Success.ai provides an extensive US Company Data service with access to over 28 million full company profiles and associated contact data. This service is tailored to enhance your business intelligence with precise and up-to-date information, ensuring you have the insights you need to make informed decisions.

API Integration: Our Enrichment APIs facilitate seamless integration and real-time updates, making it easier than ever to maintain accurate and current data within your systems. These APIs allow for efficient data management and can be customized to fit your specific needs, enhancing both the utility and accessibility of the data.

Benefits of Success.ai’s US Company Data:

• Comprehensive Data Coverage: Explore in-depth profiles that include financial details, company registries, and critical contact information.
• Regulatory Compliance: Our data solutions are GDPR-compliant, ensuring that you can use our services with confidence, adhering to the highest standards of data privacy and security.
• Tailored Data Preparation: We understand that every business has unique needs. Our data is prepared to meet your specific requirements, offering flexibility and precision.
• Best Price & Quality Guarantee: We are committed to providing the highest quality data at the most competitive prices, ensuring you receive unmatched value for your investment.

Key Use Cases:

• Market Research: Gain a competitive edge with comprehensive insights into the US business landscape.
• Sales and Marketing: Leverage detailed company and contact data to tailor your outreach and improve engagement with key decision-makers.
• Risk Management: Assess company stability and industry positioning with our detailed financial data.
• Strategic Planning: Utilize our extensive company data for scenario planning and strategic business decisions.

Why Choose Success.ai? Choose Success.ai for its robust US Company Data capabilities. Our commitment to providing detailed, accurate, and up-to-date information, paired with our innovative API technology, makes us a leader in the data services industry. Let us help you harness the power of data to propel your business forward.

And no one beats us on price!

The B2B data enrichment tool market is experiencing robust growth, driven by the increasing need for businesses to improve the accuracy and completeness of their customer data. This market, estimated at $5 billion in 2025, is projected to experience a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of marketing automation and CRM systems necessitates high-quality data to maximize their effectiveness. Secondly, the growing importance of data-driven decision-making across all business functions demands more comprehensive and accurate customer profiles. Thirdly, evolving privacy regulations are pushing companies towards compliant data enrichment practices, leading to greater investment in these tools. The market is segmented by application (SMEs and large enterprises) and data type (contact, company, technographic, intent, and others). Large enterprises currently dominate the market share due to their greater resources and data needs, but the SME segment is poised for significant growth due to increasing affordability and accessibility of these tools. Geographic distribution shows a strong concentration in North America and Europe, with rapidly expanding markets in Asia-Pacific, driven by the increasing digital adoption and economic growth in key regions like India and China. The competitive landscape is highly fragmented, with a multitude of vendors offering varying levels of functionality and pricing. Established players like ZoomInfo, Clearbit, and Cognism compete with emerging companies and niche providers, leading to a dynamic and innovative environment. The trend towards AI-powered enrichment tools is gaining traction, offering improved accuracy and automation. However, challenges remain, such as data quality issues, ensuring data privacy compliance, and managing the cost of data acquisition and enrichment. The market's future growth will likely depend on addressing these challenges and effectively leveraging technological advancements to improve data quality and integrate seamlessly with existing business workflows. Continued innovation in areas such as predictive analytics and AI-powered data enrichment will likely shape the trajectory of the market in the coming years.

Factori's Person API empowers businesses to enhance their contact database of Shopify and Klaviyo by enriching data. Simply input phone numbers, email addresses, hashed values, or name/company details, and receive comprehensive contact details in a standardized format. Fuel your marketing, sales, and customer relationship management activities with enriched contact information, including names, company details, job titles, contact information, social media profiles, and more. With optimized performance, robust error handling, and data security measures, Factori's Person API provides a seamless experience. Unlock valuable insights, personalize your outreach, and drive business growth effortlessly with Factori's Person API. Use Cases: Personalized Marketing: Enrich existing contact data with additional details such as social media profiles, educational background, or job titles. Tailor your marketing messages and campaigns to specific customer segments, improving personalization and engagement. Account-Based Marketing (ABM): Enhance your ABM strategy by enriching contact data of target accounts. Gain a comprehensive understanding of key stakeholders, their roles, and their preferences to deliver highly targeted and personalized campaigns. Sales Intelligence: Arm your sales team with enriched contact information to improve prospecting and sales conversations. Access valuable insights such as past experiences, interests, or industry expertise to establish meaningful connections and drive conversions. Data Cleansing and Validation: Ensure the accuracy and completeness of your contact database by enriching existing data with verified information. Update outdated or missing contact details, improving data quality and integrity. Market Research and Analysis: Enrich contact data to gain deeper insights into industry trends, job movements, or market dynamics. Analyze enriched data to identify patterns, opportunities, and market gaps for informed decision-making.

The Enriched Citation API provides the Intellectual Property 5 (IP5 - EPO, JPO, KIPO, CNIPA, and USPTO) and the Public with greater insight into the patent evaluation process. It allows users to quickly view information about which references, or prior art, were cited in specific patent application Office Actions, including: bibliographic information of the reference, the claims that the prior art was cited against, and the relevant sections that the examiner relied upon. The API allows for daily refresh and retrieval of enrich citation data from Office Actions mailed from October 1, 2017 to 30 days prior to the current date.

USPTO-LLM is an information-enriched chemical reaction dataset that provides more side information (reaction conditions and reaction steps division) for developing new reaction prediction and retrosynthesis methods and inspires new problems, such as reaction condition prediction. It comprises over 247K chemical reactions extracted from the patent documents of USPTO (United States Patent and Trademark Office), encompassing abundant information on reaction conditions.

We employ large language models to expedite the data collection procedures automatically with a reliable quality control process. The extracted chemical reactions are organized as heterogeneous directed graphs, allowing us to formulate a series of prediction tasks, such as reaction prediction, retrosynthesis, and reaction condition prediction, in a unified graph-filling framework.

This clean dataset is a refined version of our company datasets, consisting of 35M+ data records.

It’s an excellent data solution for companies with limited data engineering capabilities and those who want to reduce their time to value. You get filtered, cleaned, unified, and standardized B2B data. After cleaning, this data is also enriched by leveraging a carefully instructed large language model (LLM).

AI-powered data enrichment offers more accurate information in key data fields, such as company descriptions. It also produces over 20 additional data points that are very valuable to B2B businesses. Enhancing and highlighting the most important information in web data contributes to quicker time to value, making data processing much faster and easier.

For your convenience, you can choose from multiple data formats (Parquet, JSON, JSONL, or CSV) and select suitable delivery frequency (quarterly, monthly, or weekly).

Coresignal is a leading public business data provider in the web data sphere with an extensive focus on firmographic data and public employee profiles. More than 3B data records in different categories enable companies to build data-driven products and generate actionable insights. Coresignal is exceptional in terms of data freshness, with 890M+ records updated monthly for unprecedented accuracy and relevance.

A set of United States National Grids (USNGs) that are enriched with American Community Survey (ACS) Demographic, LandScan, USA structures, and other datasets. This dataset is use for prioritizing areas across political boundaries (County and State).

Supplementary tables for the manuscript "Theme Enrichment Analysis: A Statistical Test for Identifying Significantly Enriched Themes in a List of Stories with an Application to the Star Trek Television Franchise".

Supplementary Information File 1 contains a table of Star Trek TOS/TAS/TNG television series episodes featuring the Klingon alien race. The criterion for inclusion is that the Klingons were deemed by the authors to have been featured throughout the episode in a way that is central to the story plot.

Supplementary Information File 2 contains tables of over-represented Literary Theme Ontology version 0.1.1 literary themes in Star Trek TOS/TAS/TNG television series storysets as identified by the hypergeometric test.

Supplementary Information File 3 contains tables of over-represented Literary Theme Ontology version 0.1.1 literary themes in Star Trek TOS/TAS/TNG television series storysets as identified by the TF-IDF statistic.

Visualize on Visual Layer

  Oxford-Flowers-VL-Enriched

An enriched version of the Oxford-Flowers Dataset with image captions, bounding boxes, and label issues! With this additional information, the Oxford-Flowers dataset can be extended to various tasks such as image retrieval or visual question answering. The label issues help curate a cleaner and leaner dataset.

  Description

The dataset consists of 4 columns:

image_uri: The uri of original of the image… See the full description on the dataset page: https://huggingface.co/datasets/visual-layer/oxford-flowers-vl-enriched.

Pathway analysis is often the first choice for studying the mechanisms underlying a phenotype. However, conventional methods for pathway analysis do not take into account complex protein-protein interaction information, resulting in incomplete conclusions. Previously, numerous approaches that utilize protein-protein interaction information to enhance pathway analysis yielded superior results compared to conventional methods. Hereby, we present pathfindR, another approach exploiting protein-protein interaction information and the first R package for active-subnetwork-oriented pathway enrichment analyses for class comparison omics experiments. Using the list of genes obtained from an omics experiment comparing two groups of samples, pathfindR identifies active subnetworks in a protein-protein interaction network. It then performs pathway enrichment analyses on these identified subnetworks. To further reduce the complexity, it provides functionality for clustering the resulting pathways. Moreover, through a scoring function, the overall activity of each pathway in each sample can be estimated. We illustrate the capabilities of our pathway analysis method on three gene expression datasets and compare our results with those obtained from three popular pathway analysis tools. The results demonstrate that literature-supported disease-related pathways ranked higher in our approach compared to the others. Moreover, pathfindR identified additional pathways relevant to the conditions that were not identified by other tools, including pathways named after the conditions.

HIFLD data is the primary source used for CPF aggregation. There are inherent currency and accuracy (geospatial & attribution) issues identified within this national foundational catalog. Please reference back to HIFLD metadata catalog for specific layer information. County aggregated data layer organized to drive creation of dashboard map elements (Filters, Lists, Charts, Indicators, Gauges).

Lists of the named entities of the digital edition of the Codice Pelavicino in XML; There are also the same lists, where each named entity (Person, Place, Family, People, Institution) is enriched with related information as date, original document and geographic coordinates. These data are available both in JSON and CSV.

This dataset presents a large-scale collection of millions of Twitter posts related to the coronavirus pandemic in Spanish language. The collection was built by monitoring public posts written in Spanish containing a diverse set of hashtags related to the COVID-19, as well as tweets shared by the official Argentinian government offices, such as ministries and secretaries at different levels. Data was collected between March and August 2020 using the Twitter API.

In addition to tweets IDs, the dataset includes information about mentions, retweets, media, URLs, hashtags, replies, users and content-based user relations, allowing the observation of the dynamics of the shared information. Data is presented in different tables that can be analysed separately or combined.

The dataset aims at serving as source for studying several coronavirus effects in people through social media, including the impact of public policies, the perception of risk and related disease consequences, the adoption of guidelines, the emergence, dynamics and propagation of disinformation and rumours, the formation of communities and other social phenomena, the evolution of health related indicators (such as fear, stress, sleep disorders, or children behaviour changes), among other possibilities. In this sense, the dataset can be useful for multi-disciplinary researchers related to the different fields of data science, social network analysis, social computing, medical informatics, social sciences, among others.

Nowadays, there are lots of datasets available for training and experimentation in the field of recommender systems. Specifically, in the recommendation of audiovisual content, the MovieLens dataset is a prominent example. It is focused on the user-item relationship, providing actual interaction data between users and movies. However, although movies can be described with several characteristics, this dataset only offers limited information about the movie genres.

In this work, we propose enriching the MovieLens dataset by incorporating metadata available on the web (such as cast, description, keywords, etc.) and movie trailers. By leveraging the trailers, we extract audio information and generate transcriptions for each trailer, introducing a crucial textual dimension to the dataset. The audio information was extracted by the waveform and frequency analysis, followed by the application of dimensionality reduction techniques. For the transcription generation, the deep learning model Whisper was used. Finally, metadata was obtained from TMDB, and the BERT model was applied to extract embeddings.

These additional attributes enrich the original dataset, providing deeper and more precise analysis. Then, the use of this extended and enhanced dataset could drive significant advancements in recommendation systems, enhancing user experiences by providing more relevant and tailored movie recommendations based on their tastes and preferences.

Maximize your business potential with Success.ai's LinkedIn Company and Contact Data, a comprehensive solution designed to empower your business with strategic insights drawn from one of the largest professional networks in the world. This extensive dataset includes in-depth profiles from over 700 million professionals and 70 million companies globally, making it a goldmine for businesses aiming to enhance their marketing strategies, refine competitive intelligence, and drive robust B2B lead generation.

Transform Your Email Marketing Efforts With Success.ai, tap into highly detailed and direct contact data to personalize your communications effectively. By accessing a vast array of email addresses, personalize your outreach efforts to dramatically improve engagement rates and conversion possibilities.

Data Enrichment for Comprehensive Insights Integrate enriched LinkedIn data seamlessly into your CRM or any analytical system to gain a comprehensive understanding of your market landscape. This enriched view helps you navigate through complex business environments, enhancing decision-making and strategic planning.

Elevate Your Online Marketing Deploy targeted and precision-based online marketing campaigns leveraging detailed professional data from LinkedIn. Tailor your messages and offers based on specific professional demographics, industry segments, and more, to optimize engagement and maximize online marketing ROI.

Digital Advertising Optimized Utilize LinkedIn’s precise company and professional data to create highly targeted digital advertising campaigns. By understanding the profiles of key decision-makers, tailor your advertising strategies to resonate well with your target audience, ensuring high impact and better expenditure returns.

Accelerate B2B Lead Generation Identify and connect directly with key stakeholders and decision-makers to shorten your sales cycles and close deals quicker. With access to high-level contacts in your industry, streamline your lead generation process and enhance the efficiency of your sales funnel.

Why Partner with Success.ai for LinkedIn Data? - Competitive Pricing Assurance: Success.ai guarantees the most aggressive pricing, ensuring you receive unbeatable value for your investment in high-quality professional data. - Global Data Access: With coverage extending across 195 countries, tap into a rich reservoir of professional information, covering diverse industries and market segments. - High Data Accuracy: Backed by advanced AI technology and manual validation processes, our data accuracy rate stands at 99%, providing you with reliable and actionable insights. - Custom Data Integration: Receive tailored data solutions that fit seamlessly into your existing business processes, delivered in formats such as CSV and Parquet for easy integration. - Ethical Data Compliance: Our data sourcing and processing practices are fully compliant with global standards, ensuring ethical and responsible use of data. - Industry-wide Applications: Whether you’re in technology, finance, healthcare, or any other sector, our data solutions are designed to meet your specific industry needs.

Strategic Use Cases for Enhanced Business Performance - Email Marketing: Leverage accurate contact details for personalized and effective email marketing campaigns. - Online Marketing and Digital Advertising: Use detailed demographic and professional data to refine your online presence and digital ad targeting. - Data Enrichment and B2B Lead Generation: Enhance your databases and accelerate your lead generation with enriched, up-to-date data. - Competitive Intelligence and Market Research: Stay ahead of the curve by using our data for deep market analysis and competitive research.

With Success.ai, you’re not just accessing data; you’re unlocking a gateway to strategic business growth and enhanced market positioning. Start with Success.ai today to leverage our LinkedIn Company Data and transform your business operations with precision and efficiency.

Did we mention that we'll beat any price on the market? Try us.

Research in information science and scholarly communication strongly relies on the availability of openly accessible datasets of metadata and, where possible, their relative payloads. To this end, CrossRef plays a pivotal role by providing free access to its entire metadata collection, and allowing other initiatives to link and enrich its information. Therefore, a number of key pieces of information result scattered across diverse datasets and resources freely available online. As a result of this fragmentation, researchers in this domain end up struggling with daily integration problems producing a plethora of ad-hoc datasets, therefore incurring in a waste of time, resources, and infringing open science best practices.

The latest DOIBoost release is a metadata collection that enriches CrossRef (October 2019 release: 108,048,986 publication records) with inputs from Microsoft Academic Graph (October 2019 release: 76,171,072 publication records), ORCID (October 2019 release: 12,642,131 publication records), and Unpaywall (August 2019 release: 26,589,869 publication records) for the purpose of supporting high-quality and robust research experiments. As a result of DOIBoost, CrossRef records have been "boosted" as follows:

• 47,254,618 CrossRef records have been enriched with an abstract from MAG;
• 33,279,428 CrossRef records have been enriched with an affiliation from MAG and/or ORCID;
• 509,588 CrossRef records have been enriched with an ORCID identifier from ORCID.

This entry consists of two files: doiboost_dump-2019-11-27.tar (contains a set of partXYZ.gz files, each one containing the JSON files relative to the enriched CrossRef records), a schemaAndSample.zip, and termsOfUse.doc (contains details on the terms of use of DOIBoost).

Note that this records comes with two relationships to other results of this experiment:

1. link to the data paper: for more information on how the dataset is (and can be) generated;
2. link to the software: to repeat the experiment

Significantly enriched GO terms (adjust P

Success.ai delivers a sophisticated array of contact data services tailored to enhance online marketing and support comprehensive data enrichment initiatives. Our resources encompass a wide range of essential information including email addresses, phone numbers, B2B contacts, and direct CEO connections, alongside expansive B2C data, facilitating robust competitive intelligence and sales data enrichment.

• Targeted Email Address Data: Access a vast array of email information pivotal for executing precise online marketing campaigns and engaging with key business stakeholders.
• Comprehensive Phone Number Data: Utilize our extensive phone data for telemarketing, enhancing direct contact strategies, and improving customer interaction.
• Dynamic B2B and B2C Contact Data: With our detailed B2B and B2C contact data, tailor your outreach and ensure your messaging reaches the right audience, from C-suite executives to crucial consumer segments.
• Exclusive CEO Contact Information: Directly reach top-tier executives with our verified CEO contact data, ideal for high-level networking and partnership development.

Strategic Use Cases Supported by Our Data:

• Online Marketing: Leverage our email and phone data to drive targeted online marketing strategies, enhancing lead generation and customer engagement.
• Data Enrichment: Refine your database accuracy with our data enrichment services, ensuring your business decisions are based on the most current and comprehensive data.
• B2B Data Enrichment: Specifically tailor your B2B databases to improve the quality of business contact data, enhancing outreach efforts and operational efficiency.
• Sales Data Enrichment: Elevate your sales strategies with enriched contact data that increases conversion rates and sales success.
• Competitive Intelligence: Gain a competitive edge by using our detailed contact data to gather intelligence on market trends, competitor activities, and industry shifts.

Why Choose Success.ai?

• Unmatched Data Precision: We ensure a 99% accuracy rate across all data points through rigorous validation processes, supporting your strategic needs with reliable data.
• Global Reach with Tailored Solutions: Our data spans across global markets but is finely tuned to meet local business requirements, ensuring you have access to pertinent information wherever your business operates.
• Affordable Pricing with Best Value: We are committed to providing the most cost-effective data solutions on the market, ensuring you receive the best value for your investment without compromising on quality.
• Ethical Data Practices: Compliance with international data privacy standards is at the heart of what we do, ensuring that your use of our data is both responsible and legally sound.

Get Started with Success.ai Today: Partner with Success.ai to harness the full potential of high-quality contact data. Whether you're aiming to enhance your online marketing efforts, enrich your sales databases, or gain strategic competitive intelligence, our comprehensive data solutions are designed to propel your business to new heights.

Contact us to discover how we can customize our offerings to suit your specific business requirements.

This is a derivative work based on Paracrawl release 9 English-Dutch (https://paracrawl.eu/). This version of the corpus includes a set of probabilities corresponding to the affinity of each segment pair to a specific Digital Service Infrastructure (DSI), which includes Cybersecurity, Electronic Exchange of Social Security Information, E-health, E-justice, Europeana, Online Dispute Resolution, Open Data Portal and Safer Internet. The model that assigned the probabilities is a fine-tuned pre-trained language model (DeBERTa-v3-large), trained on a crawled corpus of English DSI-specific texts. More information is available on the corresponding GitHub page: https://github.com/RikVN/DSI. The rest of the information in the original version of the corpus remained unchanged.

This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author’s view. The Agency is not responsible for any use that may be made of the information it contains.