Pryon Alternatives

IBM watsonx Assistant (Formerly Watson Assistant) is a market-leading enterprise conversational AI platform that allows you to build intelligent virtual and voice assistants that can provide customers with fast, consistent and accurate answers across any messaging platform, application, device or channel. Using artificial intelligence and large language models, watsonx Assistant learns from customer conversations, improving its ability to resolve issues the first time while removing the frustration of long wait times, tedious searches and unhelpful chatbots. Most chatbots try to mimic human interactions, frustrating customers when a misunderstanding arises. IBM watsonx Assistant is more than a chatbot. It knows when to search for an answer from a knowledge base, when to ask for clarity and when to direct users to a human agent for more assistance. And since it can be deployed in any cloud or on-premises environment – smarter AI is finally available wherever you need it.

Dialogflow from Google Cloud is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product. Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers.

Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language, conversational bots (“chatbots”). With Amazon Lex, you can build bots to increase contact center productivity, automate simple tasks, and drive operational efficiencies across the enterprise. As a fully managed service, Amazon Lex scales automatically, so you don’t need to worry about managing infrastructure.

Build natural language understanding and generation into your product with a few lines of code. The Cohere API provides access to models that read billions of web pages and learn to understand the meaning, sentiment, and intent of the words we use. Use the Cohere API to write human-like text by completing a prompt or filling in blanks. You can write copy, generate code, summarize text, and more. Compute the likelihood of text and retrieve representations from the model. Use the likelihood API to filter text based on chosen categories or selected criteria. With representations, you can train your own downstream models on a wide variety of domain-specific natural language tasks. The Cohere API can compute the similarity between pieces of text, and make categorical predictions by comparing the likelihood of different text options. The model has multiple lenses through which to view ideas, so that it can recognize abstract similarities between concepts as distinct as DNA and computers.

Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.

HumanFirst provides radically efficient infrastructure and workflows to explore, curate and scale your AI training data. We productize the capabilities to scale NLU & NLP. HumanFirst accelerates conversational AI. Real voice-of-the-customer data, always in the loop. HumanFirst Studio makes working with voice and text data to train and maintain natural language understanding NLU models a breeze. Replace costly, and ad-hoc data ingestion and labeling processes with a seamless experience that allows you to build and improve the performance of your AI with real data, immediately. Import your Search and Help Center requests, emails, live chat or voice call logs to continuously train AI that understands your customers. Discover intents and improve their accuracy. Guessing what intents you need to train, and coming up with training phrases manually is painful - and often leads to low coverage and accuracy of intents.

Watson Natural Language Understanding is a cloud native product that uses deep learning to extract metadata from text such as entities, keywords, categories, sentiment, emotion, relations, and syntax. Get underneath the topics mentioned in your data by using text analysis to extract keywords, concepts, categories and more. Analyze your unstructured data in more than thirteen languages. Out-of-the-box machine learning models for text mining provide a high degree of accuracy across your content. Deploy Watson Natural Language Understanding behind your firewall or on any cloud. Train Watson to understand the language of your business and extract customized insights with Watson Knowledge Studio. Maintain ownership of your data with the assurance that your data is safe and secure. IBM will not collect or store your data. By using our advanced natural language processing (NLP) service, we give developers the tools to process and extract valuable insights from unstructured data.

Arches AI provides tools to craft chatbots, train custom models, and generate AI-based media, all tailored to your unique needs. Deploy LLMs, stable diffusion models, and more with ease. An large language model (LLM) agent is a type of artificial intelligence that uses deep learning techniques and large data sets to understand, summarize, generate and predict new content. Arches AI works by turning your documents into what are called 'word embeddings'. These embeddings allow you to search by semantic meaning instead of by the exact language. This is incredibly useful when trying to understand unstructed text information, such as textbooks, documentation, and others. With strict security rules in place, your information is safe from hackers and other bad actors. All documents can be deleted through on the 'Files' page.

Build applications with conversational language understanding, an AI language feature that understands natural language to interpret user goals and extract key information from conversational phrases. Create multilingual, customizable intent classification and entity extraction models for your domain-specific keywords or phrases across 96 languages. Train in one natural language and use them in multiple languages without retraining. Quickly create intents and entities and label your own utterances. Add prebuilt components from a wide variety of commonly available types. Evaluate with built-in quantitative measurements like precision and recall. Use the simple dashboard to manage model deployments in the intuitive and user-friendly language studio. Use seamlessly with other features within Azure AI Language, as well as Azure Bot Service for an end-to-end conversational solution. Conversational language understanding is the next generation of Language Understanding (LUIS).

Language Understanding (LUIS): A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve. Add natural language to your apps. Designed to identify valuable information in conversations, LUIS interprets user goals (intents) and distills valuable information from sentences (entities), for a high quality, nuanced language model. LUIS integrates seamlessly with the Azure Bot Service, making it easy to create a sophisticated bot. Powerful developer tools are combined with customizable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly. Dictionaries are mined from the collective knowledge of the web and supply billions of entries, helping your model to correctly identify valuable information from user conversations. Active learning is used to continuously improve the quality of the models.

Graphlogic Conversational AI Platform consists on: Robotic Process Automation (RPA) and Conversational AI for enterprises, leveraging state-of-the-art Natural Language Understanding (NLU) technology to create advanced chatbots, voicebots, Automatic Speech Recognition (ASR), Text-to-Speech (TTS) solutions, and Retrieval Augmented Generation (RAG) pipelines with Large Language Models (LLMs). Key components: - Conversational AI Platform - Natural Language understanding - Retrieval augmented generation or RAG pipeline - Speech-to-Text Engine - Text-to-Speech Engine - Channels connectivity - API builder - Visual Flow Builder - Pro-active outreach conversations - Conversational Analytics - Deploy everywhere (SaaS / Private Cloud / On-Premises) - Single-tenancy / multi-tenancy - Multiple language AI

Integrate our text analytics APIs to add world-leading NLP into your product, platform, or application. The most feature-complete NLP feature stack on the market, 19 years in development and constantly being improved with new libraries, configurations, and models. Determine whether a piece of writing is positive, negative, or neutral. Sort and organize documents into customizable groups. Determine the expressed intent of customers and reviewers. Find people, places, dates, companies, products, jobs, titles, and more. Deploy our text analytics and NLP systems across any combination of on-premise, private cloud, hybrid cloud, and public cloud infrastructure. Our core text analytics and natural language processing software libraries are at your command. Suitable for data scientists and architects who want complete access to the underlying technology or who need on-premise deployment for security or privacy reasons.

Azure AI Language is a managed service for developing natural language processing applications. Identify key terms and phrases, analyze sentiment, summarize text, and build conversational interfaces. Use Language to annotate, train, evaluate, and deploy customizable AI models with minimal machine-learning expertise. From predefined entity categories for every business to text analytics for healthcare domains, out-of-box capabilities help you get started quickly with the ability to further customize and optimize when needed. Provide a few labeled examples to train your machine learning model for your specific use case. Custom multilingual models can be trained in one language and used for multiple other languages. Access GPT-powered advanced language models through Language Studio to quickly scan and suggest labels for your content. Extract, label, and redact vital information in text across multiple categories.

Instantly uncover what your competitors are missing using NLPatent's intuitive AI-powered patent search platform. NLPatent's AI-first approach to patent search leverages large language models to understand innovation in a way that is only recently possible. Inform R&D strategy by quickly assessing novelty and inventiveness, leading to better-informed patent applications and decreased prosecution time. Quantify risk and defend against threats by effortlessly locating critical references that were previously missed. Go to market with confidence, armed with the intelligence required to de-risk product development and avoid infringing on existing patents. Describing your invention in natural language allows NLPatent to assess relevancy by conceptual similarity rather than blindly matching keywords. NLPatent is uniquely designed to optimize search outcomes through user-driven refinement based on known prior art and new results saved within the app.

Find specific answers and trends from documents and websites using search powered by AI. Watson Discovery is AI-powered search and text-analytics that uses innovative, market-leading natural language processing to understand your industry’s unique language. It finds answers in your content fast and uncovers meaningful business insights from your documents, webpages and big data, cutting research time by more than 75%. Semantic search is much more than keyword search. Unlike traditional search engines, when you ask a question, Watson Discovery adds context to the answer. It quickly combs through content in your connected data sources, pinpoints the most relevant passage and provides the source documents or webpage. A next-level search experience with natural language processing that makes all necessary information easily accessible. Use machine learning to visually label text, tables and images, while surfacing the most relevant results.

A human-machine partnership enables computers to do monotonous tasks, freeing up humans to focus on the creative, interesting details. Saifr began with access to millions of documents representing the work of regulatory and compliance experts, and thousands of content creators. These data informed Saifr’s Natural Language Understanding (NLU) models, and these data are what make Saifr uniquely able to help mitigate regulatory and reputational risk. Traditional content workflows typically have many touchpoints and email hand-offs which are inefficient and pose security risks. Saifr's solutions foster collaboration between professionals, both inside and outside the organization, as well as with our NLU engine resulting in compliant materials that are created, reviewed, approved, and filed more efficiently. Our solutions help companies create compliant public communications faster.

GradientJ provides everything you need to build large language model applications in minutes and manage them forever. Discover and maintain the best prompts by saving versions and comparing them across benchmark examples. Orchestrate and manage complex applications by chaining prompts and knowledge bases into complex APIs. Enhance the accuracy of your models by integrating them with your proprietary data.

Onboard your data and models to Openlayer and collaborate with the whole team to align expectations surrounding quality and performance. Breeze through the whys behind failed goals to solve them efficiently. The information to diagnose the root cause of issues is at your fingertips. Generate more data that looks like the subpopulation and retrain the model. Test new commits against your goals to ensure systematic progress without regressions. Compare versions side-by-side to make informed decisions and ship with confidence. Save engineering time by rapidly figuring out exactly what’s driving model performance. Find the most direct paths to improving your model. Know the exact data needed to boost model performance and focus on cultivating high-quality and representative datasets.

Infosys Nia™ is an enterprise grade AI platform which simplifies the AI adoption journey for Business & IT. Infosys Nia supports end-to-end enterprise AI journey from data management, digitization of document and images, model development to operationalizing models. Nia’s advanced, modular and scalable capabilities address business needs across Enterprises. Nia Data provides highly effective tools and frameworks for complex data workflows to power further ML experimentation on the Nia AML workbench. The Nia DocAI platform automates the end-to-end document processing lifecycle from ingestion to consumption, using AI capabilities such as InfoExtractor, computer vision, NLP and cognitive search.

Existing personal computers are limited to understanding commands rather than complex human intentions. LAM first translates natural language requests into actionable steps and responses that the operating system can use in real-time. As opposed to application programming interfaces (APIs) that have limited functionality, LAM understands and operates human-oriented interfaces across all mobile and desktop environments. Not only does LAM understand how to interact with applications to achieve certain objectives, it also knows how to achieve it in a humanizing way.

Build a natural language interface for your data. NLP is at the core of modern enterprise data processing. We provide developers with the right tools to build production-ready NLP systems quickly and efficiently. Our open-source framework for scalable, API-driven NLP application architectures. We believe in sharing. Our software is open source. We value our community, and we make modern NLP easily accessible, practical, and scalable. Natural language processing (NLP) is a branch of AI that enables machines to process and interpret human language. In general, by implementing NLP, companies can leverage human language to interact with computers and data. Areas of NLP include semantic search, question answering (QA), conversational AI (chatbots), semantic search, text summarization, question generation, text generation, machine translation, text mining, speech recognition, to name a few use cases.

Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.

LaMDA, our latest research breakthrough, adds pieces to one of the most tantalizing sections of that puzzle: conversation. While conversations tend to revolve around specific topics, their open-ended nature means they can start in one place and end up somewhere completely different. A chat with a friend about a TV show could evolve into a discussion about the country where the show was filmed before settling on a debate about that country’s best regional cuisine. That meandering quality can quickly stump modern conversational agents (commonly known as chatbots), which tend to follow narrow, pre-defined paths. But LaMDA — short for “Language Model for Dialogue Applications” — can engage in a free-flowing way about a seemingly endless number of topics, an ability we think could unlock more natural ways of interacting with technology and entirely new categories of helpful applications.

SparkCognition, a leading industrial AI company, has developed a natural language processing solution that automates workflows of unstructured data within organizations so humans can focus on high-value business decisions. The DeepNLP product uses advanced machine learning techniques to automate the retrieval of information, the classification of documents, and content analytics. The DeepNLP product integrates into existing workflows to enable organizations to better respond to changes in their business and quickly get answers to specific queries or analytics that support decision-making.

Run multiple campaigns across channels like WhatsApp, Facebook Messenger, Google Business Messaging, and more. Reap sales benefits by building the conversational flow, publishing omnichannel, and analyzing each report to hit the target. Engage and deliver meticulous responses to consumers in the form of rich snippets while customizing them to fit any scenario. Enrich customer experience by populating and intuitively visualizing data. Powered your conversations with an AI chatbot that keeps getting smarter every time. Auto-segment inquiries to the right agent, trigger handoffs when needed, and take complete control over your customer support management. Intelligent assistants automatically identify each user’s intent using NLP and respond back with intent-specific solutions. The response uses pattern recognition and metadata extraction from the service providers or databases. Keep track of everything happening across your channels to maintain an optimum customer relationship.

Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning, not just keywords! Make use of and compare the latest pre-trained transformer-based languages models like OpenAI’s GPT-3, BERT, RoBERTa, DPR, and more. Build semantic search and question-answering applications that can scale to millions of documents. Building blocks for the entire product development cycle such as file converters, indexing functions, models, labeling tools, domain adaptation modules, and REST API.

GPT-3.5 is the next evolution of GPT 3 large language model from OpenAI. GPT-3.5 models can understand and generate natural language. We offer four main models with different levels of power suitable for different tasks. The main GPT-3.5 models are meant to be used with the text completion endpoint. We also offer models that are specifically meant to be used with other endpoints. Davinci is the most capable model family and can perform any task the other models can perform and often with less instruction. For applications requiring a lot of understanding of the content, like summarization for a specific audience and creative content generation, Davinci is going to produce the best results. These increased capabilities require more compute resources, so Davinci costs more per API call and is not as fast as the other models.

GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time (opens in a new window) in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.

Our GPT-3 models can understand and generate natural language. We offer four main models with different levels of power suitable for different tasks. Davinci is the most capable model, and Ada is the fastest. The main GPT-3 models are meant to be used with the text completion endpoint. We also offer models that are specifically meant to be used with other endpoints. Davinci is the most capable model family and can perform any task the other models can perform and often with less instruction. For applications requiring a lot of understanding of the content, like summarization for a specific audience and creative content generation, Davinci is going to produce the best results. These increased capabilities require more compute resources, so Davinci costs more per API call and is not as fast as the other models.

The TextRazor API helps you extract and understand the Who, What, Why and How from your news stories with unprecedented accuracy and speed. Entity Extraction, Disambiguation and Linking. Keyphrase Extraction. Automatic Topic Tagging and Classification. All in 12 languages. Deep analysis of your content to extract Relations, Typed Dependencies between words and Synonyms, enabling powerful context aware semantic applications. Rapidly extract custom products, companies and build problem specific rules for tagging your content with your own categories. TextRazor offers a complete cloud or self-hosted text analysis infrastructure. We combine state-of-the-art natural language processing techniques with a comprehensive knowledgebase of real-life facts to help rapidly extract the value from your documents, tweets or web pages.

GPT-4 (Generative Pre-trained Transformer 4) is a large-scale unsupervised language model, yet to be released by OpenAI. GPT-4 is the successor to GPT-3 and part of the GPT-n series of natural language processing models, and was trained on a dataset of 45TB of text to produce human-like text generation and understanding capabilities. Unlike most other NLP models, GPT-4 does not require additional training data for specific tasks. Instead, it can generate text or answer questions using only its own internally generated context as input. GPT-4 has been shown to be able to perform a wide variety of tasks without any task specific training data such as translation, summarization, question answering, sentiment analysis and more.

Query, explore, and share data at ease. Askdata is the first platform that makes data interaction frictionless. Connect all your data by clicking the "+" icon in the top right corner. Collect the results of your research and analysis in easy-to-use data cards. Refine your data cards with charts, images, and personalized content and share them on the web, chat and apps. In order to create the data experience, we leverage all your existing data and analytics platforms to create a personalized experience through natural language and proactive insights. We give users the ability to answer any data-related questions with a simple search. Users can ask questions about their connected data instantly using Askdata's natural language querying technology, no training is needed. Our proprietary Human2SQL algorithm improves itself with every single search. Askdata uses cutting-edge AI and knowledge graph techniques to help users surface relevant content that is organized in data cards.

Our Natural Language Processing(NLP) APIs provide best-in-class accuracy at an affordable rate and cover all aspects of NLP under a single roof. Save weeks of time training and creating language models. Take advantage of our best-in-class APIs to kickstart your app development. We provide the building blocks to create your own apps effectively like chatbots, sentiment analysis, etc. Text classification on multiple domains and 100+ languages. Perform effective sentiment analysis. We grow when your business does. So we have put together simple pricing that allows you to easily scale your business when it needs to evolve. Perfect for individual developers who are creating apps or building proof of concepts. Head to the Dashboard and get your API Key. Place this in the header of all your API calls. Use our SDK in your preferred language to start coding. Or you can refer to the auto-generated code blocks provided in 18 programming languages.

OpenText™ Unstructured Data Analytics products employ AI and machine learning to help organizations uncover and leverage key insights stored deep within their unstructured data, including text, audio, video, and images. Organizations can connect all their data to understand the context and information locked inside high-growth unstructured content—at scale. Discover insights hidden within all types of media with unified text, speech, and video analytics that support more than 1,500 data formats. Use natural language processing, optical character recognition (OCR), and other AI-powered models to understand and track the meaning within unstructured data. Employ the latest innovations in machine learning and deep neural networks to understand written and spoken language in data, revealing greater insights.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for developing better, faster and stronger AI. We help our customers create innovative solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. The platform comes with the broadest repository of pre-trained, out-of-the-box AI models built with millions of inputs and context. Our models give you a head start; extending your own custom AI models. Clarifai Community builds upon this and offers 1000s of pre-trained models and workflows from Clarifai and other leading AI builders. Users can build and share models with other community members. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been recognized by leading analysts, IDC, Forrester and Gartner, as a leading computer vision AI platform. Visit clarifai.com

PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. Return results and detect fraud faster with ML at the database layer. PostgresML abstracts the data management overhead from the ML/AI lifecycle by enabling users to run ML/LLM models directly on a Postgres database.

Google AI Studio is a free, web-based tool that allows individuals and small teams to develop apps and chatbots using natural-language prompting. It also allows users to create prompts and API keys for app development. Google AI Studio is a development environment that allows users to discover Gemini Pro APIs, create prompts, and fine-tune Gemini. It also offers a generous free quota, allowing 60 requests per minute. Google also has a Generative AI Studio, which is a product on Vertex AI. It includes models of different types, allowing users to generate content that may be text, image, or audio.

Whether you're building an AI copilot, or chatbot, or enhancing your existing application with LLMs, Graphlit makes it simple. Built on a serverless, cloud-native platform, Graphlit automates complex data workflows, including data ingestion, knowledge extraction, LLM conversations, semantic search, alerting, and webhook integrations. Using Graphlit's workflow-as-code approach, you can programmatically define each step in the content workflow. From data ingestion through metadata indexing and data preparation; from data sanitization through entity extraction and data enrichment. And finally through integration with your applications with event-based webhooks and API integrations.

Powerful language models a click away. Join over 8,000 developers building the next wave of world-changing applications. Fine-tune and deploy GPT-J, GPT-NeoX, Codegen, and FLAN-T5. Multiple models, each with different capabilities and price points. GPT-J is the fastest model, while GPT-NeoX is the most powerful—and more are on the way. Use these models for classification, entity extraction, code generation, chatbots, content generation, summarization, paraphrasing, sentiment analysis, and much more. These models have been pre-trained on a vast amount of text from the open internet. Fine-tuning improves upon this for specific tasks by training on many more examples than can fit in a prompt, letting you achieve better results on a wide number of tasks.

Baidu Natural Language Processing, based on Baidu’s immense data accumulation, is devoted to developing cutting-edge natural language processing and knowledge graph technologies. Natural Language Processing has open several core abilities and solutions, including more than ten kinds of abilities such as sentiment analysis, address recognition, and customer comments analysis. Based on word segmentation, part-of-speech tagging, and named entity recognition technology, lexical analysis allows you to locate basic language elements, get rid of ambiguity, and support accurate understanding. Based on deep neural networks and massive high-quality data on the internet, semantic similarity is possible to calculate the similarity of two words through vectorization of words, meeting the business scenario requirements for high precision. Word vector representation can calculate texts through the vectorization of words and it can help you quickly complete semantic mining.

Semantria is a natural language processing (NLP) API from Lexalytics, leaders in enterprise sentiment analysis and text analytics since 2004. Semantria offers multi-layered sentiment analysis, categorization, entity recognition, theme analysis, intention detection and summarization in an easy-to-integrate RESTful API package. Semantria is totally customizable through graphical configuration tools, supports 24 languages, and can be deployed across private, public and hybrid clouds. Semantria scales effortlessly from single servers to entire data centers and back again to meet your on-demand processing needs. Integrate Semantria to add powerful, flexible text analytics and natural language processing capabilities to your cloud-based data analytics products or enterprise business intelligence infrastructure. Or add Lexalytics storage and visualization tools to create a complete business intelligence platform for storing, managing, analyzing and visualizing text documents.

ChatGPT retrieval plugin on steroids. Intelligent document indexing services for smarter answers. In order to get accurate ChatGPT answers it's crucial to have spans of text that respect the context of the original document. Current OpenAI text chunking services split the text based only on punctuation marks every 200 words. Pigro provides AI-based text chunking services that split content like a human would, considering the look and structure of the document, such as pagination, headings, tables, lists, images, etc. Our API natively supports Office-like documents, PDF, HTML, and plain text in many languages. Pigro delivers only the most relevant spans of text that answer the query. Our generative AI expands each of your content: we generate all possible questions answered within your document. Our search uses keywords and semantics, considering the title, body, and generated questions. Best-in-class accuracy with generative indexing.

The open-source ML observability platform. Evaluate, test, and monitor ML models from validation to production. From tabular data to NLP and LLM. Built for data scientists and ML engineers. All you need to reliably run ML systems in production. Start with simple ad hoc checks. Scale to the complete monitoring platform. All within one tool, with consistent API and metrics. Useful, beautiful, and shareable. Get a comprehensive view of data and ML model quality to explore and debug. Takes a minute to start. Test before you ship, validate in production and run checks at every model update. Skip the manual setup by generating test conditions from a reference dataset. Monitor every aspect of your data, models, and test results. Proactively catch and resolve production model issues, ensure optimal performance, and continuously improve it.

Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main components, estimators and transformers. The estimators have a method that secures and trains a piece of data to such an application. The transformer is generally the result of a fitting process and applies changes to the target dataset. These components have been embedded to be applicable to Spark NLP. Pipelines are a mechanism for combining multiple estimators and transformers in a single workflow. They allow multiple chained transformations along a machine-learning task.

ChatGPT is a language model developed by OpenAI. It has been trained on a diverse range of internet text, allowing it to generate human-like responses to a variety of prompts. ChatGPT can be used for various natural language processing tasks, such as question answering, conversation, and text generation. ChatGPT is a pre-trained language model that uses deep learning algorithms to generate text. It was trained on a large corpus of text data, allowing it to generate human-like responses to a wide range of prompts. The model has a transformer architecture, which has been shown to be effective in many NLP tasks. In addition to generating text, ChatGPT can also be fine-tuned for specific NLP tasks such as question answering, text classification, and language translation. This allows developers to build powerful NLP applications that can perform specific tasks more accurately. ChatGPT can also process and generate code.

Luminoso turns unstructured text data into business-critical insights. Using common-sense artificial intelligence to understand language, we empower organizations to discover, interpret, and act on what people are telling them. Requiring little setup, maintenance, training, or data input, Luminoso combines world-leading natural language understanding technology with a vast knowledge base to learn words from context – like humans do – and accurately analyze text in minutes, not months. Our software provides native support in over a dozen languages, so leaders can explore relationships in data, make sense of feedback, and triage inquiries to drive value, fast. Luminoso is privately held and headquartered in Boston, MA.

Scale's mission is to accelerate the development of AI applications. Better data leads to more performant models. Performant models lead to faster deployment. We help deliver value from AI investments faster with better data by providing an end-to-end solution to manage the entire ML lifecycle. Combining cutting edge technology with operational excellence, we help teams develop the highest-quality datasets because better data leads to better AI.

Conversational Intelligence is a unique way for the human user to collaborate with a machine. Humans bring to the table their intuition, and the machine comes with its ability to self-drive through data uncovering interesting patterns. Thus, humans and machines play to their strengths and collaborate to discover hidden gems in data. Using the unique Conversational Intelligence technology pioneered by DataChat, now you can carry out a broad range of data analytics functions, including exploratory data analysis, predictive analytics, structured querying, free search querying, visualization and data wrangling in a single platform. And you can do this by simply conversing with the platform in controlled natural language. Do more with less, and faster. Get richer and faster insights from data even with small teams, and move your business at the speed of data. Improve your competitive advantage. DataChat AI is a conversational, natural language, data analytics platform

With our enterprise Gen AI stack, go beyond your imagination and offload manual tasks to powerful assistants instantly – the sky is the limit. For enterprises where data security is paramount, fine-tune and deploy generative AI models on your own cloud, securely.

Cortical.io delivers AI-based Natural Language Understanding (NLU) solutions like Contract Intelligence and Message Intelligence which enable enterprises to more effectively search, extract, annotate and analyze key information from any kind of unstructured text. Cortical.io artificial intelligence-based solutions can be quickly trained unsupervised in the specialized vocabulary of any business domain and can function across multiple languages. They have been implemented at multiple Fortune 500 businesses, covering a wide spectrum of use cases,