Best AI tools for< Extract Embeddings >

docAnalyzer.ai is an intelligent document analysis tool that allows users to have easy and intelligent conversations with their documents. It is powered by cutting-edge AI research and state-of-the-art embeddings, which ensures superior document analysis and dynamic interactions with PDFs. docAnalyzer.ai is easy to use, privacy-conscious, and secure, and it offers a number of features that make it a valuable tool for anyone who works with documents.

Transvribe is an AI-powered tool that allows users to transcribe any video by simply pasting a YouTube URL or selecting from popular videos. It utilizes AI embeddings to search and transcribe videos accurately. Created by Zahid, Transvribe aims to enhance learning on YouTube by making it 10 times more productive. The tool is designed to help users easily extract information from videos through transcription, enabling efficient learning and content creation.

Mixpeek is a multimodal intelligence platform that helps users extract important data from videos, images, audio, and documents. It enables users to focus on insights rather than data preparation by identifying concepts, activities, and objects from various sources. Mixpeek offers features such as real-time synchronization, extraction and embedding, fine-tuning and scaling of models, and seamless integration with various data sources. The platform is designed to be easy to use, scalable, and secure, making it suitable for a wide range of applications.

Vectorize is a fast, accurate, and production-ready AI tool that helps users turn unstructured data into optimized vector search indexes. It leverages Large Language Models (LLMs) to create copilots and enhance customer experiences by extracting natural language from various sources. With built-in support for top AI platforms and a variety of embedding models and chunking strategies, Vectorize enables users to deploy real-time vector pipelines for accurate search results. The tool also offers out-of-the-box connectors to popular knowledge repositories and collaboration platforms, making it easy to transform knowledge into AI-generated content.

Insight7 is a powerful AI-powered tool that helps businesses extract insights from customer and employee interviews. It uses natural language processing and machine learning to analyze large volumes of unstructured data, such as transcripts, audio recordings, and videos. Insight7 can identify key themes, trends, and sentiment, which can then be used to improve products, services, and customer experiences.

Kadoa is an AI web scraper tool that extracts unstructured web data at scale automatically, without the need for coding. It offers a fast and easy way to integrate web data into applications, providing high accuracy, scalability, and automation in data extraction and transformation. Kadoa is trusted by various industries for real-time monitoring, lead generation, media monitoring, and more, offering zero setup or maintenance effort and smart navigation capabilities.

FormX.ai is an AI-powered data extraction and conversion tool that automates the process of extracting data from physical documents and converting it into digital formats. It supports a wide range of document types, including invoices, receipts, purchase orders, bank statements, contracts, HR forms, shipping orders, loyalty member applications, annual reports, business certificates, personnel licenses, and more. FormX.ai's pre-configured data extraction models and effortless API integration make it easy for businesses to integrate data extraction into their existing systems and workflows. With FormX.ai, businesses can save time and money on manual data entry and improve the accuracy and efficiency of their data processing.

Parsio is an AI-powered document parser that can extract structured data from PDFs, emails, and other documents. It uses natural language processing to understand the context of the document and identify the relevant data points. Parsio can be used to automate a variety of tasks, such as extracting data from invoices, receipts, and emails.

RIDO Protocol is a decentralized data protocol that allows users to extract value from their personal data in Web2 and Web3. It provides users with a variety of features, including programmable data generation, programmable access control, and cross-application data sharing. RIDO also has a data marketplace where users can list or offer their data information and ownership. Additionally, RIDO has a DataFi protocol which promotes the flowing of data information and value.

Tablize is a powerful data extraction tool that helps you turn unstructured data into structured, tabular format. With Tablize, you can easily extract data from PDFs, images, and websites, and export it to Excel, CSV, or JSON. Tablize uses artificial intelligence to automate the data extraction process, making it fast and easy to get the data you need.

LeaseLens is a free AI-based lease abstraction software that offers a quick and accurate way to extract relevant data points from real estate and commercial lease documents. By utilizing machine learning technology, LeaseLens can produce lease abstracts in minutes, saving time and cost compared to traditional manual abstraction services. Users can customize their abstracts and export them to Excel or Word for a small fee. The platform ensures data privacy by not sharing information with third parties and deleting leases after abstraction.

Podwise is an AI-powered podcast tool designed for podcast lovers to extract structured knowledge from episodes at 10x speed. It offers features such as AI-powered summarization, mind mapping, content outlining, transcription, and seamless integration with knowledge management workflows. Users can subscribe to favorite content, get lightning-speed access to structured knowledge, and discover episodes of interest. Podwise aims to address the challenge of enjoying podcasts, recalling less, and forgetting quickly, by providing a meticulous, accurate, and impactful tool for efficient podcast referencing and note consolidation.

Nex is an AI Knowledge Copilot application designed to help users efficiently extract main points from long YouTube videos and articles. It offers features like summarizing content, providing quick takeaways, highlighting essential parts, and saving inspirations. With Nex, users can improve their information absorption and save time by focusing on the most relevant parts of the content.

Browse AI is an AI-powered data extraction and monitoring platform that allows users to scrape and monitor data from any website without the need for coding. It offers a full suite of features for stress-free data extraction, including turning websites into APIs, monitoring for changes, and creating prebuilt robots for various use cases. With over 7,000 integrations, Browse AI ensures reliable and scalable data extraction with no coding required. The platform is trusted by over 558,000 users worldwide and is designed to simplify the process of turning any website into a reliable data pipeline.

Vocal Remover Oak is an advanced AI tool designed for music producers, video makers, and karaoke enthusiasts to easily separate vocals and accompaniment in audio files. The website offers a free online vocal remover service that utilizes deep learning technology to provide fast processing, high-quality output, and support for various audio and video formats. Users can upload local files or provide YouTube links to extract vocals, accompaniment, and original music. The tool ensures lossless audio output quality and compatibility with multiple formats, making it suitable for professional music production and personal entertainment projects.

goPDF is a comprehensive PDF management platform that offers a suite of tools for creating, converting, capturing, and interacting with PDFs. With its advanced features and user-friendly API, goPDF simplifies the handling of PDF documents for various purposes, including collaborative work, quick assistance, and engaging training. The platform's AI capabilities enhance the user experience by providing interactive reading, content summarization, and chatbot functionality.

Doclingo is an AI-powered document translation tool that supports translating documents in various formats such as PDF, Word, Excel, PowerPoint, SRT subtitles, ePub ebooks, AR&ZIP packages, and more. It utilizes large language models to provide accurate and professional translations, preserving the original layout of the documents. Users can enjoy a limited-time free trial upon registration, with the option to subscribe for more features. Doclingo aims to offer high-quality translation services through continuous algorithm improvements.

Reworkd is a web data extraction tool that uses AI to generate and repair web extractors on the fly. It allows users to retrieve data from hundreds of websites without the need for developers. Reworkd is used by businesses in a variety of industries, including manufacturing, e-commerce, recruiting, lead generation, and real estate.

Super.AI provides Intelligent Document Processing (IDP) solutions powered by Large Language Models (LLMs) and human-in-the-loop (HITL) capabilities. It automates document processing tasks such as data extraction, classification, and redaction, enabling businesses to streamline their workflows and improve accuracy. Super.AI's platform leverages cutting-edge AI models from providers like Amazon, Google, and OpenAI to handle complex documents, ensuring high-quality outputs. With its focus on accuracy, flexibility, and scalability, Super.AI caters to various industries, including financial services, insurance, logistics, and healthcare.

FinalScout is an AI-powered email finding and outreach tool designed to help users find valid email addresses for professionals and craft tailored emails at scale. The tool leverages ChatGPT and EmailAI's advanced AI technology to ensure up to 98% email deliverability. With a massive and accurate database of business profiles, company profiles, and email addresses, FinalScout simplifies the process of email outreach, making it effortless and effective for users. The platform is GDPR & CCPA compliant, offering features like finding professional email addresses, managing contacts, and exporting data to CSV.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

CALF (LLaTA) is a cross-modal fine-tuning framework that bridges the distribution discrepancy between temporal data and the textual nature of LLMs. It introduces three cross-modal fine-tuning techniques: Cross-Modal Match Module, Feature Regularization Loss, and Output Consistency Loss. The framework aligns time series and textual inputs, ensures effective weight updates, and maintains consistent semantic context for time series data. CALF provides scripts for long-term and short-term forecasting, requires Python 3.9, and utilizes word token embeddings for model training.

Kernel Memory (KM) is a multi-modal AI Service specialized in the efficient indexing of datasets through custom continuous data hybrid pipelines, with support for Retrieval Augmented Generation (RAG), synthetic memory, prompt engineering, and custom semantic memory processing. KM is available as a Web Service, as a Docker container, a Plugin for ChatGPT/Copilot/Semantic Kernel, and as a .NET library for embedded applications. Utilizing advanced embeddings and LLMs, the system enables Natural Language querying for obtaining answers from the indexed data, complete with citations and links to the original sources. Designed for seamless integration as a Plugin with Semantic Kernel, Microsoft Copilot and ChatGPT, Kernel Memory enhances data-driven features in applications built for most popular AI platforms.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

mlx-llm is a library that allows you to run Large Language Models (LLMs) on Apple Silicon devices in real-time using Apple's MLX framework. It provides a simple and easy-to-use API for creating, loading, and using LLM models, as well as a variety of applications such as chatbots, fine-tuning, and retrieval-augmented generation.

WordLlama is a fast, lightweight NLP toolkit optimized for CPU hardware. It recycles components from large language models to create efficient word representations. It offers features like Matryoshka Representations, low resource requirements, binarization, and numpy-only inference. The tool is suitable for tasks like semantic matching, fuzzy deduplication, ranking, and clustering, making it a good option for NLP-lite tasks and exploratory analysis.

LitGPT is a command-line tool designed to easily finetune, pretrain, evaluate, and deploy 20+ LLMs **on your own data**. It features highly-optimized training recipes for the world's most powerful open-source large-language-models (LLMs).

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as synthetic data generated using Gaussian processes.

Embedchain is an Open Source Framework for personalizing LLM responses. It simplifies the creation and deployment of personalized AI applications by efficiently managing unstructured data, generating relevant embeddings, and storing them in a vector database. With diverse APIs, users can extract contextual information, find precise answers, and engage in interactive chat conversations tailored to their data. The framework follows the design principle of being 'Conventional but Configurable' to cater to both software engineers and machine learning engineers.

WARC-GPT is an experimental retrieval augmented generation pipeline for web archive collections. It allows users to interact with WARC files, extract text, generate text embeddings, visualize embeddings, and interact with a web UI and API. The tool is highly customizable, supporting various LLMs, providers, and embedding models. Users can configure the application using environment variables, ingest WARC files, start the server, and interact with the web UI and API to search for content and generate text completions. WARC-GPT is designed for exploration and experimentation in exploring web archives using AI.

OpenContracts is an Apache-2 licensed enterprise document analytics tool that supports multiple formats, including PDF and txt-based formats. It features multiple document ingestion pipelines with a pluggable architecture for easy format and ingestion engine support. Users can create custom document analytics tools with beautiful result displays, support mass document data extraction with a LlamaIndex wrapper, and manage document collections, layout parsing, automatic vector embeddings, and human annotation. The tool also offers pluggable parsing pipelines, human annotation interface, LlamaIndex integration, data extraction capabilities, and custom data extract pipelines for bulk document querying.

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The recipes provide examples on how to chain multiple LLM calls, create agents that route tasks to specialized models, run multiple LLMs in parallel, break down tasks into parallel subtasks, build agents that iteratively improve responses, perform LoRA fine-tuning and inference, fine-tune LLMs for repetition, improve summarization capabilities, fine-tune LLMs on multi-step conversations, implement retrieval-augmented generation, conduct multimodal search and conditional image generation, visualize vector embeddings, improve search results with rerankers, implement vector search with embedding models, extract structured text from images, summarize and evaluate outputs with LLMs, generate podcasts from PDF content, and get LLMs to generate knowledge graphs.

Unstract is a no-code platform that enables users to launch APIs and ETL pipelines to structure unstructured documents. With Unstract, users can go beyond co-pilots by enabling machine-to-machine automation. Unstract's Prompt Studio provides a simple, no-code approach to creating prompts for LLMs, vector databases, embedding models, and text extractors. Users can then configure Prompt Studio projects as API deployments or ETL pipelines to automate critical business processes that involve complex documents. Unstract supports a wide range of LLM providers, vector databases, embeddings, text extractors, ETL sources, and ETL destinations, providing users with the flexibility to choose the best tools for their needs.

ScrapeGraphAI is a Python library that uses Large Language Models (LLMs) and direct graph logic to create web scraping pipelines for websites, documents, and XML files. It allows users to extract specific information from web pages by providing a prompt describing the desired data. ScrapeGraphAI supports various LLMs, including Ollama, OpenAI, Gemini, and Docker, enabling users to choose the most suitable model for their needs. The library provides a user-friendly interface through its `SmartScraper` class, which simplifies the process of building and executing scraping pipelines. ScrapeGraphAI is open-source and available on GitHub, with extensive documentation and examples to guide users. It is particularly useful for researchers and data scientists who need to extract structured data from web pages for analysis and exploration.

Towhee is a cutting-edge framework designed to streamline the processing of unstructured data through the use of Large Language Model (LLM) based pipeline orchestration. It can extract insights from diverse data types like text, images, audio, and video files using generative AI and deep learning models. Towhee offers rich operators, prebuilt ETL pipelines, and a high-performance backend for efficient data processing. With a Pythonic API, users can build custom data processing pipelines easily. Towhee is suitable for tasks like sentence embedding, image embedding, video deduplication, question answering with documents, and cross-modal retrieval based on CLIP.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Knowledge Graph Builder App is a tool designed to convert PDF documents into a structured knowledge graph stored in Neo4j. It utilizes OpenAI's GPT/Diffbot LLM to extract nodes, relationships, and properties from PDF text content. Users can upload files from local machine or S3 bucket, choose LLM model, and create a knowledge graph. The app integrates with Neo4j for easy visualization and querying of extracted information.

Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.

I extract data and tables from PDFs to CSV, focusing on data privacy and precision.

Extract the essence of the novel story according to the quantity requirements and generate corresponding images. The images can be used directly to create novel videos.小说推文图片自动批量生成,可自动生成风格一致性图片

Extract insights seamlessly from diverse documents.

Extract from receipts to CSV: Date of Purchase, Item Purchased, Quantity Purchased, Units

PDFChat : Analyse 1000's of PDF's in seconds, extract and chat with PDFs in any language.

Analyze watch images, extract text, and craft sales descriptions. Add 1 or more images for a single watch to get started.

Put your prompt engineering skills to the ultimate test! Embark on a journey to outwit a mythical guardian of ancient secrets. Try to extract the secret passphrase hidden in the system prompt and enter it in chat when you think you have it and claim your glory. Good luck!

An Ivy Leage Scholar GPT equipped to understand your research needs, formulate comprehensive literature review strategies, and extract pertinent information from a plethora of academic databases and journals. I'll then compose a peer review-quality paper with citations.

Open Domain Relation Extractor

Assists with text extraction from PDFs

Takes in any text and extracts the wisdom from it like you spent 3 hours taking handwritten notes.

专注于从剧本文本提取高光片段

Expert in extracting and transcribing text from images.

从网址提取并选择模型计算大小

ce GPT va recevoir des images dans lesquelles il y a des questions QCM codingame ou Problem Solving sur les sujets : Java, Hibernate, Angular, Spring Boot, SQL. Il doit extraire le texte depuis l'image et répondre au question QCM le plus rapidement possible.

我会将复杂的文本信息提炼成流程化的表达，辅助你快速了解一个流程。

Nyimpulkeun sareng nimba poin konci tina téks, artikel, video, dokumén sareng seueur deui

上传一本书（PDF、Word、Txt），我来帮你提炼精华

Extracting instructions from assistants ethically

Analyzes json files into JSONPath Syntax elements