Alternatives to Proxem Software

Utilize natural language processing to derive insights from unstructured text without needing machine learning expertise, leveraging a suite of features from Cognitive Service for Language. Enhance your comprehension of customer sentiments through sentiment analysis and pinpoint significant phrases and entities, including individuals, locations, and organizations, to identify prevalent themes and trends. Categorize medical terminology with specialized, pretrained models tailored for specific domains. Assess text in numerous languages and uncover vital concepts within the content, such as key phrases and named entities encompassing people, events, and organizations. Investigate customer feedback regarding your brand while analyzing sentiments related to particular subjects through opinion mining. Moreover, extract valuable insights from unstructured clinical documents like doctors' notes, electronic health records, and patient intake forms by employing text analytics designed for healthcare applications, ultimately improving patient care and decision-making processes.

Leverage advanced machine learning techniques for thorough text analysis that can extract, interpret, and securely store textual data. With AutoML, you can create top-tier custom machine learning models effortlessly, without writing any code. Implement natural language understanding through the Natural Language API to enhance your applications. Utilize entity analysis to pinpoint and categorize various fields in documents, such as emails, chats, and social media interactions, followed by sentiment analysis to gauge customer feedback and derive actionable insights for product improvements and user experience. The Natural Language API, combined with speech-to-text capabilities, can also provide valuable insights from audio sources. Additionally, the Vision API enhances your capabilities with optical character recognition (OCR) for digitizing scanned documents. The Translation API further enables sentiment understanding across diverse languages. With custom entity extraction, you can identify specialized entities within your documents that may not be recognized by standard models, saving both time and resources on manual processing. Ultimately, you can train your own high-quality machine learning models to effectively classify, extract, and assess sentiment, making your analysis more targeted and efficient. This comprehensive approach ensures a robust understanding of textual and audio data, empowering businesses with deeper insights.

Watson Natural Language Understanding is a cloud-native solution that leverages deep learning techniques to derive metadata from text, including entities, keywords, categories, sentiment, emotions, relationships, and syntactic structures. Delve into the topics within your data through text analysis, which enables the extraction of keywords, concepts, categories, and more. The service supports the analysis of unstructured data across over thirteen different languages. With ready-to-use machine learning models for text mining, it delivers a remarkable level of accuracy for your content. You can implement Watson Natural Language Understanding either behind your firewall or on any cloud platform of your choice. Customize Watson to grasp the specific language of your business and pull tailored insights using Watson Knowledge Studio. Your data ownership is preserved, as we prioritize the security and confidentiality of your information, ensuring that IBM will neither collect nor store your data. By employing our sophisticated natural language processing (NLP) tools, developers are equipped to process and uncover valuable insights from their unstructured data, ultimately enhancing decision-making capabilities. This innovative approach not only streamlines data analysis but also empowers organizations to harness the full potential of their information assets.

TextBlob is a Python library designed for handling textual data, providing an intuitive API to carry out various natural language processing functions such as part-of-speech tagging, sentiment analysis, noun phrase extraction, and classification tasks. Built on the foundations of NLTK and Pattern, it integrates seamlessly with both libraries. Notable features encompass tokenization (the division of text into words and sentences), frequency analysis of words and phrases, parsing capabilities, n-grams, and word inflection (both pluralization and singularization), alongside lemmatization, spelling correction, and integration with WordNet. TextBlob is compatible with Python versions 2.7 and higher, as well as 3.5 and above. The library is actively maintained on GitHub and is released under the MIT License. For users seeking guidance, thorough documentation is readily accessible, including a quick start guide and a variety of tutorials to facilitate the implementation of different NLP tasks. This rich resource equips developers with the tools necessary to enhance their text processing capabilities.

Komprehend AI offers an extensive range of document classification and NLP APIs designed specifically for software developers. Our advanced NLP models leverage a vast dataset of over a billion documents, achieving top-notch accuracy in various common NLP applications, including sentiment analysis and emotion detection. Explore our free demo today to experience the effectiveness of our Text Analysis API firsthand. It consistently delivers high accuracy in real-world scenarios, extracting valuable insights from open-ended text data. Compatible with a wide range of industries, from finance to healthcare, it also supports private cloud implementations using Docker containers or on-premise deployments, ensuring your data remains secure. By adhering to GDPR compliance guidelines meticulously, we prioritize the protection of your information. Gain insights into the social sentiment surrounding your brand, product, or service by actively monitoring online discussions. Sentiment analysis involves the contextual examination of text to identify and extract subjective insights from the material, thereby enhancing your understanding of audience perceptions. Additionally, our tools allow for seamless integration into existing workflows, making it easier for developers to harness the power of NLP.

The TextRazor API provides an efficient and precise means of uncovering the Who, What, Why, and How within your news articles. It features capabilities such as Entity Extraction, Disambiguation, and Linking, alongside Keyphrase Extraction, Automatic Topic Tagging, and Classification, supporting twelve different languages. This tool performs an in-depth analysis of your content, allowing for the extraction of Relations, Typed Dependencies between terms, and Synonyms, which empowers the development of advanced semantic applications that are context-aware. Furthermore, it enables the swift extraction of custom entities like products and companies, allowing users to create specific rules for tagging their content with personalized categories. TextRazor comprises a versatile text analysis infrastructure that can be utilized either via the cloud or through self-hosting. By integrating cutting-edge natural language processing techniques with an extensive repository of factual information, TextRazor aids in quickly deriving valuable insights from your documents, tweets, or web pages, making it an indispensable tool for content creators and analysts alike. This comprehensive approach ensures that users can maximize the effectiveness of their data processing and analysis efforts.

Spool provides a seamless way for you and your colleagues to record and retrieve essential discussions from customer calls and sales meetings with just a single click through its AI-driven sales collaboration platform. By integrating Spool with your Zoom account and installing the Spool desktop widget, you can enhance your meeting efficiency. During your customer interactions and sales discussions, the Spool widget allows you to capture only the key, non-sensitive aspects of your conversations for documentation, eliminating the need for typing. Simply hit the appropriate button on the widget to initiate and conclude the capture of any topics you wish to document throughout your discussions. Employing advanced text classification and sentiment analysis techniques, Spool identifies and organizes the most significant and impactful segments of the selected conversations, automatically generating comprehensive sales documents. Immediately following each discovery or qualification call, demo, or sales team meeting, Spool promptly sends you a well-organized sales document via email and archives it in your Spool dashboard for easy access later. This streamlined process not only saves time but also ensures that no critical information is overlooked.

For tasks such as transcription, data validation, classification, sentiment analysis, and more, UHRS offers comprehensive solutions tailored to your needs. We leverage human intelligence to enhance machine learning models, aiding you in overcoming some of your toughest challenges. Judges can conveniently access UHRS from anywhere at any time with just an internet connection. This streamlined access allows for quick engagement with tasks like video annotation within minutes. With UHRS, managing the classification of thousands of images becomes a straightforward and efficient process. Our platform enables the training of your products and tools through high-quality annotated image data, enhancing capabilities like image detection and boundary recognition. You can efficiently classify images, conduct semantic segmentation, and implement object detection. In addition, we facilitate audio-to-text validation, conversation analysis, and relevance checks. Furthermore, our services extend to sentiment identification for tweets, document classification, and various ad hoc data collection tasks, including information correction, moderation, and conducting surveys. With UHRS, you gain a versatile partner in navigating a wide range of data-related challenges.

Baidu Natural Language Processing leverages the extensive data amassed by Baidu to advance its leading-edge technologies in natural language processing and knowledge graphs. This field encompasses a diverse array of core functionalities and solutions, featuring over ten capabilities, including sentiment analysis, address identification, and customer feedback evaluation. Through techniques such as word segmentation, part-of-speech tagging, and named entity recognition, lexical analysis enables the identification of fundamental language components, eliminates ambiguities, and fosters precise comprehension. By utilizing deep neural networks along with vast amounts of high-quality online data, it becomes feasible to assess the semantic similarity between two words by transforming them into vector representations, thereby fulfilling the stringent accuracy demands of various business applications. Furthermore, the representation of words as vectors facilitates the efficient analysis of texts, ultimately aiding in the swift execution of semantic mining tasks while enhancing overall understanding.

Artificial intelligence (AI) and computer vision play a crucial role in enhancing manufacturing processes by training systems to ensure product quality, guiding robots for autonomous movement and safety protocols, and equipping cameras to monitor and analyze retail traffic, identify various car types and colors, recognize food items in a refrigerator, or generate 3D models from video footage. Additionally, these advanced technologies utilize algorithms to forecast sales, uncover relationships between different metrics and publications, and facilitate business growth, as well as categorize customers to tailor personalized offers, interpret and visualize data, and extract key information from text and video content. Techniques such as data mining, regression analysis, classification, correlation, and cluster analysis, along with decision trees and prediction models, are employed alongside neural networks to optimize outcomes. Furthermore, text analysis encompasses classification, comprehension, summarization, auto-tagging, named-entity recognition, and sentiment analysis while also enabling comparison for text similarity, dialog systems, and question-answering frameworks. Image and video processing is further enhanced through detection, segmentation, recognition, recovery, and the generation of new visual content, showcasing the vast potential of AI in various domains. This multifaceted application of AI not only streamlines operations but also opens up new avenues for innovation and efficiency in multiple industries.

Enhance the efficiency of your deep learning projects and reduce the time it takes to realize value through AI model training and inference. As technology continues to improve in areas like computation, algorithms, and data accessibility, more businesses are embracing deep learning to derive and expand insights in fields such as speech recognition, natural language processing, and image classification. This powerful technology is capable of analyzing text, images, audio, and video on a large scale, allowing for the generation of patterns used in recommendation systems, sentiment analysis, financial risk assessments, and anomaly detection. The significant computational resources needed to handle neural networks stem from their complexity, including multiple layers and substantial training data requirements. Additionally, organizations face challenges in demonstrating the effectiveness of deep learning initiatives that are executed in isolation, which can hinder broader adoption and integration. The shift towards more collaborative approaches may help mitigate these issues and enhance the overall impact of deep learning strategies within companies.

TrustServista harnesses cutting-edge AI technology to equip media professionals, analysts, and content distributors with comprehensive tools for content analysis and verification. By leveraging sophisticated algorithms, TrustServista assesses the credibility of news articles through deep content evaluation, considering factors such as the publisher's reputation, referenced sources, and varying perspectives on the same topic from different media outlets. The platform boasts a diverse array of text analytics functionalities, including automatic summarization, entity extraction, sentiment analysis, and organized content classification. An impressive capacity allows TrustServista to scrutinize over 60,000 articles daily in various languages, generating valuable real-time insights based on open data. Additionally, the service facilitates the automatic identification of semantic similarities between documents while extracting hyperlinks and references from online content, further enhancing its analytical capabilities. This comprehensive approach not only aids in understanding the media landscape but also supports informed decision-making for its users.

SANCARE is an innovative start-up focused on applying Machine Learning techniques to hospital data. We partner with leading experts in the field to enhance our offerings. Our platform delivers an ergonomic and user-friendly interface to Medical Information Departments, facilitating quick adoption and usability. Users benefit from comprehensive access to all documents forming the electronic patient record, ensuring a seamless experience. As an effective production tool, our solution meticulously tracks each phase of the coding procedure for external validation. By leveraging machine learning, we can create robust predictive models that analyze vast data sets while considering contextual factors—capabilities that traditional rule-based systems and semantic analysis tools fall short of providing. This enables the automation of intricate decision-making processes and the identification of subtle signals that may go unnoticed by human analysts. The machine learning engine behind SANCARE is grounded in a probabilistic framework, allowing it to learn from a significant volume of examples to accurately predict the necessary codes without any explicit guidance. Ultimately, our technology not only streamlines coding tasks but also enhances the overall efficiency of healthcare data management.

Harness the capabilities of machine learning to elevate your sales team's performance. To begin with, SetSail automatically gathers and enhances your customer and activity information, relieving your team of this burden. We then create a customized machine learning model tailored to your business, which assesses account and deal health by utilizing CRM data and the sentiment of communications, employing advanced natural language processing (NLP) methods. Our models focus on objective indicators, such as sentiment expressed during customer interactions, rather than relying solely on subjective assessments like deal stages. With the power of our machine learning engine, SetSail provides actionable insights that enable representatives, managers, and executives to monitor pipeline health in real-time. This robust tool can dissect data by representative, deal, account, and conversation theme, allowing you to uncover performance challenges and obstacles to closing deals. By identifying and addressing weaknesses promptly, you can safeguard your revenue and optimize your sales strategy for greater success. Furthermore, staying ahead of potential issues can enhance team morale and foster a culture of continuous improvement.

In today's world, communication occurs through various channels such as social media, text messages, emails, and phone calls, leading to an increase in customer interaction methods. To enhance the usability of documents for employees and business applications, it is essential to continue digitizing these records. The advantages of this transition are significant, including cost reduction, faster customer response times, and enhanced operational flexibility. Tessi provides a comprehensive solution that integrates all types of incoming digital or physical workflows into a single platform, catering to both mail rooms and industry-specific documents. Explore our diverse offerings that include multi-channel scanning, automatic document recognition and sorting, streamlined email management, and automated extraction and verification of supporting documents. By leveraging advanced OCR/ICR technologies along with automation and semantic analysis, we significantly improve the processes of reading, extracting, indexing, and categorizing your documents, ensuring more efficient management of your information. Embrace the future of document handling with our innovative solutions designed to meet your evolving needs.

The Language Translator offers the ability to convert text between different languages seamlessly, allowing users to access global news in their preferred language. This service enhances communication with customers by enabling interactions in their native languages, among other features. It provides a range of domain-specific models to cater to various industries. Users can also tailor translations to reflect unique terminology and language nuances, utilizing three customization options: forced glossary, parallel phrases, and corpus-level modifications. In contrast to other translation services, IBM ensures your privacy and maintains ownership of your data. The IBM Watson Language Translator Service is designed for application developers, providing them with the tools to implement multiple specialized translation models. Furthermore, it allows for the immediate translation of documents, applications, and websites, facilitating entry into new markets. Users can also develop multilingual chatbots, ensuring that customer communication is personalized and effective, thus enhancing overall engagement. This comprehensive approach to translation and customization sets IBM apart in the realm of language services.

Brightleaf offers a technology-powered service that extracts information from contracts using our proprietary semantic intelligence/natural-language processing technology, our own team to review the output, and our Six-Sigma process. This allows us to extract highly accurate data from contracts. For reporting and tracking, your legacy contractual documents can be combined with the extracted meta-data into a Contract Lifecycle Management system (CLM). This will greatly increase the value of your investment. It can be almost any data, and can be customized for each type of contract. Our software extracts all meta-data, terms, conditions, legal provisions, as well as all obligations, which are often scattered throughout your contracts.

With the help of AI, you can convert your semantic data into actionable insights that will help you make informed strategic decisions and shape your actions. As a leader in the field of Artificial Intelligence and a holder of advanced semantic data processing technologies, Synomia excels at transforming vast quantities of unstructured data into valuable insights, enabling brands to refine their strategies and activation processes. By analyzing significant and subtle market signals, you can uncover future trends that will guide your business direction. Additionally, our expertise allows us to pinpoint the most effective approaches for your digital strategies. We are proficient in all semantic AI technologies, applying them based on the specific needs of our clients, including supervised and unsupervised machine learning as well as rule-based systems. The capabilities of semantic AI empower the analysis of numerous sources and facilitate the development of methodologies focused on innovation and exploration, which are essential for creating strategies that resonate with target audiences. In today’s rapidly changing market, leveraging these insights is crucial for staying ahead of competitors and meeting consumer demands effectively.

Detect references to locations, individuals, brands, and events within various documents and social media platforms. Effortlessly gather further information regarding these entities. Categorize multilingual texts into established, predefined classifications or create a personalized classification system in just a few minutes. Assess whether the sentiment conveyed in brief texts, such as product reviews, is positive, negative, or neutral. Automatically pinpoint significant, contextually relevant concepts and key phrases in articles and social media updates. Analyze two pieces of text to determine their syntactic and semantic resemblance. Recognize when two texts pertain to the same topic. Extract clean textual content from newspapers, blogs, and other online sources, stripping away boilerplate and advertisements to obtain the full text of the article along with its images. This process not only enhances the readability of the extracted content but also ensures that the most pertinent information is highlighted.

Text analysis is an intricate and specialized procedure. Textalytic simplifies the process of deriving insights from written content with ease. You can utilize our corpus builder to prepare your text for analysis. Whether you prefer to copy and paste directly into the editor or upload a document from your computer or Dropbox, both options are available. The results can be visualized in various formats, including tables and graphs, or exported as CSV and PDF files. Additionally, the graphs can be saved as image files for use on websites or shared via email. Discover valuable insights through vibrant and informative charts and graphs that enhance your understanding. The comparison feature enables users to analyze characteristics within a dynamic scatterplot. You can also examine the frequency of words that describe nouns or pronouns, as well as those that depict actions or states of being. Furthermore, you can assess the frequency of words that indicate relationships, along with groups of words that define the subject matter clearly. This comprehensive tool allows for a multifaceted exploration of textual data, making insights accessible and actionable.

Streamline the creation and modification of FMEA, Process Flow Diagrams, and Control Plans like never before. The FMEA methodology can be quite intricate, but with FMEA Studio's automated features, you can significantly reduce the likelihood of errors. It offers user-friendly functionalities that make sharing documents with others a breeze. FMEA Studio accommodates various risk indices, including RPN, SOD, and CN, along with their respective evaluation techniques. You have the capability to assess FMEA risks through both 2D and 3D risk matrices, enhancing your analysis. Ranking parameters such as Severity, Occurrence, or Detection levels is made simpler and quicker with intuitive ranking tables that can be tailored to your specific requirements. Additionally, FMEA Studio provides a structural tree for visualizing structure, function, and failure analyses. Accessing editing tools is straightforward through a convenient right-click menu, ensuring an efficient workflow throughout the entire process. With these features, FMEA Studio not only enhances productivity but also promotes collaboration among team members for improved outcomes.

Atomic Intelligence offers an online platform dedicated to the automated examination of textual information. We analyze vast amounts of data, including news articles, social media posts, and regulatory documents, while identifying expressed opinions alongside references to companies, products, and various topics. Our services are invaluable to investment firms that leverage this data to enhance their proprietary trading methods, consumer goods companies aiming to gauge customer sentiment, and tech firms seeking to delegate text analysis tasks. Atomic Intelligence meticulously reviews text to uncover references to companies, products, sentiment, and numerous other aspects. Utilizing advanced natural language processing and machine learning technologies, we pinpoint significant mentions, whether they are explicitly stated or subtly implied within the content. Additionally, Atomic Intelligence is capable of handling any form of unstructured data. Users can upload documents through our web interface or API, or they can set up Atomic for automated scheduled retrieval from their preferred sources, thereby streamlining the analysis process. In this way, we empower organizations to gain deeper insights and make informed decisions based on comprehensive textual analysis.

Gensim is an open-source Python library that specializes in unsupervised topic modeling and natural language processing, with an emphasis on extensive semantic modeling. It supports the development of various models, including Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), which aids in converting documents into semantic vectors and in identifying documents that are semantically linked. With a strong focus on performance, Gensim features highly efficient implementations crafted in both Python and Cython, enabling it to handle extremely large corpora through the use of data streaming and incremental algorithms, which allows for processing without the need to load the entire dataset into memory. This library operates independently of the platform, functioning seamlessly on Linux, Windows, and macOS, and is distributed under the GNU LGPL license, making it accessible for both personal and commercial applications. Its popularity is evident, as it is employed by thousands of organizations on a daily basis, has received over 2,600 citations in academic works, and boasts more than 1 million downloads each week, showcasing its widespread impact and utility in the field. Researchers and developers alike have come to rely on Gensim for its robust features and ease of use.

In contrast to traditional word-for-word translation methods or statistical approaches, the GramTrans software leverages contextual rules to accurately differentiate between various translations of the same word or phrase. GramTrans™ provides exceptional, domain-neutral machine translation specifically tailored for Scandinavian languages. Its offerings are grounded in advanced, university-level research spanning Natural Language Processing (NLP), corpus linguistics, and lexicography. This research-driven system incorporates cutting-edge technologies, including Constraint Grammar dependency parsing and approaches for resolving dependency-based polysemy. It features robust analysis of source languages, along with techniques for morphological and semantic disambiguation. The system is supported by extensive grammars and lexicons created by linguists, ensuring a high level of independence across different domains such as journalism, literature, emails, and scientific texts. Furthermore, it boasts name recognition and protection capabilities, as well as the ability to recognize and separate compound words. The use of dependency formalism allows for deep syntactic analysis, while context-sensitive selection of translation equivalents enhances the overall accuracy and fluidity of the translations provided. Ultimately, GramTrans stands out as a sophisticated tool for anyone in need of precise and versatile translation solutions.

Mining activities demand comprehensive intelligence and analysis throughout both the exploration and operational stages. During the exploration phase, assessing mineral deposits necessitates a thorough approach that includes borehole drilling and careful sample analysis to ascertain the nature and quantity of resources available. In the operational phase, our advanced technology platform can effectively monitor alterations in subsurface structures and detect the formation of air gaps. This capability empowers mining companies to proactively address these changes, thereby mitigating the risks associated with potential tunnel collapses. Furthermore, the mDetect technology platform is designed to aid mining firms in evaluating how new underground formations and channels might impact the integrity of existing subterranean structures, ensuring safer and more efficient mining operations. By leveraging these technological advancements, the industry can enhance its safety protocols and operational efficiency significantly.

Collaborative text analytics for machine-learning and human. We offer a variety of multilingual, text mining and data science features, as well as human annotation and machine-learning capabilities. DiscoverText provides a variety of cloud-based software tools that allow users to quickly and accurately analyze large amounts of text data. Our customers use DiscoverText to sort unstructured text commonly found in market research. They also include associated metadata such as customer feedback platforms, CRMs and chats. Discover why we are ranked #1 in text, metadata, social network analysis support, and trusted by hundreds academic research groups. Machine-learning sifters can be created in just hours or minutes by crowdsourcing. We provide an API and support technical integrations to SurveyMonkey and Twitter.

WordStat is a user-friendly and versatile text analysis application designed to facilitate the extraction of themes and trends through text mining tools, as well as to provide meticulous measurement capabilities with advanced quantitative content analysis features. It serves anyone in need of swiftly extracting and analyzing large volumes of documents for valuable insights. This software can be applied in various contexts, including the evaluation of open-ended survey responses, enhancing business intelligence, analyzing news coverage, detecting fraud, and much more. With its seamless integration with SimStat, a statistical data analysis application, QDA Miner for qualitative data analysis, and Stata, a comprehensive statistical software from StataCorp, WordStat offers unparalleled flexibility in correlating text analysis with structured data, encompassing both numerical and categorical information. Additionally, its adaptable nature makes it suitable for diverse industries and research fields, allowing users to tackle different analytical challenges effectively.

Azure AI Language offers a comprehensive managed service tailored for the creation of natural language processing applications. This platform enables users to identify essential terms and phrases, assess sentiment, condense text, and develop interactive conversational interfaces. It empowers you to annotate, train, evaluate, and deploy customizable AI models with little to no expertise in machine learning. With predefined entity categories suitable for various industries and text analytics tailored for the healthcare sector, the service provides out-of-the-box features that facilitate rapid onboarding while allowing for further customization and optimization as required. To enhance the training of your machine learning models for specific applications, you can supply several labeled examples. Moreover, custom multilingual models can be developed in one language and effectively utilized across multiple others. By leveraging Language Studio, you can access advanced GPT-powered language models that efficiently analyze and propose labels for your content. Additionally, the platform allows for the extraction, labeling, and redaction of critical information within text across several categories, ensuring that sensitive data is handled appropriately. This versatility makes Azure AI Language an invaluable tool for businesses looking to enhance their natural language processing capabilities.

Fullstory is a platform for behavioral data that reveals the hidden story behind consumer behavior. Fullstory allows product, engineering and data teams to connect sentiments signals with other data sources in order to design the next best actions. Fullstory provides deeper and more immediate actionable insights than conventional web and product analyses that can only surface what is happening but not why. It is the only behavioral data platforms that provide the context needed to create in-the moment experiences that drive revenue. Fullstory's behavioral analytics is ready for AI. It uses first-party data that has been automatically captured, indexed and semantically structured. No longer do enterprises waste hours and resources on data analysis.

You can forget about manual content classification or data entry. Doculayer.ai provides a configurable workflow that includes document processing services such as OCR, document type classification and topic classification, as well data extraction and masking. Doculayer.ai allows business users to take control of their learning and training by providing an intuitive user interface that makes labeling documents and data easy. Our hybrid data extraction approach allows machine learning models to be combined with patterns, rules, and library scripts to produce better results in less time. Data masking is an option to anonymize or pseudonymize sensitive data in documents. Doculayer.ai provides document intelligence to your Content Services Platform and Business Process Management systems. Your existing IT environment can be augmented for document processing by machine learning, natural language processing and computer vision technologies.

B.I.R.B.AL., our innovative AI engine, has been developed using a vast database comprising over a million articles in various languages, leveraging advanced Natural Language Processing (NLP) techniques. This technology encompasses features such as machine learning classification, interlanguage clustering, ranking of news topics, and extraction-based summarization, all designed to tailor news filtering for diverse users and applications. Employing both supervised and unsupervised machine learning algorithms enhanced by Deep Learning, B.I.R.B.AL. enables users to move beyond conventional online content monitoring, identifying the most pertinent topics emerging on the web. By gathering and analyzing extensive data sets, users can derive strategic insights that enhance their decision-making capabilities. Additionally, B.I.R.B.AL. empowers users to enrich their financial analyses with comprehensive web data collections, allowing for a deeper understanding of performance trends through a powerful new tool, while also effectively applying structured web data to predictive analytics and risk modeling strategies. This multifaceted approach ensures that organizations remain at the forefront of data-driven insights and decision-making.

Levity is a no-code platform for creating custom AI models that take daily, repetitive tasks off your shoulders. Levity allows you to train AI models on documents, free text or images without writing any code. Build intelligent automations into existing workflows and connect them to the tools you already use. The platform is designed in a non-technical way, so everybody can start building within minutes and set up powerful automations without waiting for developer resources. If you struggle with daily tedious tasks that rule-based automation just can't handle, Levity is the quickest way to finally let machines handle them. Check out Levity's extensive library of templates for common use-cases such as sentiment analysis, customer support or document classification to get started within minutes. Add your custom data to further tailor the AI to your specific needs and only stay in the loop for difficult cases, so the AI can learn along the way.

XLNet introduces an innovative approach to unsupervised language representation learning by utilizing a unique generalized permutation language modeling objective. Furthermore, it leverages the Transformer-XL architecture, which proves to be highly effective in handling language tasks that require processing of extended contexts. As a result, XLNet sets new benchmarks with its state-of-the-art (SOTA) performance across multiple downstream language applications, such as question answering, natural language inference, sentiment analysis, and document ranking. This makes XLNet a significant advancement in the field of natural language processing.

Semantria (natural language processing) API is offered by Lexalytics, a leader in enterprise sentiment analysis and text analysis since 2004. Semantria provides multi-layered sentiment analysis, categorization and entity recognition, theme analysis as well as intention detection, summarization, and summary in an easy to integrate RESTful API package. Semantria can be customized through graphical configuration tools. It supports 24 languages and can be deployed across public, private and hybrid clouds. Semantria scales easily from single servers to entire data centres and back again to meet your processing needs. Integrate Semantria for powerful, flexible text analytics and natural word processing capabilities to cloud-based data analysis products or enterprise business intelligence infrastructure. To create a complete business intelligence platform, you can add Lexalytics storage or visualization tools to store, manage, analyze, and visualize text documents.

HelpHub provides a way for users to access help documents, AI-driven Instant Answers, and additional support seamlessly within your application. By incorporating HelpHub, users can find solutions to their problems without disrupting their experience in the app, which often leads to a noticeable increase in conversion rates for our clients. To enhance the searchability of help documents and Instant Answers, HelpHub employs semantic search technology, which focuses on the meaning behind the words rather than just the terms themselves. This feature is particularly beneficial as users may not always be familiar with the specific vocabulary used in your application. As a result, even if they search using approximate phrases related to your app's terminology, they are still likely to receive relevant answers to their inquiries. This capability not only improves user satisfaction but also contributes to a more intuitive support experience.

Paradise employs advanced unsupervised machine learning alongside supervised deep learning techniques to enhance data interpretation and derive deeper insights. It creates specific attributes that help in extracting significant geological information, which can then be utilized for machine learning analyses. The system identifies attributes that exhibit the most variation and influence within a geological context. Additionally, it visualizes neural classes and their corresponding colors from Stratigraphic Analysis, which reveal the spatial distribution of different facies. Faults are detected automatically through a combination of deep learning and machine learning methods. Furthermore, it allows for a comparison between machine learning classification outcomes and other seismic attributes against traditional high-quality logs. Lastly, it generates both geometric and spectral decomposition attributes across a cluster of computing nodes, achieving results in a fraction of the time it would take on a single machine. This efficiency enhances the overall productivity of geoscientific research and analysis.

Allganize offers top-notch AI solutions designed to enhance the efficiency of customer and employee support for businesses. Within just four months of implementation, companies can automate approximately 72% of their monthly support inquiries. Our AI is capable of managing straightforward customer requests, allowing support agents to focus on more challenging problems. Employees can engage in a conversational manner to seek information from various document formats. The pre-trained conversational AI chatbot is optimized for your website, streamlining customer service operations. Additionally, our intelligent search functionality swiftly extracts precise answers from any type of document. It also identifies significant keywords within documents and organizes them, yielding valuable insights. The system adeptly interprets the context of product reviews by using natural language processing to identify whether experiences are positive or negative. Furthermore, it classifies customer support conversations into predefined categories to accurately ascertain user intent and improve service delivery. This comprehensive approach not only enhances operational efficiency but also fosters a better overall experience for both customers and employees alike.

Ontosight.ai serves as an advanced research assistant powered by artificial intelligence, enabling businesses and researchers to derive more informed insights through the application of natural language processing and machine learning techniques to extensive unstructured data. By allowing users to extract meaningful insights, automate various research activities, and support data-driven decision-making, it enhances operational efficiency. The platform caters to a wide range of sectors, including finance, healthcare, and market research, offering capabilities such as sentiment analysis, trend identification, and competitor evaluation. Featuring a user-friendly interface, Ontosight.ai empowers individuals to upload their datasets, streamline report creation, and tailor research inquiries, ultimately boosting productivity. Additionally, it integrates effortlessly with numerous data sources, ensuring users have a holistic understanding of their research requirements. This versatility not only enhances research quality but also fosters a more strategic approach to information management.

Monitor, monitor, and improve your cyberhealth throughout your entire ecosystem. Threat Meter provides an outside-in view into the security status of your entire IT infrastructure. Threat Meter allows you to see how your security posture compares with other risk categories based on the frequency at which you choose to monitor. You can identify and minimize external risks by learning about exploitable weaknesses, compliance issues as well as misconfigurations, open ports, and other issues. Detect and identify impersonating domains, social accounts, and mobile apps. Stop them before they target customers or employees. Monitor the surface, dark, and deep web. Track exposed data across online file storage, criminal forums and code repositories. Get the best insight into different phishing threats. Find typo squatting domains and phishing pages and take them down.

CogwiseAI employs an advanced generative model to generate text responses to user queries. This model effectively recognizes linguistic patterns and connections thanks to extensive exposure to a large dataset of text. Our innovative technology harnesses cutting-edge machine learning algorithms to scrutinize blockchain data, enabling users to make well-informed trading choices. This form of AI-driven trading empowers investors and traders to discern market trends, anticipate fluctuations, and execute lucrative trades informed by current data. Additionally, the creation of virtual characters through an AI bot integrates machine learning and natural language processing techniques, allowing for the development of interactive personas capable of engaging with users in digital settings. Our sophisticated model not only provides insights into blockchain, cryptocurrencies, and global matters but also delivers real-time analytics, forecasts, and alerts for traders. Furthermore, it adeptly pinpoints trading prospects, facilitates automated trade execution, and offers tailored strategies to enhance profit potential. By combining these features, our technology aims to revolutionize the trading experience in the digital market landscape.

Enhance your product's capabilities with artificial intelligence. Our platform provides an extensive range of ready-to-use models along with an intuitive no-code interface for creating custom models. Effortlessly integrate AI into your applications for a distinct competitive advantage. Sentiment analysis, often referred to as opinion mining, involves the extraction of subjective insights from textual data, including customer reviews, social media interactions, and feedback, categorizing these insights as positive, negative, or neutral. The significance of this technology has surged in recent years, with a growing number of businesses leveraging it to comprehend customer sentiments and requirements, ultimately leading to data-driven decisions that can refine their offerings and marketing approaches. By employing sentiment analysis, organizations can gain valuable insights into customer feedback, enabling them to enhance their products, services, and promotional strategies effectively. This advancement not only aids in improving customer satisfaction but also fosters innovation within the company.

Advanced video analysis technology can identify more than 20,000 different objects, locations, and activities within video content. It allows for the extraction of comprehensive metadata across various levels, including the entire video, individual shots, or specific frames. Users have the capability to define custom entity labels through AutoML Video Intelligence, tailoring the tool to their needs. Additionally, it offers the ability to gather insights in near real-time, using streaming video annotation alongside object-based event triggers. This functionality enables the creation of captivating customer experiences through highlight reels and personalized recommendations. Furthermore, it supports the recognition of over 20,000 objects, places, and actions in both stored and live video feeds. Users can search their video libraries in a manner similar to document searches, facilitating easier access to specific content. The rich metadata extracted can also serve to index, organize, and filter video assets, ensuring that the most relevant content is highlighted. With these features, organizations can leverage video data more effectively to enhance their operations and engage their audiences.

Choose two tailored cell groups by utilizing metadata to uncover their most significantly differentially expressed genes. Utilize the extensive collection of millions of cells from the integrated CZ CELLxGENE corpus for in-depth analysis. Conduct interactive examinations of datasets to investigate how gene expression patterns are influenced by spatial, environmental, and genetic variables through an intuitive no-code user interface. Gain insights into existing datasets or leverage them as a foundation to discover new cell subtypes and states. Census offers the capability to access any customized segment of standardized cell data available within CZ CELLxGENE, with opportunities for exploration in both R and Python. Delve into an interactive encyclopedia containing over 700 cell types that includes comprehensive definitions, marker genes, lineage information, and associated datasets all in one location. Additionally, you can browse and obtain hundreds of standardized data collections along with more than 1,000 datasets that detail the functionality of both healthy mouse and human tissues, enriching your research and understanding of cellular biology. This resource provides a valuable tool for researchers aiming to enhance their exploration of cellular dynamics and gene expression.

Developers should not waste time juggling AI APIs to perform essential tasks such as OCR, translations, sentiment analysis, PII removal, and text summarization. Intelligent API streamlines the process, allowing you to integrate AI-driven functionality into your apps and APIs with no complexity, hidden costs or runaway expenses. AI-Powered Smart Endpoints Document OCR – Extract text from receipts and invoices. Also, extract text from identity documents. Language Detection and Translation - Detect any language in a text or translate between 75+ different languages with ease. PII protection - Identify and redact personally identifiable data (PII) in any text by making a single phone call. Text Insights: Analyze sentiments or create concise summaries of long-form texts. Start instantly with 200 free credits.

Patentfield serves as a comprehensive platform for patent exploration and analysis, integrating sophisticated search capabilities, data visualization, and artificial intelligence features. It goes beyond mere patent searches by offering AI-driven semantic search and classification tools that expedite the patent screening process. The platform's AI has been trained on over 10 million patent documents, allowing it to comprehend word meanings and identify related patents effectively. By generating a similarity score that ranks results in descending order, users can swiftly access patent literature relevant to their specific technological inquiries without the need for pre-existing training datasets. Additionally, the similar image search functionality enables users to upload image data to find patents and design publications with comparable visuals, specifically focusing on the illustrations presented within those documents. Users can also input multiple drawings, facilitating searches that draw on a combination of various perspectives, such as six distinct views for design patents or a mix of exterior and internal images for regular patents, enhancing the overall search experience. This multifaceted approach to patent searching streamlines the process, making it more efficient and user-friendly.

Enhance your decision-making process with a smarter and quicker approach using our Enterprise Document Intelligence Platform, designed to transform raw data into actionable insights. This adaptable platform leverages advanced cognitive Machine Learning and Natural Language Processing algorithms to automatically classify, extract, enrich, and integrate pertinent, timely, and accurate information from various documents. Delivered as a service, this solution minimizes ownership costs and accelerates the realization of value. The platform operates through a systematic process: first, it CLASSIFIES by ingesting structured, semi-structured, or unstructured documents and utilizing semantic understanding alongside visual cues to identify and categorize them. Next, it EXTRACTS essential words, phrases, and text segments from both printed and handwritten materials while detecting signatures or annotations on pages, allowing for easy review and corrections of the extracted content. Furthermore, the AI system learns and improves from human corrections, enhancing its accuracy over time. Finally, the platform offers ENRICHMENT through customizable data verification, validation, standardization, and normalization, ensuring that the information you rely on is both reliable and relevant. With this comprehensive approach, organizations can unlock the full potential of their documents and drive informed decisions.

Beosin EagleEye offers 24/7 security monitoring and notification services for blockchain. It sends customers security alerts and warnings whenever it detects risks such as hacker attacks, frauds or flash loans. 1. 24x7 Monitoring of Blockchain Project Security 2. Risk Transaction Identification: Large Outflow, Flash Loans, Privileged Operation and Exploiter, among others. 3. Alerts and warnings in real-time about security incidents 4. Based on Off-chain and On-chain Data Analysis 5. Multi-dimensional Security Assessments 6. Notification of Blockchain Sentiment Support User Interface & Method API

Cultivate expertise in your field and enhance organic traffic to your website by utilizing high-caliber content metrics sourced directly from Google's vast database. Showcase your knowledge across a variety of subjects that resonate with your audience while addressing any gaps in information. Position yourself as a central knowledge hub through interconnected articles that encourage search engine algorithms to thoroughly explore your entire site. Elevate your position in search engine results by uncovering competitive topic strategies. Leverage user insights gathered from 'Google Suggest' to pinpoint relevant questions and trending ideas. The next step involves selecting from an extensive pool of keywords extracted from both Google Keyword and Google Suggest databases to meet customer needs and bolster your authority. Utilize Zen metrics to uncover the specific keywords your audience is actively searching for, organizing them based on the stages of your SEO campaigns. Additionally, employ proprietary technology to analyze Allintitle data, revealing keywords with high conversion potential yet minimal competition, thus enhancing your strategic positioning in the digital landscape. By consistently refining your content strategy and keyword focus, you create a sustainable pathway for growth and engagement.

An exclusively designed contract data management solution tailored for the financial services sector. Users can effortlessly drag and drop files, perform bulk uploads, or utilize a specially designed API to securely integrate scans into the Lyncs platform. Additionally, entity reference data can be uploaded to ensure precise organization of scans. The system incorporates automated duplicate detection, melding machine learning with rule-based hybrid auto-classification to enhance accuracy. Scans are systematically categorized by entity, type, and date, facilitating the precise extraction of terms while considering amendment chains. Various methodologies are employed to automatically retrieve data from documents, combining machine learning, established rules, and user-assisted data capture for optimal precision and effectiveness. Each phase of the document processing is supported by a role-based workflow, which allows for documents to be locked to restrict alterations by others, assigned to specific users, and transitioned between different workflow states through promotion or rejection. Furthermore, the platform includes comprehensive version tracking, auditing capabilities, and a data 'time-machine' feature for enhanced oversight and management. The combination of these features ensures an unparalleled level of control and accuracy in contract data management.

Fluxguard offers cloud-based website monitoring. Locate errors, defacement or other business-critical website modifications, even on complex web apps and multi-page, multistep sequences. Filter out irrelevant changes. To alert IT staff and business users to any changes to web pages, create simple rules. You can also delegate the analysis and monitoring to one of our Solution Architects, who will optimize monitoring and create a change report. Natural Language Processing is used to simplify monitoring. This allows variation detection of the extracted features of a document, such as people and products. These insights can be used to create compelling dashboards or unique interrelationship analysis. Staff remediation, analysis, and investigation will be done quickly with the change summaries. You will receive detailed reports as soon changes are detected.