while financial reporting and analytics tools provide valuable insights for effective financial planning and performance tracking. Overall, the market continues to evolve, offering innovative solutions to meet the diverse needs of businesses and individuals.

How is this Financial Planning Software Industry segmented?

The financial planning software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Component

  Software
  Services


Application

  Financial advice and management
  Portfolio/accounting/trading management
  Wealth management
  Personal banking


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    China
    Japan


  Rest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

The market is experiencing significant growth due to the increasing need for businesses and individuals to effectively manage and organize their financial data. This demand is driven by various entities, including financial education programs and financial literacy initiatives, wealth management firms, financial institutions, and personal finance applications. Risk management, financial coaching, and financial dashboards are also integral components of financial planning software, providing valuable insights into financial literacy, regulations, and cash flow analysis. Moreover, small businesses and individual investors are leveraging financial planning services, financial forecasting, and financial consulting to make informed decisions about their financial future.

Machine learning and data analytics are increasingly being integrated into financial planning software, enabling advanced portfolio management, asset allocation, and open banking solutions. Financial technology, financial independence, investment planning, financial security, and financial services are all areas where financial planning software plays a crucial role

Snapshot img

Robo Advisory Services Market Size 2024-2028

The robo advisory services market size is forecast to increase by USD 1306.37 billion, at a CAGR of 9.16% between 2023 and 2028.

The market is witnessing significant growth, driven by the increasing adoption of artificial intelligence (AI) and machine learning (ML) technologies. These advanced technologies enable robo advisors to offer personalized investment recommendations based on an individual's financial goals, risk tolerance, and investment history. Furthermore, the emergence of hybrid robo advisory models, which combine human financial advisors with AI algorithms, is gaining popularity as it offers the benefits of both human expertise and automated investment management. However, the market faces challenges related to data security and privacy concerns. With the increasing use of digital platforms for managing financial information, ensuring the security and privacy of sensitive customer data is paramount.
Breaches can lead to significant reputational damage and financial losses for both the robo advisory firms and their clients. As such, companies must invest in robust cybersecurity measures and adhere to stringent data protection regulations to mitigate these risks and build trust with their customers.

What will be the Size of the Robo Advisory Services Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
Request Free Sample

The robo-advisory services market continues to evolve, integrating advanced financial technologies to cater to diverse client needs. Robo-advisors seamlessly blend financial education, insurance planning, account balances, risk-adjusted return, and robo-advisor platforms to deliver personalized financial advice. These platforms utilize data analytics to understand clients' financial goals, tax-loss harvesting, investment strategies, historical data, and risk tolerance, enabling automated investment and tax optimization. Robo-advisors prioritize user experience (UX) and user interface (UI) design, ensuring seamless account opening and funding. API integration facilitates data exchange with external sources, enhancing investment research and goal setting. Compliance regulations are meticulously addressed, ensuring privacy regulations and security protocols protect clients' data.

Performance tracking, portfolio optimization, and rebalancing are essential components of robo-advisory services. Fees and charges, including transaction fees and machine learning algorithms, are transparently disclosed. Retirement projections, estate planning, and goal setting are integrated into the robo-advisor platform, providing clients with comprehensive financial planning. Robo-advisors employ artificial intelligence (AI) and machine learning to offer investment recommendations and asset allocation, optimizing investment performance and risk management based on clients' investment horizon and reporting capabilities. ETF selection and retirement planning are also available, addressing various investment goals and tax implications. Customer support and financial education are integral to robo-advisory services, ensuring clients are well-informed about their investments and financial planning.

Digital wealth management offers a convenient and accessible solution for managing accounts and tracking investment performance. Overall, the robo-advisory services market is a dynamic and evolving landscape, continually adapting to meet the changing needs of clients.

How is this Robo Advisory Services Industry segmented?

The robo advisory services industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  High net worth individuals
  Retail investors


Service Type

  Portfolio management
  Tax optimization
  Retirement planning
  Others


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    India
    Japan


  Rest of World (ROW)

By End-user Insights

The high net worth individuals segment is estimated to witness significant growth during the forecast period.

High net worth individuals (HNWIs) increasingly turn to robo advisory services for cost-effective, personalized investment management solutions. These platforms offer lower fees than traditional wealth management firms, providing HNWIs with 24/7 access to tools and services. Robo advisors employ user-friendly interfaces and seamless API integrations for account funding, enabling HNWIs to easily open and manage accounts. Financial technology (fintech) and data analytics power these platforms, allowing for customized investment strategies based on individual financial goals, risk toleranc

CoinAPI delivers ultra-low latency cryptocurrency market data built for professional traders who demand absolute precision. Our tick-by-tick updates capture every market movement in real-time, providing the critical insights needed for split-second decisions in volatile markets.

Our WebSocket implementation streams live data directly to your trading systems with minimal delay, giving you the edge when identifying emerging patterns and opportunities. This immediate visibility helps optimize your trading strategies and manage risk more effectively in rapidly changing conditions.

We've engineered our infrastructure specifically for reliability under pressure. When markets surge and data volumes spike, our systems maintain consistent performance and delivery - ensuring your critical operations continue without interruption. For high-frequency trading and institutional investors who can't afford to wait, CoinAPI provides real-time cryptocurrency intelligence that drives successful decision-making

Why work with us?

Market Coverage & Data Types: - Real-time and historical data since 2010 (for chosen assets) - Full order book depth (L2/L3) - Tick-by-tick data - OHLCV across multiple timeframes - Market indexes (VWAP, PRIMKT) - Exchange rates with fiat pairs - Spot, futures, options, and perpetual contracts - Coverage of 90%+ global trading volume - Full Cryptocurrency Investor Data.

Technical Excellence: - 99,9% uptime guarantee - Multiple delivery methods: REST, WebSocket, FIX, S3 - Standardized data format across exchanges - Ultra-low latency data streaming - Detailed documentation - Custom integration assistance

CoinAPI delivers mission-critical insights to financial institutions globally, enabling informed decision-making in volatile cryptocurrency markets. Our enterprise-grade infrastructure processes milions of data points daily, offering unmatched reliability.

Dataset Description

The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their sentiment.

The dataset holds 11,932 documents annotated with 3 labels:

sentiments = { "LABEL_0": "Bearish", "LABEL_1": "Bullish", "LABEL_2": "Neutral" }

The data was collected using the Twitter API. The current dataset supports the multi-class classification… See the full description on the dataset page: https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment.

View LSEG's Lipper Fund Research Database, providing independent fund content to benchmark fund performance, manage risk, and more.

Snapshot img

Fintech Software Market Size 2025-2029

The fintech software market size is forecast to increase by USD 25.56 billion, at a CAGR of 8.2% between 2024 and 2029. The market is driven by the increasing need to improve business efficiency and the surging demand for data integration and visual analytics.

Major Market Trends & Insights

Asia Pacific dominated the market and accounted for a 38% share in 2023.
The market in the US and Canada are expected to grow significantly over the forecast period.
Based on deployment, the cloud-based segment led the market and was valued at USD 32.55 billion of the global revenue in 2023.
Based on end-user, the banking segment accounted for the largest market revenue share in 2023.

Market Size & Forecast

2024 Market Size: USD 53.23 Billion
Future opportunities: USD 25.56 billion
CAGR (2024-2029): 8.2%
Asia-Pacific: Largest market in 2023

The market continues to evolve, with dynamic market activities unfolding across various sectors. Customer onboarding processes are streamlined through digital identity verification and two-factor authentication, ensuring regulatory compliance and reducing fraud risks. Third-party risk management is addressed through robust network security measures and API integrations, ensuring data encryption and secure transaction processing. Financial modeling and predictive analytics leverage machine learning algorithms to optimize investment management and supply chain finance. Regtech and open banking initiatives facilitate regulatory compliance and user authentication, while mobile payments and digital wallets expand access to financial services. Security tokens and blockchain technology offer new opportunities for wealth management and algorithmic trading, enhancing transparency and security.

What will be the Size of the Fintech Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

Data migration and data analytics enable businesses to gain valuable insights from big data, driving innovation and growth. The ongoing integration of these technologies addresses the evolving needs of the fintech industry, with continuous advancements in areas such as risk management, portfolio optimization, and kyc/aml compliance. The on-premises segment is the second largest segment and was valued at USD 17.08 billion in 2023. The market's adaptability and responsiveness to emerging trends ensure its relevance and importance in the financial services landscape.

Companies are recognizing the value of automating financial processes and leveraging data insights to make informed decisions. However, this market faces significant challenges, primarily in the realm of data privacy and security. With the growing adoption of cloud-based solutions and the increasing volume of financial data being generated and transmitted, ensuring the security and confidentiality of this information becomes paramount.

As such, fintech software providers must invest in robust security measures and adhere to stringent regulatory standards to mitigate risks and build trust with their clients. Additionally, the integration of data from various sources and ensuring its accuracy and consistency poses another challenge. Companies must address these obstacles to capitalize on the market's potential and provide innovative solutions that cater to the evolving needs of their clients.

How is this Fintech Software Industry segmented?

The fintech software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  Cloud based
  On-premises


End-user

  Banking
  Insurance
  Securities


Service

  Money transfer and payments
  Savings and investments
  Digital lending and lending marketplaces
  Online insurance and insurance marketplaces
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Deployment Insights

The cloud based segment is estimated to witness significant growth during the forecast period. The segment was valued at USD 32.55 billion in 2023. It continued to the largest segment at a CAGR of 7.08%.

In the market, cloud computing is a significant trend, with the demand for cloud-based deployment models increasing. This growth can be attributed to features such as quick deployment, enhanced flexibility and scalability, real-time data visibility, and customization capabilities. Cloud-based solutions enable seamless integration with other software applications, providing automation benefits. Service providers offer flexible

Success.ai presents an exclusive opportunity to connect directly with top-tier decision-makers in the finance sector through our CEO Contact Data, specifically designed for venture capital and private equity investors based in the USA. This tailored database is part of our expansive collection that draws from over 700 million global profiles, meticulously verified to ensure the highest quality and reliability.

Why Choose Success.ai’s CEO Contact Data?

Specialized Investor Profiles: Access detailed profiles of CEOs and senior executives from leading venture capital and private equity firms across the United States. Investment Insights: Gain valuable insights into investment trends, fund sizes, and sectors of interest directly from the decision-makers. Verified Contact Details: We provide up-to-date email addresses and phone numbers, ensuring that you reach the right people without the hassle of outdated information. Data Features:

Targeted Financial Sector Data: Directly target influential figures in the financial sector who have the authority to make investment decisions. Comprehensive Executive Information: Profiles include not just contact information but also professional backgrounds, areas of investment focus, and operational histories. Geographic Precision: Focus your outreach efforts on US-based investors with our geographically segmented data. Flexible Delivery and Integration: Choose from various delivery options including API access for real-time integration or static files for periodic campaign use, allowing for seamless incorporation into your CRM or marketing automation tools.

Competitive Pricing with Best Price Guarantee: Success.ai is committed to providing competitive pricing without compromising on quality, backed by our Best Price Guarantee.

Effective Use Cases for CEO Contact Data:

Fundraising Initiatives: Connect with venture capital and private equity firms for fundraising activities or financial endorsements. Partnership Development: Forge strategic partnerships and collaborations with leading investors in the industry. Event Invitations: Send personalized invites to investment summits, roundtables, and networking events catered to top financial executives. Market Analysis: Utilize executive insights to better understand the investment landscape and refine your market strategies. Quality Assurance and Compliance:

Rigorous Data Verification: Our data undergoes continuous verification processes to maintain accuracy and completeness. Compliance with Regulations: All data handling practices adhere to GDPR and other relevant data protection laws, ensuring ethical and lawful use. Support and Custom Solutions:

Client Support: Our team is available to assist with any queries or specific data needs you may have. Tailored Data Solutions: Customize data sets according to specific criteria such as investment size, sector focus, or geographic location. Start Connecting with Venture Leaders: Empower your business strategy and network building by accessing Success.ai’s CEO Contact Data for venture capital and private equity investors. Whether you're looking to initiate funding rounds, explore investment opportunities, or engage with top financial leaders, our reliable data will pave the way for meaningful connections and successful outcomes.

Contact Success.ai today to discover how our precise and comprehensive data can transform your business approach and help you achieve your strategic goals.