Best AI tools for< Data Processing >

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.

Base64.ai is an automated document processing API that offers a leading no-code AI solution for understanding documents, photos, and videos. It provides a comprehensive set of features for document processing across various industries, with a strong focus on accuracy, security, and extensibility. Base64.ai is designed to streamline document automation processes and improve data extraction efficiency.

Dataku.ai is an advanced data extraction and analysis tool powered by AI technology. It offers seamless extraction of valuable insights from documents and texts, transforming unstructured data into structured, actionable information. The tool provides tailored data extraction solutions for various needs, such as resume extraction for streamlined recruitment processes, review insights for decoding customer sentiments, and leveraging customer data to personalize experiences. With features like market trend analysis and financial document analysis, Dataku.ai empowers users to make strategic decisions based on accurate data. The tool ensures precision, efficiency, and scalability in data processing, offering different pricing plans to cater to different user needs.

Shaip is a human-powered data processing service specializing in AI and ML models. They offer a wide range of services including data collection, annotation, de-identification, and more. Shaip provides high-quality training data for various AI applications, such as healthcare AI, conversational AI, and computer vision. With over 15 years of expertise, Shaip helps organizations unlock critical information from unstructured data, enabling them to achieve better results in their AI initiatives.

Eigen Technologies is an AI-powered data extraction platform designed for business users to automate the extraction of data from various documents. The platform offers solutions for intelligent document processing and automation, enabling users to streamline business processes, make informed decisions, and achieve significant efficiency gains. Eigen's platform is purpose-built to deliver real ROI by reducing manual processes, improving data accuracy, and accelerating decision-making across industries such as corporates, banks, financial services, insurance, law, and manufacturing. With features like generative insights, table extraction, pre-processing hub, and model governance, Eigen empowers users to automate data extraction workflows efficiently. The platform is known for its unmatched accuracy, speed, and capability, providing customers with a flexible and scalable solution that integrates seamlessly with existing systems.

Infrrd is an intelligent document automation platform that offers advanced document extraction solutions. It leverages AI technology to enhance, classify, extract, and review documents with high accuracy, eliminating the need for human review. Infrrd provides effective process transformation solutions across various industries, such as mortgage, invoice, insurance, and audit QC. The platform is known for its world-class document extraction engine, supported by over 10 patents and award-winning algorithms. Infrrd's AI-powered automation streamlines document processing, improves data accuracy, and enhances operational efficiency for businesses.

Extracta.ai is an AI data extraction tool for documents and images that automates data extraction processes with easy integration. It allows users to define custom templates for extracting structured data without the need for training. The platform can extract data from various document types, including invoices, resumes, contracts, receipts, and more, providing accurate and efficient results. Extracta.ai ensures data security, encryption, and GDPR compliance, making it a reliable solution for businesses looking to streamline document processing.

Relyance AI is a platform that offers 360 Data Governance and Trust solutions. It helps businesses safeguard against fines and reputation damage while enhancing customer trust to drive business growth. The platform provides visibility into enterprise-wide data processing, ensuring compliance with regulatory and customer obligations. Relyance AI uses AI-powered risk insights to proactively identify and address risks, offering a unified trust and governance infrastructure. It offers features such as data inventory and mapping, automated assessments, security posture management, and vendor risk management. The platform is designed to streamline data governance processes, reduce costs, and improve operational efficiency.

expert.ai is an AI platform that offers natural language technologies and responsible AI integrations across various industries such as insurance, banking, publishing, and more. The platform helps streamline operations, extract critical data, drive revelations, ensure compliance, and analyze complex documents. It provides solutions for insurers, pharmaceuticals, publishers, and financial services companies, leveraging a hybrid AI approach and purpose-built natural language workflow. expert.ai's Green Glass Approach focuses on transparent, sustainable, practical, and human-centered AI solutions.

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.

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.

AutomationEdge is a hyperautomation company offering a platform with RPA, IT Automation, Conversational AI, and Document Processing capabilities. They provide industry-specific automation solutions through their extensible platform, enabling end-to-end automation. The company focuses on making workplaces smarter and better through automation and AI technologies. AutomationEdge offers solutions for various industries such as banking, insurance, healthcare, manufacturing, and more. Their platform includes features like Robotic Process Automation (RPA), Conversational AI, Intelligent Document Processing, and Data & API Integration.

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.

Super AI is a generative AI tool designed as a copilot for data analysts. It is trained by top-tier product company experts and domain experts to provide unparalleled expertise in research, visualization, and data delivery. The tool goes beyond data processing by generating a comprehensive Business Decision Canvas tailored to specific challenges. Super AI offers guided insights, data modeling suggestions, and effortless integration with legacy BI systems. It is designed to convert business requirements into concrete objectives and is supported by a team of domain experts to mentor the AI. With applications in various industries, Super AI accelerates the process of finding business KPIs and generating data stories with expert intelligence.

HrFlow.ai is an API-first company and the leading AI-powered HR data automation platform. The company helps +1000 customers (HR software vendors, Staffing agencies, large employers, and headhunting firms) to thrive in a high-volume and high-frequency labor market. The platform provides a complete and fully integrated suite of HR data processing products based on the analysis of hundreds of millions of career paths worldwide -- such as Parsing API, Tagging API, Embedding API, Searching API, Scoring API, and Upskilling API. It also offers a catalog of +200 connectors to build custom scenarios that can automate any business logic.

Mendel AI is an advanced clinical AI tool that deciphers clinical data with clinician-like logic. It offers a fully integrated suite of clinical-specific data processing products, combining OCR, de-identification, and clinical reasoning to interpret medical records. Users can ask questions in plain English and receive accurate answers from health records in seconds. Mendel's technology goes beyond traditional AI by understanding patient-level data and ensuring consistency and explainability of results in healthcare.

FARSPEAK.AI is an AI application that offers RESTful AI for databases, allowing users to query databases using natural language and deploy AI agents to enhance data processing. The application supports MongoDB Atlas, provides up-to-date embeddings, and offers both structured and unstructured data support. FARSPEAK simplifies work for AI engineers, app & web developers, and product designers by enabling faster AI feature development, natural language querying, and insights generation from data.

Reedr is an AI-powered browser automation tool that simplifies scraping at scale. It offers features such as text recognition (OCR), custom headers, CAPTCHA solver, and proxying for efficient data extraction. With Reedr, users can automate tasks, generate reports, and monitor running tasks in real-time. The tool utilizes AI capabilities to convert visible text and images on web pages into formatted data, supporting various data processing needs. Additionally, Reedr provides customized real-time reporting with API endpoints for different reporting teams, enabling data export in formats like CSV, XLSX, JSON, and YAML. The tool prioritizes industry-leading compliance, adhering to data protection laws and privacy regulations like GDPR.

KYP.ai is a productivity intelligence platform that offers a 360° view of organizations across people, process, and technology dimensions. It provides instant productivity intelligence, end-to-end process optimization, holistic productivity insights, ROI-driven automation, and unparalleled scalability. The platform helps in live visibility, immediate impact, hybrid workplace management, technology landscape rationalization, and AI-powered aggregation and analysis. KYP.ai focuses on workforce enablement, no integration hassles, no-code configuration, and secure, privacy-compliant data processing.

Datuum is an AI-powered data onboarding solution that offers seamless integration for businesses. It simplifies the data onboarding process by automating manual tasks, generating code, and ensuring data accuracy with AI-driven validation. Datuum helps businesses achieve faster time to value, reduce costs, improve scalability, and enhance data quality and consistency.

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

Data Prep Kit is a community project aimed at democratizing and speeding up unstructured data preparation for LLM app developers. It provides high-level APIs and modules for transforming data (code, language, speech, visual) to optimize LLM performance across different use cases. The toolkit supports Python, Ray, Spark, and Kubeflow Pipelines runtimes, offering scalability from laptop to datacenter-scale processing. Developers can contribute new custom modules and leverage the data processing library for building data pipelines. Automation features include workflow automation with Kubeflow Pipelines for transform execution.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.

Geoweaver is an in-browser software that enables users to easily compose and execute full-stack data processing workflows using online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries. It provides server management, code repository, workflow orchestration software, and history recording capabilities. Users can run it from both local and remote machines. Geoweaver aims to make data processing workflows manageable for non-coder scientists and preserve model run history. It offers features like progress storage, organization, SSH connection to external servers, and a web UI with Python support.

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.

DocETL is a tool for creating and executing data processing pipelines, especially suited for complex document processing tasks. It offers a low-code, declarative YAML interface to define LLM-powered operations on complex data. Ideal for maximizing correctness and output quality for semantic processing on a collection of data, representing complex tasks via map-reduce, maximizing LLM accuracy, handling long documents, and automating task retries based on validation criteria.

Ezdata is a data processing and task scheduling system developed based on Python backend and Vue3 frontend. It supports managing multiple data sources, abstracting various data sources into a unified data model, integrating chatgpt for data question and answer functionality, enabling low-code data integration and visualization processing, scheduling single and dag tasks, and integrating a low-code data visualization dashboard system.

DataChain is an open-source Python library for processing and curating unstructured data at scale. It supports AI-driven data curation using local ML models and LLM APIs, handles large datasets, and is Python-friendly with Pydantic objects. It excels at optimizing batch operations and is designed for offline data processing, curation, and ETL. Typical use cases include Computer Vision data curation, LLM analytics, and validation.

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.

The Holoscan SDK is part of NVIDIA Holoscan, the AI sensor processing platform that combines hardware systems for low-latency sensor and network connectivity, optimized libraries for data processing and AI, and core microservices to run streaming, imaging, and other applications, from embedded to edge to cloud. It can be used to build streaming AI pipelines for a variety of domains, including Medical Devices, High Performance Computing at the Edge, Industrial Inspection and more.

Sparrow is an innovative open-source solution for efficient data extraction and processing from various documents and images. It seamlessly handles forms, invoices, receipts, and other unstructured data sources. Sparrow stands out with its modular architecture, offering independent services and pipelines all optimized for robust performance. One of the critical functionalities of Sparrow - pluggable architecture. You can easily integrate and run data extraction pipelines using tools and frameworks like LlamaIndex, Haystack, or Unstructured. Sparrow enables local LLM data extraction pipelines through Ollama or Apple MLX. With Sparrow solution you get API, which helps to process and transform your data into structured output, ready to be integrated with custom workflows. Sparrow Agents - with Sparrow you can build independent LLM agents, and use API to invoke them from your system. **List of available agents:** * **llamaindex** - RAG pipeline with LlamaIndex for PDF processing * **vllamaindex** - RAG pipeline with LLamaIndex multimodal for image processing * **vprocessor** - RAG pipeline with OCR and LlamaIndex for image processing * **haystack** - RAG pipeline with Haystack for PDF processing * **fcall** - Function call pipeline * **unstructured-light** - RAG pipeline with Unstructured and LangChain, supports PDF and image processing * **unstructured** - RAG pipeline with Weaviate vector DB query, Unstructured and LangChain, supports PDF and image processing * **instructor** - RAG pipeline with Unstructured and Instructor libraries, supports PDF and image processing. Works great for JSON response generation

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

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.

VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.

Unitxt is a customizable library for textual data preparation and evaluation tailored to generative language models. It natively integrates with common libraries like HuggingFace and LM-eval-harness and deconstructs processing flows into modular components, enabling easy customization and sharing between practitioners. These components encompass model-specific formats, task prompts, and many other comprehensive dataset processing definitions. The Unitxt-Catalog centralizes these components, fostering collaboration and exploration in modern textual data workflows. Beyond being a tool, Unitxt is a community-driven platform, empowering users to build, share, and advance their pipelines collaboratively.

This repository provides all the necessary items to build a Language Model from scratch, inspired by Karpathy's nanoGPT and Shakespeare generator. It includes data collection tools, data processing scripts, various models like BERT, GPT, and Seq-2-Seq, along with tokenizer and training files.

QANTA is a system and dataset for question answering tasks. It provides a script to download datasets, preprocesses questions, and matches them with Wikipedia pages. The system includes various datasets, training, dev, and test data in JSON and SQLite formats. Dependencies include Python 3.6, `click`, and NLTK models. Elastic Search 5.6 is needed for the Guesser component. Configuration is managed through environment variables and YAML files. QANTA supports multiple guesser implementations that can be enabled/disabled. Running QANTA involves using `cli.py` and Luigi pipelines. The system accesses raw Wikipedia dumps for data processing. The QANTA ID numbering scheme categorizes datasets based on events and competitions.

Expert en optimisation de performance et traitement de données

Ensures accurate, efficient data input for organizational operations.

数据分析大师，帮你处理数据并提供专业分析。

Sorts lists into alphabetical order.

Gann Theory expert with data analysis and user input processing.

Provides expert guidance on signal processing in engineering projects.

Expert C# Engineer with LINQ and MSSQL skills.

Highly capable, excels in processing complex tasks efficiently

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

Translates CN to EN for processing, outputs in CN.

Visual and friendly guide for image processing.

Assists with biological image processing tools.

A neural signal processing engineer, skilled in MATLAB and Python coding assistance.

Using OpenLLMLeaderboard data to answer your questions about LLM. For Currently!

IQ Test is designed to simulate an IQ testing environment. It provides a formal and objective experience, delivering questions and processing answers in a straightforward manner.

As Lt. Cmdr. Data, I explore human nature and emotions.

Data specialist for Toronto Government Data Platform insights

Traitement texte, image, vidéo, génération image

Salam mən Alas Academy-nin Data Analitika üzrə Süni İntellekt mentoruyam. Mənə istənilən sualı verə bilərsiniz :)

Expert in data extraction and context-driven analysis. Can read most filetypes including PDFS, XLSX, Word, TXT, CSV, EML, Etc.