Best Natural Language Processing Software in India - Page 5

Secuvy, a next-generation cloud platform, automates data security, privacy compliance, and governance via AI-driven workflows. Unstructured data is treated with the best data intelligence. Secuvy, a next-generation cloud platform that automates data security, privacy compliance, and governance via AI-driven workflows is called Secuvy. Unstructured data is treated with the best data intelligence. Automated data discovery, customizable subjects access requests, user validations and data maps & workflows to comply with privacy regulations such as the ccpa or gdpr. Data intelligence is used to locate sensitive and private information in multiple data stores, both in motion and at rest. Our mission is to assist organizations in protecting their brand, automating processes, and improving customer trust in a world that is rapidly changing. We want to reduce human effort, costs and errors in handling sensitive data.

Across the globe, organizations utilize the Eigen platform to enhance operational efficiency, inform critical business decisions, and capitalize on previously overlooked opportunities by tapping into unstructured data contained within documents. This platform caters to the data requirements of various departments, including operations, finance, legal, risk, compliance, and customer service teams. Your focus should be on making informed and timely decisions rather than sifting through countless pages of documents. The no-code Document AI solution offered by Eigen requires only between 2 to 50 documents to initiate its training process. You have the flexibility to begin with pre-designed question templates or apply your own insights to create tailored models. Eigen is designed to provide superior accuracy even with a limited number of documents while ensuring data security throughout the process. By leveraging the Eigen platform, you can swiftly and accurately unlock the valuable information in your documents, which empowers you to manage risks more effectively and enhance your decision-making capabilities. Ultimately, this innovative approach not only streamlines workflows but also transforms the way teams interact with data.

ResoluteAI offers a secure platform that allows users to simultaneously search through a variety of aggregated scientific, regulatory, and business databases. The platform's interactive analytics and downloadable visualizations enable users to forge connections that may lead to significant breakthroughs. Nebula, which is ResoluteAI's enterprise search solution tailored for the scientific community, leverages structured metadata alongside a suite of AI tools that enhance your institutional knowledge. This sophisticated approach incorporates various technologies such as natural language processing, optical character recognition, image recognition, and transcription, making it easier to locate and access proprietary information. With Nebula, researchers have the capability to reveal the latent value within their studies, experiments, market intelligence, and acquired assets. By utilizing structured metadata derived from unstructured text, users benefit from features like semantic expansion, conceptual search, and document similarity search, ensuring a comprehensive exploration of their data. This innovative platform transforms the way scientific data is accessed and utilized, paving the way for enhanced research outcomes.

The insurance sector focuses on achieving optimal rates and effectively managing risk. In such a competitive landscape, reducing manual processes is essential to distinguish ourselves from other industry players. A significant workforce is often necessary to sift through, interpret, categorize, analyze, and disseminate information for underwriting and support activities. Much of this information is unstructured and text-based, requiring manual examination. Scaling operations typically involves hiring additional personnel or resorting to outsourcing solutions. It is vital to filter and classify complaints based on their subject matter and severity level. Automotive businesses collect these complaints through various channels, including emails, feedback forms, and comments. Lymba’s Underwriting and Support NLP solution addresses the text-heavy challenges by converting data into actionable insights; this efficiency not only saves time and resources but also facilitates the initial review process, ultimately enhancing overall productivity and decision-making. By leveraging such technology, companies can focus more on strategic initiatives rather than getting bogged down by manual data handling.

At SoundHound Inc., we envision a world where every brand has a distinct voice and individuals can effortlessly engage with the products around them through natural conversation. Collaborating with our strategic partners, we aim to foster a more inclusive and interconnected environment. Our mission includes developing tailored voice assistants for businesses that prioritize their brand identity, user engagement, and data security. Leveraging our proprietary Speech-to-Meaning® and Deep Meaning Understanding® technologies, the Houndify platform delivers a level of conversational intelligence that is unparalleled in the industry. Embrace the future with Houndify! By voice-enabling the world, we strive to create a voice AI platform that surpasses human capabilities, adding value and enjoyment through an expansive ecosystem enriched by innovation and monetization potential. With our headquarters situated in Silicon Valley, we operate as a global entity, boasting nine offices across essential markets and teams spanning 16 countries, all dedicated to transforming the way people interact with technology. Our commitment to enhancing user experiences through cutting-edge voice technology is at the core of everything we do.

At Iris.ai we have spent the last 6 years building an award-winning AI engine for scientific text understanding. Our algorithms for text similarity, tabular data extraction, domain-specific entity representation learning and entity disambiguation and linking measure up to the best in the world. On top of that, our machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it and also give feedback to the system. The Iris.ai Researcher Workspace is a flexible tool suite that allows to approach a project in a variety of ways. Modules include content based explorative search, machine analysis of document sets, extracting and systematizing data points, automatically writing summaries of multiple documents - and very powerful filters based on context descriptions, the machine’s analysis, or specific data points or entities. The Iris.ai engine for scientific text understanding is a powerful interdisciplinary system that can be automatically reinforced on a specific research field for much more nuanced machine understanding - without human training or annotation.

SentioAI is an innovative technology solution that leverages natural language processing, machine learning, and predictive analytics to swiftly and accurately pinpoint the most pertinent documents from a vast array. By addressing the classification challenges inherent in Big Data through its unique proprietary methods, SentioAI outperforms other technologies, providing quicker and more precise results while also being cost-effective. The system ranks documents from the most to least relevant, allowing users to review and tag a small subset of the dataset. This tagged data trains SentioAI's prediction engine, which continuously enhances its accuracy with each new document added. The system intelligently assesses when the training phase is complete and subsequently applies its models to the entire dataset to produce comprehensive results. Ultimately, SentioAI not only accelerates the document retrieval process but also ensures that users receive the most reliable information efficiently.

The Rinalogy Classification API offers a flexible machine learning solution that seamlessly integrates into your existing application while allowing you to operate within your own infrastructure. In contrast to traditional cloud-based machine learning APIs that necessitate data transfer and operate in an external environment, Rinalogy allows for deployment within your IT framework, ensuring data security and compliance as it works behind your firewall. This API utilizes Exhaustive Sequential Classification, systematically applying models to every document within a dataset. The models generated can be enhanced with additional training data or leveraged for predicting outcomes on new documents at a later time. With its ability to scale through cluster deployment, you can modify the number of workers based on your current workload needs. Furthermore, the Rinalogy API empowers client applications by incorporating features such as text classification, enhanced search capabilities, and personalized recommendations, providing a comprehensive toolkit for data-driven decision-making. This versatility makes it an appealing choice for organizations aiming to optimize their machine learning processes while maintaining control over their data.

Wluper, an advanced voice-based conversational Ai platform that allows workers to leverage advanced natural languages capabilities to create meaningful experiences, is called Wluper. You can calibrate and create the workforce experience in your sector or industry, strengthen your position, and empower your staff with a unique solution that scales.

The collaboration between humans and machines allows computers to handle repetitive tasks, thus enabling people to concentrate on more creative and engaging aspects of their work. Saifr was built upon a vast array of documents that reflect the expertise of regulatory and compliance professionals, along with insights from numerous content creators. This extensive information has shaped Saifr's Natural Language Understanding (NLU) models, empowering the platform to effectively reduce regulatory and reputational risks. In contrast to traditional content processes, which often involve numerous hand-offs and email exchanges that can lead to inefficiencies and potential security vulnerabilities, Saifr's innovative solutions promote seamless teamwork among professionals, both within and beyond their organizations. By integrating with our NLU engine, these solutions ensure that compliant materials are generated, assessed, approved, and submitted in a more streamlined manner. Consequently, businesses benefit from the ability to produce compliant public communications at a significantly faster pace. Ultimately, the partnership between technology and human creativity enhances overall productivity and fosters a more efficient approach to compliance.

Industry experts indicate that unstructured data stands as the most significant source of untapped and undervalued customer information, and its growth is accelerating in today's customer-focused landscape. In an age characterized by Big Data, where corporate data doubles approximately every three months, effectively leveraging this information has become essential for maintaining a competitive edge and ensuring business longevity. EpiAnalytics offers Artificial Intelligence (AI) solutions tailored to meet your business requirements, enabling you to extract greater value from the data you already possess, no matter where it is stored. Our solutions aim to boost sales, enhance data quality, guarantee compliance, and improve operational efficiencies. By integrating our legacy VINoptions product with its AI and VIN data engineering capabilities and our extensive ChromeData vehicle data catalog that spans 30 years, we have developed an advanced VIN decoding solution. Additionally, ChromeData VIN Descriptions have become the industry benchmark for accurately identifying and detailing vehicles based on their VIN. This innovative approach not only streamlines processes but also empowers businesses to make data-driven decisions with confidence.

Our platform for comparative text analysis, rooted in a commitment to online child safety, helps unlock significant business insights from your existing text data. Relative Insight’s innovative technology empowers marketing professionals and brand experts to enhance the value derived from their text resources. By employing a comparative methodology, we facilitate the rapid generation of in-depth audience insights at scale, enriching your qualitative analysis with a level of sophistication and rigor. With these unique marketing insights, brands have the potential to refine their communications, optimize brand positioning, and create more impactful campaigns. Our platform streamlines the process of interpreting and leveraging unstructured data, significantly cutting down your analysis time. Additionally, this methodology is applicable to a variety of primary research formats, including interviews, focus groups, and videos, revealing the wealth of data you may not even realize you have. Relative Insight also allows for direct comparisons of your brand messaging with that of your competitors, ensuring you remain competitive in your market. By exploring these insights, brands can better connect with their audiences and drive engagement.

Canvs AI is an insight platform that transforms open-ended texts from surveys, social media and transcripts into conversational intelligence. It can also be used to analyze product reviews and other information such as product reviews and product reviews. Canvs is used worldwide by some of the most respected brands, research agencies, media and entertainment companies to speed up time-to-insights and deepen understanding of audience. It also reduces the cost of analysis. Automate the analysis and interpretation of open-ended text to quickly uncover consumer insights with deep emotional context and high analytical confidence. Canvs' intuitive and easy-to-use insights portal allows you to quickly explore, filter and compare your findings. You can also generate stunning data visualizations. Automate the coding of attribute, recall, and awareness questions. Quickly identify and categorize sentiments and emotions associated with respondents and responses.

In the course of patient treatment, physicians typically dedicate around two-thirds of their time to documenting care instead of focusing on examinations or engaging in patient discussions. To enhance the time doctors can allocate to patient interaction, Averbis is developing Speech2Structure, an innovative software solution that captures documentation in real-time through voice input and organizes it immediately. This system is adept at accurately identifying and addressing various linguistic nuances, including negations and different types of diagnoses, as it processes information. Additionally, it translates pathological lab results and microbiology findings into relevant diagnoses, further streamlining the documentation process. Moreover, the medications noted during consultations can also offer significant insights regarding potential diagnoses, thereby enriching the overall clinical picture.

Business data can be found in many formats and from different sources. Many business data is not structured or semi-structured. IDP (Intelligent Document Processing), which uses AI and programmable automation (such repetitive tasks) to convert business data into usable, structured formats and for consumption by downstream system. Blox.ai uses Natural Language Processing (NLP), Computer Vision, (CV) and machine learning tools to identify, label and extract relevant data from any type. The AI then converts the extracted information into a structured format and creates a model that can be used for all types of similar documents. Blox.ai is used to reconcile data based upon business requirements and push the output to downstream system automatically.

Our platform, designed with regulatory compliance in mind, enhances clinical research by using algorithms to sift through unstructured EMR data to identify life-threatening conditions. We create cutting-edge technologies that broaden access to groundbreaking healthcare solutions through Clinical Trials. Our dedicated team is committed to saving lives by facilitating access to therapeutic innovations that are still being researched. We strongly advocate that every patient should be informed and empowered regarding their potential to engage in clinical trials that could offer significant therapeutic benefits. As a forward-thinking healthcare AI research firm, we have created a computational platform that identifies patients who meet a detailed set of criteria for participation in clinical trials, ensuring that the most suitable candidates are considered for these critical studies. Through our work, we aim to revolutionize the way patients connect with life-changing treatment opportunities.

Sparrow serves as a research prototype and a demonstration project aimed at enhancing the training of dialogue agents to be more effective, accurate, and safe. By instilling these attributes within a generalized dialogue framework, Sparrow improves our insights into creating agents that are not only safer but also more beneficial, with the long-term ambition of contributing to the development of safer and more effective artificial general intelligence (AGI). Currently, Sparrow is not available for public access. The task of training conversational AI presents unique challenges, particularly due to the complexities involved in defining what constitutes a successful dialogue. To tackle this issue, we utilize a method of reinforcement learning (RL) that incorporates feedback from individuals, which helps us understand their preferences regarding the usefulness of different responses. By presenting participants with various model-generated answers to identical questions, we gather their opinions on which responses they find most appealing, thus refining our training process. This feedback loop is crucial for enhancing the performance and reliability of dialogue agents.

Baidu has developed ERNIE Bot, an AI-driven conversational assistant that aims to create smooth and natural interactions with users. Leveraging the ERNIE (Enhanced Representation through Knowledge Integration) framework, ERNIE Bot is adept at comprehending intricate queries and delivering human-like responses across diverse subjects. Its functionalities encompass text processing, image generation, and multimodal communication, allowing it to be applicable in various fields, including customer service, virtual assistance, and business automation. Thanks to its sophisticated understanding of context, ERNIE Bot provides an effective solution for organizations looking to improve their digital communication and streamline operations. Furthermore, the bot's versatility makes it a valuable tool for enhancing user engagement and operational efficiency.

Incorporate our advanced text analytics APIs to infuse your product, platform, or application with state-of-the-art natural language processing capabilities. Boasting the most comprehensive NLP feature set available, our technology has been refined over 19 years and is continually updated with new libraries, configurations, and models. You can assess whether a written piece conveys a positive, negative, or neutral sentiment, as well as sort and categorize documents into tailored groups. Additionally, our system can identify the expressed intentions of customers and reviewers, and extract pertinent information such as people, locations, dates, companies, products, jobs, and titles. You have the flexibility to deploy our text analytics and NLP solutions across a variety of infrastructures, including on-premise, private cloud, hybrid cloud, and public cloud environments. Our foundational software libraries for text analytics and natural language processing are fully accessible and at your service. This offering is especially advantageous for data scientists and architects who seek unrestricted access to the core technology or require on-premise deployment to maintain security and privacy standards. Ultimately, our innovative solutions empower you to harness the full potential of language data effectively.

Explore the capabilities of text analytics and NLP software libraries that can be deployed on-premise or integrated seamlessly into your systems. You can incorporate Salience into your enterprise business intelligence framework or even customize it for your own data analytics solutions. With the ability to handle up to 200 tweets per second, Salience efficiently scales from individual cores to extensive data center infrastructures while maintaining a compact memory footprint. Choose from Java, Python, or .NET/C# bindings for user-friendly integration, or opt for the native C/C++ interface to achieve peak performance. Gain comprehensive control over the foundational technology, allowing you to fine-tune every aspect of text analytics and NLP functions, including tokenization, part of speech tagging, sentiment analysis, categorization, and thematic exploration. The platform is designed around a pipeline model consisting of NLP rules and machine learning algorithms, enabling you to pinpoint issues in the process easily. You can modify specific features without affecting the overall system's integrity. Moreover, Salience operates entirely on your own servers while remaining adaptable enough to transfer non-sensitive data to cloud environments, offering both security and versatility for your analytics needs. This flexibility empowers organizations to leverage advanced analytics features while ensuring data privacy and performance efficiency.

Business users have the ability to pose the same inquiries that they typically direct to the data team directly within platforms such as Slack, Teams, and email, without needing to adjust their phrasing or learn a new system. This seamless interaction ensures that all questions are cataloged in a comprehensive knowledge base, eliminating the need for repetitive inquiries; moreover, as Seek is utilized more frequently, it enhances its proficiency in managing your data. Equipped with a code editor, knowledge base, and integrations for data warehouses, Seek also prioritizes your data security, adhering to SOC2 Type I compliance while providing customizable user and group permissions. With these features, businesses can streamline their data inquiries with confidence, knowing that their information is both accessible and secure.

The MindMeld Conversational AI Platform is a comprehensive machine learning framework based in Python, designed to include all necessary algorithms and tools for creating high-quality conversational applications. Developed through years of experience in crafting and implementing numerous sophisticated interfaces, MindMeld excels in creating conversational assistants that possess a profound comprehension of specific use cases or domains, all while delivering highly effective and adaptable conversational interactions. It features robust command-line tools and Python APIs, providing the flexibility needed to meet diverse product demands. Users benefit from access to cutting-edge machine learning algorithms along with efficient management of extensive custom training datasets. Additionally, the platform incorporates improved entity recognition and resolution capabilities to effectively address automatic speech recognition (ASR) inaccuracies, further enhancing its utility in real-world applications. This adaptability makes it an invaluable asset for developers looking to create seamless conversational experiences.

We have been pioneers in the development of clinical NLP platforms and their applications for over 15 years. This has resulted in high precision and accuracy. Our core competency is to interpret unstructured notes accurately and at scale. Tested on billions of real clinical notes and documents. AI that can explain with context, reasoning, and evidence for output. NLP with medical knowledge infused with 4M+ entities and 50M+ relationships. Innovative Machine Learning (ML), & Deep Learning(DL) models were used to build this NLP. Use a foundation of rich ontologies and clinician-specific terminologies. We can understand, interpret, and extract context & significance from the inconsistent, inconsistent, and non-standard data contained in medical documents. Our clinical domain experts continually infuse knowledge graphs to our NLP by mapping all clinical entities and their relationship between them. We have more than 4,000,000 entities and 50,000,000 relationships.

Integrate your datasets and models into Openlayer while collaborating closely with the entire team to establish clear expectations regarding quality and performance metrics. Thoroughly examine the reasons behind unmet objectives to address them effectively and swiftly. You have access to the necessary information for diagnosing the underlying causes of any issues. Produce additional data that mirrors the characteristics of the targeted subpopulation and proceed with retraining the model accordingly. Evaluate new code commits against your outlined goals to guarantee consistent advancement without any regressions. Conduct side-by-side comparisons of different versions to make well-informed choices and confidently release updates. By quickly pinpointing what influences model performance, you can save valuable engineering time. Identify the clearest avenues for enhancing your model's capabilities and understand precisely which data is essential for elevating performance, ensuring you focus on developing high-quality, representative datasets that drive success. With a commitment to continual improvement, your team can adapt and iterate efficiently in response to evolving project needs.

Leverage cutting-edge NLP advancements by utilizing Haystack's pipeline architecture on your own datasets. You can create robust solutions for semantic search, question answering, summarization, and document ranking, catering to a diverse array of NLP needs. Assess various components and refine models for optimal performance. Interact with your data in natural language, receiving detailed answers from your documents through advanced QA models integrated within Haystack pipelines. Conduct semantic searches that prioritize meaning over mere keyword matching, enabling a more intuitive retrieval of information. Explore and evaluate the latest pre-trained transformer models, including OpenAI's GPT-3, BERT, RoBERTa, and DPR, among others. Develop semantic search and question-answering systems that are capable of scaling to accommodate millions of documents effortlessly. The framework provides essential components for the entire product development lifecycle, such as file conversion tools, indexing capabilities, model training resources, annotation tools, domain adaptation features, and a REST API for seamless integration. This comprehensive approach ensures that you can meet various user demands and enhance the overall efficiency of your NLP applications.