Alternatives to Embedditor

Qdrant is a vector database and similarity engine. It is an API service that allows you to search for the closest high-dimensional vectors. Qdrant allows embeddings and neural network encoders to be transformed into full-fledged apps for matching, searching, recommending, etc. This specification provides the OpenAPI version 3 specification to create a client library for almost any programming language. You can also use a ready-made client for Python, or other programming languages that has additional functionality. For Approximate Nearest Neighbor Search, you can make a custom modification to the HNSW algorithm. Search at a State of the Art speed and use search filters to maximize results. Additional payload can be associated with vectors. Allows you to store payload and filter results based upon payload values.

Artificial intelligence long-term memory The Pinecone vector database makes building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

Create a natural language interface to your data. NLP is the heart of modern enterprise data processing. We provide developers the tools they need to quickly and efficiently build NLP systems that are ready for production. Our open-source framework allows for API-driven, scalable NLP application architectures. We believe in sharing. Our software is open-source. We value our community and make modern NLP accessible, practical, scalable, and easy to use. Natural language processing (NLP), a branch in AI, allows machines to interpret and process human language. Companies can use human language to interact and communicate with data and computers by implementing NLP. NLP is used in areas such as semantic search, question answering (QA), conversational A (chatbots), text summarization and question generation. It also includes text mining, machine translation, speech recognition, and text mining.

With just a few lines, you can integrate natural language understanding and generation into the product. The Cohere API allows you to access models that can read billions upon billions of pages and learn the meaning, sentiment, intent, and intent of every word we use. You can use the Cohere API for human-like text. Simply fill in a prompt or complete blanks. You can create code, write copy, summarize text, and much more. Calculate the likelihood of text, and retrieve representations from your model. You can filter text using the likelihood API based on selected criteria or categories. You can create your own downstream models for a variety of domain-specific natural languages tasks by using representations. The Cohere API is able to compute the similarity of pieces of text and make categorical predictions based on the likelihood of different text options. The model can see ideas through multiple lenses so it can identify abstract similarities between concepts as distinct from DNA and computers.

Document processing can be complicated but it doesn't need to be. Intelligent document processing platform that can understand what you are trying to find, extract and categorize. Infinia ML uses machine-learning to quickly understand context and the relationships between words and charts. We can help you achieve your goals with our machine learning capabilities. Machine learning can help you make better business decisions. We tailor your code to your business problem, uncovering hidden insights and making accurate predictions to help your zero in on success. Our intelligent document processing solutions don't work by magic. They are based on decades of experience and advanced technology.

Use user feedback and semantic relevance to reliably retrieve optimal document chunks for your retrieval-augmented generation system. In your search system, combine semantic relevance with document freshness because recent results are more accurate. Create a personalized ecommerce feed in real-time using user vectors based on the SKU embeddings that were viewed by the user. A vector index in your warehouse can be used to discover behavioral clusters among your customers. Use spaces to build your indices, and run queries all within a Python Notebook.

Klevu is an intelligent site-search solution that helps e-commerce businesses increase their onsite sales and improve customer online shopping experience. Klevu powers the navigation and search experience for thousands of enterprise and mid-level online retailers. It leverages advanced semantic search, natural word processing, merchandising, and multilingual capabilities to ensure that visitors to your site find exactly the information they need, regardless of device or query complexity.

OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.

Search powered by AI allows you to find specific answers and trends in documents and websites. Watson Discovery is an AI-powered search engine and text-analytics. It uses market-leading natural language processing technology to understand the unique language of your industry. It quickly finds answers in your content and uncovers business insights from documents, webpages, and big data. This reduces research time by more that 75%. Semantic search goes beyond keyword search. Watson Discovery provides context for answers to questions, which is a departure from traditional search engines. It quickly scans your connected data sources to find the most relevant passage, and then provides the source documents or webpage. Natural language processing and next-level search capabilities make all information accessible.

The era of Big Data is here, where data-driven insights can transform your business. The solution is here: a powerful, innovative, and adaptive platform that provides all the features you need to search, discover, and analyze your data. It is called 3RDi "Third Eye" It is the semantic search engine your company needs to take action, increase revenues, and cut costs. It is powered by NLP and semantic searches and designed for multidimensional information analysis as well as easy search relevancy management. The comprehensive, scalable platform that solves every problem in search and text mining. It can manage unstructured content and extract deeper insights that will help you grow your business. 3RDi is more than a search engine. It offers a complete suite of solutions for text mining and enterprise search, as well as content integration, governance, analytics, and much more.

Vespa is forBig Data + AI, online. At any scale, with unbeatable performance. Vespa is a fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real-time. Users build recommendation applications on Vespa, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. To build production-worthy online applications that combine data and AI, you need more than point solutions: You need a platform that integrates data and compute to achieve true scalability and availability - and which does this without limiting your freedom to innovate. Only Vespa does this. Together with Vespa's proven scaling and high availability, this empowers you to create production-ready search applications at any scale and with any combination of features.

Security is a key part of our business. That's why Active Directory settings are the most secure distribution of rights. This ensures that files are only visible to the person who has been assigned. Many companies desire their own innovative search for the website and intranet. The Hulbee Enterprise Search software allows you to perform a semantic search that returns relevant results. You can also customize your search with API and SDK. Many companies are very technical and can adapt Hulbee Enterprise Search to suit their needs. We would be delighted to offer this opportunity! You can modify and expand our software in the same way as a Lego system. Everything can be linked via API and expanded with SDK, no matter if it is intranet or internet. You can also connect to our search your own development environment, so you are not dependent on third parties.

Zeta Alpha is the best Neural Discovery Platform to AI and beyond. You and your team can use state-of the-art NeuralSearch to improve the way you and others discover, organize, and share knowledge. Modern AI can help you make better decisions, avoid reinventing your wheel, and make it easier to stay in the know. The most up-to-date neural discovery across all relevant AI research sources and engineering information sources. With a seamless combination search, organization, recommendation, you can ensure that nothing is left behind. You can improve decision-making and reduce risks by having a single view of all relevant information, both internal and external. Get a clear view of what your team is reading or working on.

Vectara offers LLM-powered search as-a-service. The platform offers a complete ML search process, from extraction and indexing to retrieval and re-ranking as well as calibration. API-addressable for every element of the platform. Developers can embed the most advanced NLP model for site and app search in minutes. Vectara automatically extracts text form PDF and Office to JSON HTML XML CommonMark, and many other formats. Use cutting-edge zero-shot models that use deep neural networks to understand language to encode at scale. Segment data into any number indexes that store vector encodings optimized to low latency and high recall. Use cutting-edge, zero shot neural network models to recall candidate results from millions upon millions of documents. Cross-attentional neural networks can increase the precision of retrieved answers. They can merge and reorder results. Focus on the likelihood that the retrieved answer is a probable answer to your query.

Inbenta Semantic Search Engine's ability understand customer queries allows for more accurate results. The search engine is the most widely used self-service tool on websites, with 85% of sites using it. However, being able to provide the most relevant information could make the difference between a good and poor customer experience. Inbenta Search pulls data directly from your customer relationship tools such as Zendesk and Salesforce.com, as well as from other designated websites. The semantic Inbenta Search uses Inbenta Symbolic AI technology and Natural Language Processing technology to quickly understand customer questions and provide the most relevant answers. This will reduce support costs and help you save money. Inbenta Symbolic AI technology means there is no need to train data. This allows you to quickly deploy and use the Inbenta Search engine tool.

A true second brain for knowledge-based work. Orchard is an AI assistant that can converse with you and understand complex requests. Orchard Classic is still the best AI editor for text editing. Ask questions about your documents from wherever they are located. Neural search across all your documents + synthesis using AI = The best way to learn from your work. A text editor that can finish your sentences and suggest related ideas, based on your institutional knowledge. AI text editing is now contextually aware. Orchard should be your personal analyst, able to understand you and your work. Orchard will determine if and how it can use the information it has about you each time you submit a request. It's almost as if ChatGPT had cited sources that included resources relevant to your work. Orchard is able to break down complex tasks much more accurately than ChatGPT. Orchard creates a search engine that can find all your data. Orchard is being integrated with businesses.

Microsoft Purview is a unified data governance service that helps you manage and govern your on-premises, multicloud, and software-as-a-service (SaaS) data. You can easily create a comprehensive, up-to date map of your data landscape using automated data discovery, sensitive classification, and end to end data lineage. Data consumers can find trustworthy, valuable data. Automated data discovery, lineage identification and data classification across on and off-premises, multicloud, as well as SaaS sources. For more effective governance, a unified map of all your data assets and their relationships. Semantic search allows data discovery using technical or business terms. Get insight into the movement and location of sensitive data in your hybrid data landscape. Purview Data Map will help you establish the foundation for data usage and governance. Automate and manage metadata from mixed sources. Use built-in and customized classifiers to classify data and Microsoft Information Protection sensitive labels to protect it.

Apache Lucene™, an open-source search engine, is developed by the Apache Lucene™. The project releases Lucene™, a core search library. It also includes PyLucene, a python binding to Lucene. Lucene Core is a Java library providing powerful indexing and search features, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities. The PyLucene sub-project provides Python bindings to Lucene Core. The Apache Software Foundation supports the Apache community of open-source projects. Apache Lucene is available under a commercially-friendly Apache Software license. Apache Lucene is the benchmark for search and indexing performance. Lucene is the search engine for both Apache Solr™, and Elasticsearch™. Our core algorithms and the Solr search server power applications all over the globe, from mobile devices to websites like Twitter, Apple, Wikipedia, and Google. Apache Lucene's goal is to provide world-class search capabilities.

Production-ready AI models that are fast and accurate. High-availability inference API that leverages the most advanced NVIDIA GPUs. We have selected the most popular open-source natural language processing models (NLP) and deployed them for the community. You can fine-tune your models (including GPT-J) or upload your custom models. Then, deploy them to production. Upload your AI models, including GPT-J, to your dashboard and immediately use them in production.

Repustate is an AI-powered semantic search, sentiment analytics and text analysis platform that provides world-class AI-powered data mining for organizations worldwide. It allows businesses to analyze terabytes and uncover valuable, actionable business insights. Repustate offers continuous deep dives into complex, integrated data across all industries, from our respected clients in the Healthcare sector to leaders in Education, Banking, Governance. Our solution drives sentiment analysis, text analytics, Voice of Customer (VOC), video content analysis (VCA), across platforms. It covers the multitude of acronyms, emojis, and slangs that supersede formal language in social media. It doesn't matter if you have data from Youtube, IGTV or Facebook, Twitter, TikTok or your own customer reviews forums, employee surveys or EHRs. You can pinpoint the most important aspects of your business.

You can access countless corporate documents and systems, regardless of platform, and keep track millions of data. A combination of state-of-the art neural search techniques, enterprise search functionality, and many standard connectors create a new search experience. INTERGATOR Cloud can also be hosted by a German hoster. This allows you to comply with all requirements of German and European law, especially data protection. We adapt to your needs. INTERGATOR Cloud is easily scaleable to meet your search needs. You can search your company data anywhere in the world, and access information without complicated VPN solutions. Natural Language Processing (NLP), and neural networks are used to train models that can extract the most important information from documents and data, and then consider the entire information stock. This comprehensive solution provides you with the best information and knowledge management.

Vald is a distributed, fast, dense and highly scalable vector search engine that approximates nearest neighbors. Vald was designed and implemented using the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT for searching neighbors. Vald supports automatic vector indexing, index backup, horizontal scaling, which allows you to search from billions upon billions of feature vector data. Vald is simple to use, rich in features, and highly customizable. Usually, the graph must be locked during indexing. This can cause stop-the world. Vald uses distributed index graphs so that it continues to work while indexing. Vald has its own highly customizable Ingress/Egress filter. This can be configured to work with the gRPC interface. Horizontal scaling is available on memory and cpu according to your needs. Vald supports disaster recovery by enabling auto backup using Persistent Volume or Object Storage.

The complete platform for all aspects of research. {Instantly retrieve and wrangle the insights you need, no matter your source of unstructured data.|No matter what source of unstructured data, you can instantly retrieve and extract the insights that you need.} Find answers from millions of public sources like SEC Filings, Earnings Calls and expert network transcripts. Or leverage your firm's expertise. Hebbia can instantly connect to any source of unstructured information in your company, and can ingest any file type or API. You can work faster by using tools for diligence and research processes, regardless of the task. With a single click, you can spread financials, find public comps or structure unstructured information. Hebbia is trusted with the most sensitive data by some of the world's most powerful financial institutions and governments. Security is our core. Hebbia is the only encrypted search engine available on the market.

Jina Search makes it easy to search for any topic in seconds. It's faster and more accurate than traditional search engines. Our AI search captures all information stored in images, text, and provides you with the most comprehensive results. Jina Search unlocks the power of search to revolutionize how you find what your looking for. Classical Search was unable to retrieve relevant results because not all items in the dataset had the right label. Jina Search does not rely on tags and was able to find better items. Make the most of state-of-the art ML models that can work with multiple data types, including images and text. All customizations are maintained by Elasticsearch. Jina Search will automatically recognize each image in your database and store it accordingly.

Site Search 360 is an intelligent, ad-free search engine for your website. You can quickly get your search up-and-running with a simple drag and drop integration. Your visitors will find exactly what they need right away. Site Search 360 features include: Visual configuration is quick and simple Search suggestions and autocomplete Search results for Facet-organized Semantic Search: Built-in Dictionary in 19 Languages + the ability to add custom synonyms Analytics to help you get more out of your search: What are your visitors looking for? What results do they click on? What queries don't bring any results? Full control over search results: boost, reorder, redirect Integration with Google Analytics & Google Tag Manager Import of Google Custom Search Promotions Amazing support: Live chat, email, and phone

Natively store data for graphs, documents and search needs. One query language allows for feature-rich access. You can map data directly to the database and access it using the best patterns for the job: traversals, joins search, ranking geospatial, aggregateions - you name them. Polyglot persistence without the cost. You can easily design, scale, and adapt your architectures to meet changing needs with less effort. Combine the flexibility and power of JSON with graph technology to extract next-generation features even from large datasets.

Zevi is a site-search engine that uses natural language processing (NLP), and machine learning (ML), to better understand users' search intent. Zevi uses its ML models to produce the most relevant search results instead of relying on keywords. They have been trained using vast amounts of multilingual data. Zevi is able to deliver highly relevant results regardless of search query, providing users with an intuitive search experience that minimizes cognitive load. Zevi also allows website owners to create personalized search results, promote specific search results based upon different criteria, and use search data to inform business decisions.

Our commerce-specific digital experience platform, enables brands to deliver incredible, revenue-driving commerce experiences through three key pillars. 1. Engagement: World-class CDP capabilities seamlessly integrated with omnichannel marketing automation delivers experiences so personalized, they feel like magic. 2. Discovery: Product and content search, merchandising, SEO, and recommendations in one place, backed by an AI engine built with more than a decade of data. 3. Content: A headless CMS with the APIs and flexibility to power any front end while retaining powerful personalization and authoring capabilities. We want to help you to make full use of our tools so that you're set up for winning from day zero. We Care About Your Success - Creating cutting edge 1:1 digital experiences is complex. You now have the right tools; the next step is to ensure your organization is aligned to get full use of them. Bloomreach’s Professional Services team brings you advice from our product experts and best practices from across our customers to ensure you get the most out of your investment.

Semantee, a managed database that is easy to configure and optimized for semantic searches, is hassle-free. It is available as a set REST APIs that can be easily integrated into any application in minutes. It offers multilingual semantic searching for applications of any size, both on-premise and in the cloud. The product is significantly cheaper and more transparent than most providers, and is optimized for large-scale applications. Semantee also offers an abstraction layer over an e-shop's product catalog, enabling the store to utilize semantic search instantly without having to re-configure its database.

Sinequa is an intelligent enterprise search that connects workers in the digital workplace to the information, expertise, and insights they require to do their jobs. It can handle large and complex data volumes and ensure compliance in even the most challenging environments. Employees can access relevant information and insights to increase innovation and customer responsiveness. Intelligent search empowers people to do their jobs more effectively, which results in significant cost savings. Employees can get insights from their work context to help them comply with regulations quickly and reduce financial and reputational risk. Sinequa’s Neural Search provides the most sophisticated engine for discovering enterprise information assets available on the market today. By combining state-of-the-art deep learning language models with the best NLP and statistical techniques, employees and customers spend less time searching for information and more time developing insights to drive decisions and solutions.

*GraphDB allows the creation of large knowledge graphs by linking diverse data and indexing it for semantic search. * GraphDB is a robust and efficient graph database that supports RDF and SPARQL. The GraphDB database supports a highly accessible replication cluster. This has been demonstrated in a variety of enterprise use cases that required resilience for data loading and query answering. Visit the GraphDB product page for a quick overview and a link to download the latest releases. GraphDB uses RDF4J to store and query data. It also supports a wide range of query languages (e.g. SPARQL and SeRQL), and RDF syntaxes such as RDF/XML and Turtle.

Dgraph is an open-source, low-latency, high throughput native and distributed graph database. DGraph is designed to scale easily to meet the needs for small startups and large companies with huge amounts of data. It can handle terabytes structured data on commodity hardware with low latency to respond to user queries. It addresses business needs and can be used in cases that involve diverse social and knowledge networks, real-time recommendation engines and semantic search, pattern matching, fraud detection, serving relationship information, and serving web applications.

ChatGPT retrieval plug-in on steroids Intelligent document indexing services for smarter answers. For accurate ChatGPT responses, it is important to have text segments that respect the original document's context. OpenAI's text chunking services currently split the text only based on punctuation every 200 words. Pigro offers AI-based text chuncking services that divide content as a human would. They take into account the layout and structure of a document, including pagination, headings tables, lists, images etc. Our API supports Office-like documents in PDF, HTML and plain text. Pigro only delivers the relevant text to answer the query. Our generative AI expands your content by generating all possible questions within your document. Our search considers title, body and generated questions, as well as keywords and semantics. Generative indexing provides the best accuracy.

Our AI technology will handle the rest. Copy and paste your queries or type directly into our search box. Accurate search results increase efficiency by 50-80%. JAQI®, a product description translator, makes life easier for buyers by converting their descriptions into searchable terms. Your ecommerce clients or sales reps do not need to "match" your catalog. Our search technology supports industrial material with flexible customization options. Bye-bye to the inefficient dropdown menus and filters that require you to search one line item at a given time. Search 10, 20, or 100+ line items at once and add them to your quote within seconds. JAQI API plug in easily integrates with ecommerce applications, such as websites and ERP systems, to provide fast and accurate results for your customers. Our technology makes it easier and faster than ever to find any product from any catalog, in any format. JAQI powers AI search technology for your ecommerce site or ERP.

Elastic is a search company. Elasticsearch, Kibana Beats, Logstash, and Elasticsearch are the founders of the ElasticStack. These SaaS offerings allow data to be used in real-time and at scale for analytics, security, search, logging, security, and search. Elastic has over 100,000 members in 45 countries. Elastic's products have been downloaded more than 400 million times since their initial release. Today, thousands of organizations including Cisco, eBay and Dell, Goldman Sachs and Groupon, HP and Microsoft, as well as Netflix, Uber, Verizon and Yelp use Elastic Stack and Elastic Cloud to power mission critical systems that generate new revenue opportunities and huge cost savings. Elastic is headquartered in Amsterdam, The Netherlands and Mountain View, California. It has more than 1,000 employees in over 35 countries.

Businesses and developers can now create cutting-edge neural searches, generative AI and multimodal services using state of the art LMOps, LLOps, and cloud-native technology. Multimodal data is everywhere. From tweets to short videos on TikTok to audio snippets, Zoom meeting records, PDFs containing figures, 3D meshes and photos in games, there's no shortage of it. It is powerful and rich, but it often hides behind incompatible data formats and modalities. High-level AI applications require that one solve search first and create second. Neural Search uses AI for finding what you need. A description of a sunrise may match a photograph, or a photo showing a rose can match the lyrics to a song. Generative AI/Creative AI use AI to create what you need. It can create images from a description or write poems from a photograph.

One tool allows you to operationalize your embeddings. A comprehensive database that provides embedding functionality previously unavailable on multiple platforms is now available to you. Embeddinghub makes it easy to accelerate your machine learning. Embeddings are dense numerical representations of real world objects and relationships. They can be expressed as vectors. They are often created by first defining an unsupervised machine learning problem, also known as a "surrogate issue". Embeddings are intended to capture the semantics from the inputs they were derived. They can then be shared and reused for better learning across machine learning models. This is possible with Embeddinghub in an intuitive and streamlined way.

Weaviate is an open source vector database. It allows you to store vector embeddings and data objects from your favorite ML models, and scale seamlessly into billions upon billions of data objects. You can index billions upon billions of data objects, whether you use the vectorization module or your own vectors. Combining multiple search methods, such as vector search and keyword-based search, can create state-of-the art search experiences. To improve your search results, pipe them through LLM models such as GPT-3 to create next generation search experiences. Weaviate's next generation vector database can be used to power many innovative apps. You can perform a lightning-fast, pure vector similarity search on raw vectors and data objects. Combining keyword-based and vector search techniques will yield state-of the-art results. You can combine any generative model with your data to do Q&A, for example, over your dataset.

Carbon is a cost-effective alternative to expensive pipelines. You only pay monthly for usage. Utilise less and spend less with our usage-based pricing; use more and save more. Use our ready-made components for file uploading, web scraping, and 3rd party verification. A rich library of APIs designed for developers that import AI-focused data. Create and retrieve chunks, embeddings and data from all sources. Unstructured data can be searched using enterprise-grade keyword and semantic search. Carbon manages OAuth flows from 10+ sources. It transforms source data to vector store-optimized files and handles data synchronization automatically.

Build your RAG system intuitively with fewer abstractions than solutions like LangChain. You can choose from a variety of hosted and remote providers, including vector databases, datasets and Large Language Models. SciPhi allows you to version control and deploy your system from anywhere using Git. SciPhi's platform is used to manage and deploy an embedded semantic search engine that has over 1 billion passages. The team at SciPhi can help you embed and index your initial dataset into a vector database. The vector database will be integrated into your SciPhi workspace along with your chosen LLM provider.

Arches AI offers tools to create chatbots, train custom model, and generate AI-based content, all tailored to meet your specific needs. Deploy stable diffusion models, LLMs and more. A large language model agent (LLM) is a type artificial intelligence that uses deep-learning techniques and large data sets in order to understand, summarize and predict new content. Arches AI converts your documents into 'word embeddings.' These embeddings let you search by semantic meaning rather than by exact language. This is extremely useful when trying understand unstructured text information such as textbooks or documentation. Your information is protected from hackers and other bad characters by the strict security rules. You can delete all documents on the 'Files page'.

In recent years, the ability to convert text into pictures using artificial intelligence has attracted significant attention. Stable diffusion, which uses deep neural networks and their power to generate images from textual description, is an effective way to achieve this task. The first step is converting the textual description into a numerical format a neural networks can process. Text embedding, a popular technique, converts each word of the text into vector representation. After encoding the text, a deep-learning network creates an initial image using the encoded text. This image is noisy and lacks details, but it is a good starting point for the following step. The image is refined several times to improve its quality. Diffusion steps smooth and remove noise while preserving important details such as edges and contours.

Lilac is a free open-source tool that allows data and AI practitioners improve their products through better data. Understanding your data is easy with powerful filtering and search. Work together with your team to create a single dataset. Use best practices for data curation to reduce the size of your dataset and training costs and time. Our diff viewer allows you to see how your pipeline affects your data. Clustering is an automatic technique that assigns categories to documents by analyzing their text content. Similar documents are then placed in the same category. This reveals your dataset's overall structure. Lilac uses LLMs and state-of-the art algorithms to cluster the data and assign descriptive, informative titles. We can use keyword search before we do advanced searches, such as concept or semantic searching.

Your team can develop AI applications using models such as GPT-4, and operate them visually. You can deploy your application within 5 minutes, whether it is for internal team use or an external release. Using documents/webpages/Notion content as the context for AI, automatically complete text preprocessing, vectorization and segmentation. No need to learn embedding methods anymore. This will save you weeks of development. Dify offers a smooth user experience for model access and context embedding. It also provides cost control, data annotation, and cost control. You can easily create AI apps for internal team use, or product development. Start with a prompt but go beyond its limitations. Dify offers rich functionality in many scenarios.

No one wants to have their AI respond to a client with outdated information. Neum AI provides accurate and current context for AI applications. Set up your data pipelines quickly by using built-in connectors. These include data sources such as Amazon S3 and Azure Blob Storage and vector stores such as Pinecone and Weaviate. Transform and embed your data using built-in connectors to embed models like OpenAI, Replicate and serverless functions such as Azure Functions and AWS Lambda. Use role-based controls to ensure that only the right people have access to specific vectors. Bring your own embedding model, vector stores, and sources. Ask us how you can run Neum AI on your own cloud.

Store the embeddings from previous attacks in a database of vectors to recognize and prevent them in the future. Use a dedicated LLM for analyzing incoming prompts to identify potential attacks. Add canary tokens in prompts to detect leakages. This allows the framework to store embedded embeddings of the incoming prompt into the vector database to prevent future attacks. Filter out malicious input before it reaches LLM.

You can instantly generate documents from your SharePoint library or list. Instant presentations, proposals, and reports - with no errors. Export SharePoint views, selected items, or entire lists easily into Word reports. You can customize the Word reports to include specific metadata, charts and images. You can update content without opening any documents. No more manual filling, copy-pasting or tedious routine tasks. Mail merge business letters, labels and custom proposals, contracts, worksheets, and more easily. You can create a document from multiple items or merge multiple documents into one. You can break up frequently used content into smaller parts and then combine them into documents using check boxes. In seconds, create custom Word documents and PowerPoint presentations.

Solar's Chat API allows you to create a simple agent that can have a conversation. Function Calling, the method of connecting LLM with external tools, is now supported. The embedding vectors are useful for retrieval and classification. Context-aware English to Korean translation that uses previous dialogues for unmatched coherence in your conversations. Verifies that the LLM's generated answers are appropriate based on the question asked by the user and the search results. A healthcare LLM is being developed to automate patient communications, personalize treatment plans and aid in clinical decision-support. It will also support medical transcription. The goal is to make it easy for business owners and companies, to deploy generative AI bots on mobile apps and websites. This will provide human-like customer support.

Data can disrupt markets and open new frontiers, but it only works when it is trusted and understood. Stakeholders in your organization can collaborate to achieve data excellence by leveraging our AI/ML-enhanced cloud-based solution, which is built with 25 years worth of best practices. With hundreds of pre-built reports and embedded best practices, you can quickly identify and remediate data quality issues. Cleanse data before or during data migration. Track data quality in real time with customizable data intelligence dashboards. Monitor data objects continuously and automatically initiate remediation workflows to direct them to the correct data owners. To accelerate future data initiatives, consolidate data on a single cloud-based platform. All data stakeholders working together in one system will reduce effort and improve results.

We've been working on Generative AI for 5 years. Deep Lake combines the power and flexibility of vector databases and data lakes to create enterprise-grade LLM-based solutions and refine them over time. Vector search does NOT resolve retrieval. You need a serverless search for multi-modal data including embeddings and metadata to solve this problem. You can filter, search, and more using the cloud, or your laptop. Visualize your data and embeddings to better understand them. Track and compare versions to improve your data and your model. OpenAI APIs are not the foundation of competitive businesses. Your data can be used to fine-tune LLMs. As models are being trained, data can be efficiently streamed from remote storage to GPUs. Deep Lake datasets can be visualized in your browser or Jupyter Notebook. Instantly retrieve different versions and materialize new datasets on the fly via queries. Stream them to PyTorch, TensorFlow, or Jupyter Notebook.