Best AI tools for< Process Handwritten Text >

GenIQ is an AI-powered application that allows users to interact with files through natural language. It generates concise summaries of lengthy documents using Generative AI technology. Users can work with various file types such as audio, video, PDF, and Word documents by asking questions in natural language and receiving real-time answers. GenIQ offers features like audio & video analysis, document processing, multilingual support, and handwritten document analysis.

PicNotes is a web-based image-to-text converter that can convert messy images into summaries, text, or explanations. It supports handwritten papers, medical reports, and other types of images. The tool is easy to use: simply upload an image and choose the desired output format. PicNotes will then process the image and return the results within seconds.

Graded Pro is an advanced AI grading tool designed for teachers and educators worldwide. It offers automated assessment and grading of various academic works, including handwritten submissions, art, coding assignments, essays, and diagrams. The platform supports a wide range of educational standards and curriculums, providing detailed feedback to students based on customizable rubrics. Graded Pro prioritizes security and privacy, complying with GDPR and FERPA regulations to safeguard student data. With features like effortless grading, support for all subjects and file types, and integration with Google Classroom, Graded Pro streamlines the grading process and enhances the teaching experience.

BidBuilder is an AI-powered proposal generator designed to simplify the process of creating high-quality Upwork proposals. With BidBuilder, freelancers can generate tailored proposals in just a few minutes, saving time and increasing their chances of winning projects. The tool uses advanced AI algorithms to analyze project titles and descriptions, generating customized proposals that match the client's requirements. BidBuilder is easy to use and does not require any technical expertise. Freelancers simply need to input their project details and skills, and BidBuilder will create a personalized proposal. The tool also allows users to edit and add personal touches to generated proposals for a unique, individualized result.

Process Street is an AI-powered platform that helps businesses streamline their processes and improve operational efficiency. It offers features such as workflows automation, data unification, document sharing, and AI transformation. With Process Street, users can create, track, and complete tasks efficiently, make data-driven decisions, and automate repetitive tasks using generative AI. The platform also provides analytics to track key performance indicators and ensure consistent adherence to procedures. Process Street is trusted by top companies to revolutionize workflow management and drive productivity and growth.

Process Street is a powerful checklist, workflow, and SOP software that is designed to streamline and automate business processes. It offers a wide range of features such as workflows, projects, data sets, forms, and pages to help organizations organize and manage their operations efficiently. With AI capabilities, Process Street can transform manual processes, boost productivity, and empower decision-making with analytics. The platform also provides integrations with various tools for maximum efficiency.

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.

Smace is an AI-powered SaaS platform designed to enhance process implementation efficiency. It offers features such as enhanced process collaboration, automated workflows and integration, streamlined task management, and data-driven decision support. Smace aims to bridge the gap between process design and execution, promoting team efficiency, streamlined collaboration, and advanced integration.

Greenhouse is an AI-powered applicant tracking software and hiring platform that offers smart hiring tools to streamline the hiring process. It provides features such as AI tools for sourcing, texting solutions, and feature upgrades to help connect teams and propel success. Greenhouse is designed to help companies hire fairly and purposefully, offering expertise and advice to maximize hiring ROI and support business growth at any stage.

Expertia AI is an AI-powered hiring partner that leverages advanced algorithms and machine learning to streamline the recruitment process. It offers a comprehensive suite of tools to assist HR professionals in sourcing, screening, and selecting top talent efficiently. By automating repetitive tasks and providing data-driven insights, Expertia AI helps companies make informed hiring decisions and improve overall recruitment outcomes.

Meshy is a free 3D AI model generator that empowers artists, game developers, and creators to bring their visions to life with a toolkit for creating 3D models in minutes. It offers powerful AI generation tools, lightning speed modeling, PBR maps, versatile art styles, and user-friendly interface. Meshy allows users to convert text to 3D, images to 3D models, and upload existing 3D models to transform words into textures. With multilingual support, API integration, and various export options, Meshy provides a seamless 3D workflow for users to unleash their creativity like never before.

HireQuotient is an end-to-end recruitment automation platform for non-tech hiring. It supports talent leaders in sourcing, screening, and interviewing top talent in an inclusive way. The platform offers features such as AI-recommended candidate filters, multi-channel outreach automation, and seamless navigation for hiring. HireQuotient's AI tool revolutionizes talent discovery processes, providing warmth, efficiency, and optimization to organizations' people functions.

PyjamaHR is a leading AI-powered Applicant Tracking System (ATS) and recruitment software designed to streamline the hiring process for businesses of all sizes. It offers advanced features such as source management, candidate evaluation, collaboration tools, and AI-powered candidate tests to enhance the efficiency and effectiveness of the recruitment process. With a user-friendly interface and robust security measures, PyjamaHR is a trusted solution for managing talent acquisition and improving hiring outcomes.

MyEssayWriter.ai is an AI-powered essay writing tool that offers advanced features to help students generate high-quality essays efficiently. The tool is designed to save time, improve writing skills, and provide unique and plagiarism-free content. With a user-friendly interface and customizable essays, MyEssayWriter.ai aims to revolutionize the writing process for students worldwide.

La Growth Machine is a multichannel sales automation tool that helps users import and enrich leads, automate conversions, manage leads, and analyze performances. It offers features such as LinkedIn Voice Messages, multichannel inbox, calls, automation of actions and messages, AI-powered writing assistance, campaign analysis, lead management, and more. La Growth Machine streamlines operational processes, enhances performance, and centralizes data in one place. With a focus on multi-channel prospecting, the tool aims to increase conversations and opportunities for users. Trusted by over 10,000 professionals, La Growth Machine provides a seamless experience for reaching out to leads across various platforms.

myInterview is an AI tool designed for intelligent candidate video screening. It utilizes artificial intelligence to streamline the recruitment process by analyzing video interviews. The tool helps employers efficiently evaluate candidates' communication skills, personality traits, and overall suitability for the job role. With myInterview, organizations can save time and resources typically spent on traditional screening methods, leading to faster hiring decisions and improved candidate experience.

hireEZ is a Sourcing and Recruitment CRM for Talent Acquisition Platform that leverages AI technology to streamline the recruitment process. It offers features such as AI Sourcing, Applicant Match, Automated Outreach, Intelligent Talent Pools, and Insights & Analytics. The platform aims to enhance candidate experience, improve recruitment efficiency, and empower data-driven recruiting strategies for businesses across various industries.

ContentBot is an AI content automation platform that offers a suite of tools to streamline content creation processes for digital marketers, content creators, founders, copywriters, SEO specialists, and bloggers. It leverages AI models like GPT-4 by OpenAI to generate unique and original content in over 110 languages. ContentBot provides features such as AI Flows for digital marketing automation, AI Writer for long-form content generation, Importer for bulk data uploads, and various content creation tools like blog post builders, landing page creators, and more. The platform aims to simplify content marketing tasks and empower users to create targeted, engaging content effortlessly.

Scratchpad is an AI-powered workspace designed for sales teams to streamline their sales processes and enhance productivity. It offers features such as AI Sales Assistant, Pipeline Management, Slack Deal Rooms, Automations & Enablement, Deal Inspection, and Sales Forecasting. With Scratchpad, sales teams can automate collaboration, improve Salesforce hygiene, track deal progress, and gain insights into deal movement and pipeline changes. The application aims to simplify sales workflows, provide real-time notes and call summaries, and enhance team collaboration for better performance and efficiency.

Recooty is a modern applicant tracking system designed for growing companies to streamline their recruiting process. It offers features such as applicant tracking, job posting, candidate tracking, interview scheduling, talent pool management, employer branding, and HR tools. With Recooty, companies can attract, engage, and hire their next teammates with ease. The platform also provides resources like job descriptions, templates, interview questions, and AI tools to enhance the recruitment experience.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

The 'unilm' repository is a collection of tools, models, and architectures for Foundation Models and General AI, focusing on tasks such as NLP, MT, Speech, Document AI, and Multimodal AI. It includes various pre-trained models, such as UniLM, InfoXLM, DeltaLM, MiniLM, AdaLM, BEiT, LayoutLM, WavLM, VALL-E, and more, designed for tasks like language understanding, generation, translation, vision, speech, and multimodal processing. The repository also features toolkits like s2s-ft for sequence-to-sequence fine-tuning and Aggressive Decoding for efficient sequence-to-sequence decoding. Additionally, it offers applications like TrOCR for OCR, LayoutReader for reading order detection, and XLM-T for multilingual NMT.

Panel Cleaner is a tool that uses machine learning to find text in images and generate masks to cover it up with high accuracy. It is designed to clean text bubbles without leaving artifacts, avoiding painting over non-text parts, and inpainting bubbles that can't be masked out. The tool offers various customization options, detailed analytics on the cleaning process, supports batch processing, and can run OCR on pages. It supports CUDA acceleration, multiple themes, and can handle bubbles on any solid grayscale background color. Panel Cleaner is aimed at saving time for cleaners by automating monotonous work and providing precise cleaning of text bubbles.

AIDE is a machine learning code generation agent that can generate solutions for machine learning tasks from natural language descriptions. It has the following features: 1. **Instruct with Natural Language**: Describe your problem or additional requirements and expert insights, all in natural language. 2. **Deliver Solution in Source Code**: AIDE will generate Python scripts for the **tested** machine learning pipeline. Enjoy full transparency, reproducibility, and the freedom to further improve the source code! 3. **Iterative Optimization**: AIDE iteratively runs, debugs, evaluates, and improves the ML code, all by itself. 4. **Visualization**: We also provide tools to visualize the solution tree produced by AIDE for a better understanding of its experimentation process. This gives you insights not only about what works but also what doesn't. AIDE has been benchmarked on over 60 Kaggle data science competitions and has demonstrated impressive performance, surpassing 50% of Kaggle participants on average. It is particularly well-suited for tasks that require complex data preprocessing, feature engineering, and model selection.

uTensor is an extremely light-weight machine learning inference framework built on Tensorflow and optimized for Arm targets. It consists of a runtime library and an offline tool that handles most of the model translation work. The core runtime is only ~2KB. The workflow involves constructing and training a model in Tensorflow, then using uTensor to produce C++ code for inferencing. The runtime ensures system safety, guarantees RAM usage, and focuses on clear, concise, and debuggable code. The high-level API simplifies tensor handling and operator execution for embedded systems.

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LLM training in simple, pure C/CUDA. There is no need for 245MB of PyTorch or 107MB of cPython. For example, training GPT-2 (CPU, fp32) is ~1,000 lines of clean code in a single file. It compiles and runs instantly, and exactly matches the PyTorch reference implementation. I chose GPT-2 as the first working example because it is the grand-daddy of LLMs, the first time the modern stack was put together.

The LiveKit Agent Framework is designed for building real-time, programmable participants that run on servers. Easily tap into LiveKit WebRTC sessions and process or generate audio, video, and data streams. The framework includes plugins for common workflows, such as voice activity detection and speech-to-text. Agents integrates seamlessly with LiveKit server, offloading job queuing and scheduling responsibilities to it. This eliminates the need for additional queuing infrastructure. Agent code developed on your local machine can scale to support thousands of concurrent sessions when deployed to a server in production.

Sail is a tool designed to unify stream processing, batch processing, and compute-intensive workloads, serving as a drop-in replacement for Spark SQL and the Spark DataFrame API in single-process settings. It aims to streamline data processing tasks and facilitate AI workloads.

RPA Framework is an open-source collection of libraries and tools for Robotic Process Automation (RPA), designed to be used with Robot Framework and Python. It offers well-documented core libraries for Software Robot Developers, optimized for Robocorp Control Room and Developer Tools, and accepts external contributions. The project includes various libraries for tasks like archiving, browser automation, date/time manipulations, cloud services integration, encryption operations, database interactions, desktop automation, document processing, email operations, Excel manipulation, file system operations, FTP interactions, web API interactions, image manipulation, AI services, and more. The development of the repository is Python-based and requires Python version 3.8+, with tooling based on poetry and invoke for compiling, building, and running the package. The project is licensed under the Apache License 2.0.

Cyber is a superintelligence protocol that aims to create a decentralized and censorship-resistant internet. It uses a novel consensus mechanism called CometBFT and a knowledge graph to store and process information. Cyber is designed to be scalable, secure, and efficient, and it has the potential to revolutionize the way we interact with the internet.

pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.

PromptMage simplifies the process of creating and managing LLM workflows as a self-hosted solution. It offers an intuitive interface for prompt testing and comparison, incorporates version control features, and aims to improve productivity in both small teams and large enterprises. The tool bridges the gap in LLM workflow management, empowering developers, researchers, and organizations to make LLM technology more accessible and manageable for the next wave of AI innovations.

SiLLM is a toolkit that simplifies the process of training and running Large Language Models (LLMs) on Apple Silicon by leveraging the MLX framework. It provides features such as LLM loading, LoRA training, DPO training, a web app for a seamless chat experience, an API server with OpenAI compatible chat endpoints, and command-line interface (CLI) scripts for chat, server, LoRA fine-tuning, DPO fine-tuning, conversion, and quantization.

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