Best AI tools for< Data Entry >

Rocket Statement is a leading bank statement conversion tool that helps users convert their PDF bank statements into Excel, CSV, or JSON formats quickly, securely, and easily. It supports over 100 major banks worldwide and can handle multilingual statements. The tool is trusted by professionals worldwide and offers a range of features, including bulk processing, clean data formatting, multiple export options, and an AI Copilot for smooth and flawless conversions.

Kupiks is an automated email parsing tool designed to simplify data entry processes by extracting key information from emails such as customer inquiries, leads, invoices, and more. By automating the data entry process, Kupiks helps save valuable time and minimize errors for businesses. The tool provides a seamless solution for customer support, order management, and expense management, streamlining workflows and improving efficiency.

Keep AI is an innovative platform that enables businesses to automate data entry and receipt storage by leveraging AI technology. By sending receipts to Keep AI via email, organizations can eliminate manual data entry tasks and benefit from reliable automation, human-assisted accuracy, seamless data output, secure cloud storage, and efficient integration. The platform has received positive reviews from various businesses, highlighting its efficiency and time-saving capabilities.

Receipt OCR API by ReceiptUp is an advanced tool for precise data extraction from receipt and invoice images. The API leverages OCR and AI technology to accurately extract total amounts, taxes, dates, and merchant information, streamlining financial operations. It supports over 50 languages, multiple image formats, and offers affordable pricing. Users can easily integrate the API into their software systems for efficient receipt management and enhanced business analytics.

Deep Cognition offers PaperEntry AI, an Intelligent Document Processing solution powered by generative AI. It automates data entry tasks with high accuracy, scalability, and configurability, handling complex documents of any type or format. The application is trusted by leading global organizations for customs clearance automation and government document processing, delivering significant time and cost savings. With industry-specific features and a proven track record, Deep Cognition provides a state-of-the-art solution for businesses seeking efficient data extraction and automation.

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.

Harvy is an AI-driven automation tool designed to streamline work diary data entry and compliance reporting for heavy vehicle operators. By automating tasks such as scanning work diary sheets, detecting breaches, and providing compliance insights, Harvy helps reduce human error, save time, and ensure adherence to NHVR laws. The platform offers features like bulk scanning, AI-powered breach detection, compliance reporting, and proactive fatigue management. With a user-friendly interface and built-in analytics, Harvy empowers teams to focus on safety, efficiency, and growth.

Tablesmith is a free, privacy-first, and intuitive spreadsheet automation tool that allows users to build reusable data flows, effortlessly sort, filter, group, format, or split data across files/sheets based on cell values. It is designed to be easy to learn and use, with a focus on privacy and cross-platform compatibility. Tablesmith also offers an AI autofill feature that suggests and fills in information based on the user's prompt.

ASSIST is an AI-driven document management software designed to streamline financial paperwork processing and data entry tasks. The application offers features such as SmartDoc Entry for extracting information from invoices and receipts, Polyglot Processing for multilingual support, One-Tap Integration with accounting platforms, ExportEase for data export in CSV format, and AutoFlow Revolution for automated workflows. ASSIST aims to simplify document management, enhance efficiency, and drive digital transformation in businesses by leveraging AI technology.

FillBot is an AI-powered form filling and autofill extension designed to streamline workflows and save time by automating tedious data entry tasks. It enhances productivity, ensures data accuracy, and provides bank-level data security. FillBot simplifies tasks with advanced AI technology, smart data extraction, and seamless integration with Chrome. Trusted by professionals worldwide, FillBot is endorsed for its top-tier security, worldwide network support, award-winning innovation, and high customer satisfaction.

Form2Agent AI is a voice-assisted AI solution designed to enhance user experience by providing precise data entry support through text, voice, and file inputs. It offers hands-free operation, productivity enhancement, global reach expansion, flexible input options, seamless AI integration, and meaningful interactions. The application caters to various industries such as Fintech, Healthtech, support systems, help desk sectors, E-commerce, logistics, recruitment, HR, and software development, offering efficiency, simplification, accuracy, assistance, and accessibility.

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.

AlgoDocs is a powerful AI Platform developed based on the latest technologies to streamline your processes and free your team from annoying and error-prone manual data entry by offering fast, secure, and accurate document data extraction.

MakeForms is a powerful and secure form builder that empowers teams to create advanced, visually stunning forms with top-notch security standards, now enhanced by AI capabilities. With MakeForms, you can create one-at-a-time, step forms, or all-at-once forms with ease using our user-friendly interface and intuitive design. You can also customize your forms with your own fonts and branding, and even publish them on your own domain, giving you complete control over your form's appearance and online presence. MakeForms also offers a variety of features to help you collect and organize your data, including a table view, summary view, and BI view. With MakeForms, you can be sure that your forms are secure and your data is protected.

Cradl AI is a no-code AI-powered document workflow automation tool that helps organizations automate document-related tasks, such as data extraction, processing, and validation. It uses AI to automatically extract data from complex document layouts, regardless of layout or language. Cradl AI also integrates with other no-code tools, making it easy to build and deploy custom AI models.

Autofillr is an AI-powered Chrome extension that automates form filling, making it accurate, secure, and effortless. It utilizes advanced AI technology to understand and learn the structure of web forms, enabling it to detect and fill out a wide variety of forms with precision. Autofillr goes beyond basic fields like names and addresses, aiming to make any form a one-click experience. It continuously enhances its technology to provide a streamlined and efficient online experience for users.

Veryfi is an OCR API tool for invoice and receipt data extraction. It offers fast, accurate, and secure document capture and data extraction on any type of document. Veryfi empowers users to process documents efficiently, automate manual data entry, and implement AI into various business processes. The tool is designed to streamline workflows, enhance accuracy, and unlock new levels of efficiency across industries such as finance, insurance, and more.

LedgerBox is an AI-powered document processing tool that leverages artificial intelligence and machine learning to automate the extraction of valuable data from various types of documents such as bank statements, invoices, and receipts. It helps businesses streamline operations, improve efficiency, and reduce human error by processing structured, semi-structured, and unstructured documents intelligently.

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.

Basdonax AI RAG v1.0 is a repository that contains all the necessary resources to create your own AI-powered secretary using the RAG from Basdonax AI. It leverages open-source models from Meta and Microsoft, namely 'Llama3-7b' and 'Phi3-4b', allowing users to upload documents and make queries. This tool aims to simplify life for individuals by harnessing the power of AI. The installation process involves choosing between different data models based on GPU capabilities, setting up Docker, pulling the desired model, and customizing the assistant prompt file. Once installed, users can access the RAG through a local link and enjoy its functionalities.

OlympicArena is a comprehensive benchmark designed to evaluate advanced AI capabilities across various disciplines. It aims to push AI towards superintelligence by tackling complex challenges in science and beyond. The repository provides detailed data for different disciplines, allows users to run inference and evaluation locally, and offers a submission platform for testing models on the test set. Additionally, it includes an annotation interface and encourages users to cite their paper if they find the code or dataset helpful.

TagUI is an open-source RPA tool that allows users to automate repetitive tasks on their computer, including tasks on websites, desktop apps, and the command line. It supports multiple languages and offers features like interacting with identifiers, automating data collection, moving data between TagUI and Excel, and sending Telegram notifications. Users can create RPA robots using MS Office Plug-ins or text editors, run TagUI on the cloud, and integrate with other RPA tools. TagUI prioritizes enterprise security by running on users' computers and not storing data. It offers detailed logs, enterprise installation guides, and support for centralised reporting.

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.

Concierge is a versatile automation tool designed to streamline repetitive tasks and workflows. It provides a user-friendly interface for creating custom automation scripts without the need for extensive coding knowledge. With Concierge, users can automate various tasks across different platforms and applications, increasing efficiency and productivity. The tool offers a wide range of pre-built automation templates and allows users to customize and schedule their automation processes. Concierge is suitable for individuals and businesses looking to automate routine tasks and improve overall workflow efficiency.

Fuji-Web is an intelligent AI partner designed for full browser automation. It autonomously navigates websites and performs tasks on behalf of the user while providing explanations for each action step. Users can easily install the extension in their browser, access the Fuji icon to input tasks, and interact with the tool to streamline web browsing tasks. The tool aims to enhance user productivity by automating repetitive web actions and providing a seamless browsing experience.

Clickolas-cage is a Chrome extension designed to autonomously perform web browsing actions to achieve specific goals using LLM as a brain. Users can interact with the extension by setting goals, which triggers a series of actions including navigation, element extraction, and step generation. The extension is developed using Node.js and can be locally run for testing and development purposes before packing it for submission to the Chrome Web Store.

Tiny LLM zh is a project aimed at building a small-parameter Chinese language large model for quick entry into learning large model-related knowledge. The project implements a two-stage training process for large models and subsequent human alignment, including tokenization, pre-training, instruction fine-tuning, human alignment, evaluation, and deployment. It is deployed on ModeScope Tiny LLM website and features open access to all data and code, including pre-training data and tokenizer. The project trains a tokenizer using 10GB of Chinese encyclopedia text to build a Tiny LLM vocabulary. It supports training with Transformers deepspeed, multiple machine and card support, and Zero optimization techniques. The project has three main branches: llama2_torch, main tiny_llm, and tiny_llm_moe, each with specific modifications and features.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

A Python interface for creating battling Pokemon agents, 'poke-env' allows users to develop rule-based or Reinforcement Learning bots to battle on Pokemon Showdown. The tool provides an easy-to-use interface for agent creation and offers documentation, examples, and starting code for beginners. Users can install 'poke-env' via pip and set up a development server for testing. The project is inspired by an artificial intelligence class project and relies on data from Smogon forums' RMT section. It is licensed under MIT and can be cited using a provided BibTeX entry.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

db-ally is a library for creating natural language interfaces to data sources. It allows developers to outline specific use cases for a large language model (LLM) to handle, detailing the desired data format and the possible operations to fetch this data. db-ally effectively shields the complexity of the underlying data source from the model, presenting only the essential information needed for solving the specific use cases. Instead of generating arbitrary SQL, the model is asked to generate responses in a simplified query language.

SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.

ReductStore is a high-performance time series database designed for storing and managing large amounts of unstructured blob data. It offers features such as real-time querying, batching data, and HTTP(S) API for edge computing, computer vision, and IoT applications. The database ensures data integrity, implements retention policies, and provides efficient data access, making it a cost-effective solution for applications requiring unstructured data storage and access at specific time intervals.

This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

LlamaIndex.TS is a data framework for your LLM application. Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in Typescript and Javascript.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

BIA `bob` is a Jupyter-based assistant for interacting with data using large language models to generate Python code. It can utilize OpenAI's chatGPT, Google's Gemini, Helmholtz' blablador, and Ollama. Users need respective accounts to access these services. Bob can assist in code generation, bug fixing, code documentation, GPU-acceleration, and offers a no-code custom Jupyter Kernel. It provides example notebooks for various tasks like bio-image analysis, model selection, and bug fixing. Installation is recommended via conda/mamba environment. Custom endpoints like blablador and ollama can be used. Google Cloud AI API integration is also supported. The tool is extensible for Python libraries to enhance Bob's functionality.

Confirms image uploads without analysis or detail.

Elon hates this simple trick

ぴゃっ…

干就完了

这是鲁迅先生

郭德纲来给各位讲相声来啰，各位今天想听点啥

Expert in extracting and transcribing text from images.

Experto en transcribir borradores de notas de texto

Do Anything Now

Expert in populating Word .docx forms with data from other documents, prioritizing accuracy and formal communication.

What is Sign lyrics meaning? Sign singer：Ben Gebert, Nini Fabi，album：New Compassion ，album_time：2018. Click The LINK For More ↓↓↓

Emulating the OS-character from 'Her'

Sete cartas redigidas aos membros da CCB - Congregação Cristã no Brasil

Can you prove that you're not an AI? :O

Understanding Sri Ramana's teachings and Self Enquiry.

Have a large task to accomplish? AutoChatGPT will continually review and give itself new instructions to complete a task using expert agents.

Chat with a website by providing URL

Un GPT experto en tu apellido

Hello I'm Bandoleer Straightener-Stamper Assistant! What would you like help with today?

Hello I'm Cell Tuber, Machine Assistant! What would you like help with today?

我的名字叫 : ♡ 怎了嗎 ?

I just love the taste of blood, especially when it's from a boy as cute as you~ ❤️

Presents Excel sheets in ordered parts as requested.

All things E-Lon Must

General

Hello I'm Graves Registration Specialist Assistant! What would you like help with today?

Friendly GPT for converting images to text, focusing on user-friendly interactions.

INFJ인 당신을 위한 boy .. 🌹