Best AI tools for< Handle Documents >

Further AI is an AI application designed to revolutionize insurance operations by providing AI Teammates for various tasks such as quote generation, policy checking, and renewal follow-ups. The platform aims to enhance efficiency, reduce errors, and automate repetitive tasks in the insurance industry. Further AI offers innovative solutions for insurance brokers, general agents, and insurers, allowing them to scale their business without the need for additional hiring. By leveraging AI technology, users can streamline workflows, automate client calls, navigate portals, and extract data from complex documents with ease and accuracy.

Doc2Lang is an AI-powered document translation service that offers fast and accurate translations for various file formats including Excel, Word, PowerPoint, and PDF. Users can upload their files, have them automatically translated by the AI, and then download the translated documents. The service provides high-quality translations tailored to business needs and ensures security by allowing users to delete uploaded files for data removal. With a simple and convenient process, flexible billing options, and support for multiple languages, Doc2Lang is a reliable solution for document translation needs.

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.

Legaliser is an AI-powered contract management tool that offers comprehensive contract analysis, intuitive drafting tools, and customizable legal templates. It leverages advanced AI technology and legal expertise to streamline legal workflows, enhance compliance, and revolutionize how businesses handle legal documents.

Collato is an AI assistant designed to help product teams save time on writing documents, answering questions, and generating new content. It can find, summarize, and generate new content based on your own product knowledge, saving you hours in manual work. Collato is also self-hosted, so you can keep your data private and secure.

Tipis AI is an AI assistant for data processing that uses Large Language Models (LLMs) to quickly read and analyze mainstream documents with enhanced precision. It can also generate charts, integrate with a wide range of mainstream databases and data sources, and facilitate seamless collaboration with other team members. Tipis AI is easy to use and requires no configuration.

Ticket AI is a Discord bot that automates customer support by answering tickets with AI. It simplifies support by allowing users to upload training data, such as support documents, and then using that data to answer customer questions. Ticket AI is easy to use, with no coding experience required, and it offers features such as custom support channels, ephemeral replies, and 24/7 availability. With Ticket AI, businesses can save time and improve the efficiency of their customer support.

BotX is a No-Code AI Platform that enables users to automate and deploy generative AI workflows, chatbots, and solutions. It offers production-ready AI systems to increase productivity, build AI agents and chatbots, automate workflows, create or process documents, and connect models effortlessly. With a focus on efficiency and reliability, BotX aims to simplify AI implementation for businesses of all sizes.

AmyGB Platform Services offers Gen AI-powered Document Processing and API Services to supercharge productivity for businesses. Their trendsetting digital products have revolutionized how organizations handle data and streamline workflows, enabling businesses to easily optimize operations 24x7, enhance data accuracy, and improve customer satisfaction. The platform empowers business operations by driving automation revolution, providing 8x productivity, 70% cost efficiency, 80% higher accuracy, and 95% automation. AmyGB's AI-powered document processing solutions help convert documents into digital assets, extract data, and enhance customer fulfillment through automated software solutions.

Wordsmith is an AI-powered legal operations platform designed for in-house legal teams to streamline workflows, process documents, and handle routine legal tasks efficiently. The platform offers features such as compliance workflows, policy and knowledge sharing, triage and routing, advanced contract and document analysis, and AI consultancy services. Wordsmith aims to make legal operations accessible and efficient for businesses by leveraging artificial intelligence technology.

Remove Handwriting is a free online tool that uses artificial intelligence to remove handwriting from images and PDFs. It can handle a variety of complex document image issues, including curling, shadows, wrinkles, stains, finger obstructions, text showing through from the back, and moiré patterns. It can also detect the overall shape of documents, accurately locate areas, and intelligently correct various distortions caused by warping and creasing. Remove Handwriting is easy to use. Simply upload an image or PDF, and the AI will automatically remove the handwriting. Within a few seconds, you will receive an image or PDF without any handwriting.

Hebbia is an AI tool designed to help users collaborate with AI agents more confidently over all the documents that matter. It offers Matrix agents that can handle questions about millions of documents at a time, executing workflows with hundreds of steps. Hebbia is known for its Trustworthy AI approach, showing its work at each step to build user trust. The tool is used by top enterprises, financial institutions, governments, and law firms worldwide, saving users time and making them more efficient in their work.

Casca is a next-generation loan origination system that enables banks, credit unions, and non-bank lenders to originate commercial loans with significantly less manual effort. With features like AI loan assistant, automated tasks, and digital approvals, Casca aims to revolutionize the small business lending process. The platform helps in improving lead quality, increasing conversion rates, saving time for loan officers, and streamlining the loan origination process. Casca leverages AI technology to provide a modern user experience and personalized follow-ups, making the loan application process more efficient and magical.

Callin.io is an innovative AI solution that offers AI-driven virtual phone agents and assistants to enhance customer engagement and support. The platform provides customizable AI voice agents tailored to meet the specific needs of businesses, handling inbound and outbound customer conversations efficiently. With features like answering missed calls, assisting with appointment bookings, and responding to FAQs, Callin.io aims to revolutionize customer service operations and improve overall customer experience. The AI technology is designed to seamlessly integrate with existing CRM solutions and call center technology, providing real-time call transcripts and valuable insights from every conversation.

Kimiya is an AI Conversational Digital Human application designed to provide better customer support through a generative AI conversational assistant. It offers features such as selecting diverse avatars, 24/7 support, real-time analytics, interactive communication with users, and personalized recommendations for E-Commerce, Hotel, and Museum industries. Kimiya is adaptable to diverse organizational needs and aims to enhance customer experiences through AI-powered assistance.

Mirai Translator is an AI-powered automatic translation service that provides high-security and high-accuracy translations. It is used by many global organizations to overcome language barriers and expand their global reach. Mirai Translator's AI technology ensures that translations are accurate and fluent, and it can handle a variety of languages and document types. The service is easy to use and can be integrated with a variety of applications and workflows.

AnythingLLM is an all-in-one AI application designed for everyone. It offers a comprehensive suite of tools for working with LLMs (Large Language Models), documents, and agents in a fully private manner. Users can download AnythingLLM for Desktop on Windows, MacOS, and Linux, enabling flexible one-click installation. The application supports custom model integration, including closed-source models like GPT-4 and custom fine-tuned models like Llama2. With the ability to handle various document formats beyond PDFs, AnythingLLM provides tailored solutions with locally running defaults for privacy. Additionally, users can access AnythingLLM Cloud for extended functionalities.

Noem.AI is an AI platform that offers autonomous AI agents to assist with a wide range of tasks, from content creation to project management. Users can hire specialized AI agents, called noems, to handle specific tasks autonomously. The platform operates on a pay-as-you-go model using tokens, allowing users to purchase tokens to pay for tasks performed by the AI agents. Noem.AI aims to simplify complex processes, enhance productivity, and streamline business operations.

PDFMerse is an AI-powered data extraction tool that revolutionizes how users handle document data. It allows users to effortlessly extract information from PDFs with precision, saving time and enhancing workflow. With cutting-edge AI technology, PDFMerse automates data extraction, ensures data accuracy, and offers versatile output formats like CSV, JSON, and Excel. The tool is designed to dramatically reduce processing time and operational costs, enabling users to focus on higher-value tasks.

AI-Responder for HostAway is an AI-powered Chrome extension that significantly reduces writing time by providing automated responses based on property-specific knowledge documents, guest data, and previous chat history. The tool utilizes advanced AI models like OpenAI GPT-4o and GPT NeoX 20B to generate high-quality responses that mimic human-like interactions. With a focus on enhancing guest communication and streamlining response processes, AI-Responder for HostAway aims to revolutionize customer service in the hospitality industry.

Open Parse is a Python library for visually discerning document layouts and chunking them effectively. It is designed to fill the gap in open-source libraries for handling complex documents. Unlike text splitting, which converts a file to raw text and slices it up, Open Parse visually analyzes documents for superior LLM input. It also supports basic markdown for parsing headings, bold, and italics, and has high-precision table support, extracting tables into clean Markdown formats with accuracy that surpasses traditional tools. Open Parse is extensible, allowing users to easily implement their own post-processing steps. It is also intuitive, with great editor support and completion everywhere, making it easy to use and learn.

MegaParse is a powerful and versatile parser designed to handle various types of documents such as text, PDFs, Powerpoint presentations, and Word documents with no information loss. It is fast, efficient, and open source, supporting a wide range of file formats. MegaParse ensures compatibility with tables, table of contents, headers, footers, and images, making it a comprehensive solution for document parsing.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

LLoCO is a technique that learns documents offline through context compression and in-domain parameter-efficient finetuning using LoRA, which enables LLMs to handle long context efficiently.

ExtractThinker is a library designed for extracting data from files and documents using Language Model Models (LLMs). It offers ORM-style interaction between files and LLMs, supporting multiple document loaders such as Tesseract OCR, Azure Form Recognizer, AWS TextExtract, and Google Document AI. Users can customize extraction using contract definitions, process documents asynchronously, handle various document formats efficiently, and split and process documents. The project is inspired by the LangChain ecosystem and focuses on Intelligent Document Processing (IDP) using LLMs to achieve high accuracy in document extraction tasks.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

Redbox is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License. Security measures are in place to ensure user data privacy and considerations are being made to make the core-api secure.

Redbox Copilot is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License.

Chroma is an open-source embedding database that provides a simple, scalable, and feature-rich way to build Python or JavaScript LLM apps with memory. It offers a fully-typed, fully-tested, and fully-documented API that makes it easy to get started and scale your applications. Chroma also integrates with popular tools like LangChain and LlamaIndex, and supports a variety of embedding models, including Sentence Transformers, OpenAI embeddings, and Cohere embeddings. With Chroma, you can easily add documents to your database, query relevant documents with natural language, and compose documents into the context window of an LLM like GPT3 for additional summarization or analysis.

chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. It is developed under the MIT License and powers inference behind Gradient.ai. The API allows users to deploy models from SentenceTransformers, offers fast inference backends utilizing various accelerators, dynamic batching for efficient processing, correct and tested implementation, and easy-to-use API built on FastAPI with Swagger documentation. Users can embed text, rerank documents, and perform text classification tasks using the tool. Infinity supports various models from Huggingface and provides flexibility in deployment via CLI, Docker, Python API, and cloud services like dstack. The tool is suitable for tasks like embedding, reranking, and text classification.

The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of `unstructured` revolve around streamlining and optimizing the data processing workflow for LLMs. `unstructured` modular functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.

LlamaBot is a Pythonic bot interface to Large Language Models (LLMs), providing an easy way to experiment with LLMs in Jupyter notebooks and build Python apps utilizing LLMs. It supports all models available in LiteLLM. Users can access LLMs either through local models with Ollama or by using API providers like OpenAI and Mistral. LlamaBot offers different bot interfaces like SimpleBot, ChatBot, QueryBot, and ImageBot for various tasks such as rephrasing text, maintaining chat history, querying documents, and generating images. The tool also includes CLI demos showcasing its capabilities and supports contributions for new features and bug reports from the community.

Local Multimodal AI Chat is a hands-on project that teaches you how to build a multimodal chat application. It integrates different AI models to handle audio, images, and PDFs in a single chat interface. This project is perfect for anyone interested in AI and software development who wants to gain practical experience with these technologies.

OpsPilot is an AI-powered operations navigator developed by the WeOps team. It leverages deep learning and LLM technologies to make operations plans interactive and generalize and reason about local operations knowledge. OpsPilot can be integrated with web applications in the form of a chatbot and primarily provides the following capabilities: 1. Operations capability precipitation: By depositing operations knowledge, operations skills, and troubleshooting actions, when solving problems, it acts as a navigator and guides users to solve operations problems through dialogue. 2. Local knowledge Q&A: By indexing local knowledge and Internet knowledge and combining the capabilities of LLM, it answers users' various operations questions. 3. LLM chat: When the problem is beyond the scope of OpsPilot's ability to handle, it uses LLM's capabilities to solve various long-tail problems.

BlinkID iOS is a mobile SDK that enables developers to easily integrate ID scanning and data extraction capabilities into their iOS applications. The SDK supports scanning and processing various types of identity documents, such as passports, driver's licenses, and ID cards. It provides accurate and fast data extraction, including personal information and document details. With BlinkID iOS, developers can enhance their apps with secure and reliable ID verification functionality, improving user experience and streamlining identity verification processes.

qlora-pipe is a pipeline parallel training script designed for efficiently training large language models that cannot fit on one GPU. It supports QLoRA, LoRA, and full fine-tuning, with efficient model loading and the ability to load any dataset that Axolotl can handle. The script allows for raw text training, resuming training from a checkpoint, logging metrics to Tensorboard, specifying a separate evaluation dataset, training on multiple datasets simultaneously, and supports various models like Llama, Mistral, Mixtral, Qwen-1.5, and Cohere (Command R). It handles pipeline- and data-parallelism using Deepspeed, enabling users to set the number of GPUs, pipeline stages, and gradient accumulation steps for optimal utilization.

TableLLM is a large language model designed for efficient tabular data manipulation tasks in real office scenarios. It can generate code solutions or direct text answers for tasks like insert, delete, update, query, merge, and chart operations on tables embedded in spreadsheets or documents. The model has been fine-tuned based on CodeLlama-7B and 13B, offering two scales: TableLLM-7B and TableLLM-13B. Evaluation results show its performance on benchmarks like WikiSQL, Spider, and self-created table operation benchmark. Users can use TableLLM for code and text generation tasks on tabular data.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

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Welcome to AwkwardSituation Solver GPT! I am here to help you handle those cringe-worthy social moments with a touch of humor and creativity.

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This GPT is a specialized assistant for Flask, the popular web framework in Python. It is designed to help both beginners and experienced developers with Flask-related queries, ranging from basic setup and routing to advanced features like database integration and application scaling.