Best AI tools for< Import Data >

nuvo is an AI-powered data import solution that offers fast, secure, and scalable data import solutions for software companies. It provides tools like nuvo Data Importer SDK and nuvo Data Pipeline to streamline manual and recurring ETL data imports, enabling users to manage data imports independently. With AI-enhanced automation, nuvo helps prepare clean data for preferred systems quickly and efficiently, reducing manual effort and improving data quality. The platform allows users to upload unlimited data in various formats, match imported data to system schemas, clean and validate data, and import clean data into target systems with just a click.

Superjoin is an AI-powered tool that allows users to automatically pull data from various tools into Google Sheets without the need for writing any code. It offers features like one-click connectors, auto-refresh schedules, data preview, and the ability to send report screenshots to Slack and Email. Superjoin is loved by thousands of users across hundreds of companies for its efficiency in automating workflows and data management.

ANDRE is an AI-powered Analytic Narrative Discovery & Reporting Engine that uncovers hidden narratives in raw data, providing valuable insights summarized in concise slides. It simplifies data analysis, making expert-level analysis accessible to all by slashing analysis time by up to 90%. The application blends advanced AI with analytical methods to deliver executive-level data stories. Users can import data from various sources and receive comprehensive reports with conclusions. ANDRE transforms complex data into clear insights and narratives, offering flexibility for automated analysis or user-driven exploration.

Coefficient is a data connector tool for Google Sheets and Excel that empowers users to unlock the full potential of their spreadsheets by providing live connections to over 60 business systems. It offers features such as two-way syncing, automatic refreshes, and scheduled alerts, all powered by AI. Coefficient streamlines data import, visualization, and system updates, enabling users to eliminate manual work, improve data accuracy, and save time. Trusted by over 50,000 companies, Coefficient is a user-friendly tool that enhances data analysis and reporting processes.

LLMStack is an open-source platform that allows users to build AI Agents, workflows, and applications using their own data. It is a no-code AI app builder that supports model chaining from major providers like OpenAI, Cohere, Stability AI, and Hugging Face. Users can import various data sources such as Web URLs, PDFs, audio files, and more to enhance generative AI applications and chatbots. With a focus on collaboration, LLMStack enables users to share apps publicly or restrict access, with viewer and collaborator roles for multiple users to work together. Powered by React, LLMStack provides an easy-to-use interface for building AI applications.

Ultimaps is an AI-powered map visualization tool designed for humans to create color-coded interactive maps in seconds. Users can import data from Excel, Google Spreadsheet, or Notion, or instruct the AI to build a map based on their requirements. The tool allows users to add drawings, change colors and fonts, and easily download, share, or embed the maps. Ultimaps offers features like automatic color-coding based on imported data, customization options, auto-saving of visualizations, and the ability to create interactive maps without any coding. It is a user-friendly platform suitable for various mapping needs.

Deepsheet is a cloud-based spreadsheet application that uses artificial intelligence to help users analyze and visualize data. It offers a variety of features, including the ability to import data from a variety of sources, create charts and graphs, and perform data analysis. Deepsheet is designed to be easy to use, even for users with no prior experience with spreadsheets.

LiveChatAI is an AI chatbot application that works with your data to provide interactive and personalized customer support solutions. It blends AI and human support to deliver dynamic and accurate responses, improving customer satisfaction and reducing support volume. With features like AI Actions, custom question & answers, and content import, LiveChatAI offers a seamless integration for businesses across various platforms and languages. The application is designed to be user-friendly, requiring no AI expertise, and offers instant localization in 95 languages.

Cohesive is an AI tool designed to provide outsourced analysts and assistants for businesses. It enables users to prospect at scale, perform outbound activities with AI enrichment and web scraping directly within Google Sheets. The tool is Google Sheets native, allowing users to enrich and scrape the web without the need to import data into a separate platform. Cohesive also leverages AI for bulk data analysis, personalization generation, web scraping, and email finding/validation. It offers free usage with the option to join the Cohesive Slack community for additional support.

Budgetfy Pro is an AI-powered financial analysis tool designed to simplify and streamline your financial management. With advanced artificial intelligence capabilities, it effortlessly categorizes and analyzes your financial statements with high accuracy. The tool ensures complete privacy by encrypting your financial data and never sharing it with third parties. Users can create custom categories to tailor the tool to their unique financial needs and benefit from multi-currency support for handling transactions in various currencies. Gain detailed insights into your spending habits and financial trends, and easily integrate data from different sources like CSV, PDF, and Excel formats. Take control of your finances and join thousands of users who have optimized their financial management with Budgetfy Pro.

ModularMind is a powerful AI assistant application designed to supercharge work efficiency by offering a range of AI-powered features. It allows users to extract relevant content and links from multiple web pages simultaneously, build AI workflows without coding, save prompts, import data, and utilize ready-to-use templates. Trusted by professionals, ModularMind enhances productivity by automating tasks and streamlining workflows.

Chatbase is a platform that allows users to create custom chatbots for their websites. These chatbots can be used for a variety of purposes, including customer support, lead generation, and user engagement. Chatbase provides a variety of features to help users create and customize their chatbots, including the ability to import data from multiple sources, customize the chatbot's appearance and behavior, and integrate with other tools. Chatbase also offers a variety of pre-built templates and examples to help users get started.

AskCSV is a revolutionary AI-powered tool that empowers you to unlock valuable insights from your CSV files. Simply ask any question about your data, and AskCSV will provide you with instant, accurate answers and visualizations. Your data remains completely secure, processed directly in your browser's memory without any server uploads. With AskCSV, you can effortlessly analyze your data, identify trends, make informed decisions, and gain a deeper understanding of your business.

Entry Point AI is a modern AI optimization platform for fine-tuning proprietary and open-source language models. It provides a user-friendly interface to manage prompts, fine-tunes, and evaluations in one place. The platform enables users to optimize models from leading providers, train across providers, work collaboratively, write templates, import/export data, share models, and avoid common pitfalls associated with fine-tuning. Entry Point AI simplifies the fine-tuning process, making it accessible to users without the need for extensive data, infrastructure, or insider knowledge.

Tactic is an AI-powered platform that provides generative insights and solutions for customers by leveraging AI technology to generate target accounts unique to businesses and new customer insights from various data sources. It offers features such as no-code custom AI builder, process automation, multi-step reasoning, model agnostic data import, and simple user experience. Tactic is trusted by hypergrowth startups and Fortune 500 companies for market research, audience automation, and customer data management. The platform helps users increase revenue, save time on research and analysis, and close more deals efficiently.

CatalogueFlow is an AI-powered platform that automates the creation of product descriptions for online marketplaces. By utilizing sophisticated artificial intelligence algorithms, CatalogueFlow not only saves time and resources but also significantly enhances the visibility and performance of products online. The platform offers features such as automatic generation of product descriptions in customizable formats, translation into various languages with native context, customization of prompts for volume results, template utilization for PDF catalog generation, and the ability to import product data from Excel to generate thousands of descriptions. Transform your business with CatalogueFlow for efficient and optimized product catalog management.

Cradle is a protein engineering platform that uses machine learning to design improved protein sequences. It allows users to import assay data, generate new sequences, test them in the lab, and import the results to improve the model. Cradle can be used to optimize multiple properties of a protein simultaneously, and it has been used by leading biotech teams to accelerate new and ongoing projects.

TaxTim is an AI-powered tax filing application designed to help individuals and businesses in South Africa easily and accurately complete their tax returns. The platform offers a user-friendly interface where users can answer simple questions to generate a fully completed tax return ready for submission to the South African Revenue Service (SARS). TaxTim is integrated with SARS to import IRP5 data, ensuring accurate and timely filing. With a focus on security and maximum refunds, TaxTim is a reliable solution for tax compliance.

EdrawMax is a diagramming software that uses AI to help users create stunning diagrams. It has a wide range of features, including smart containers, Boolean operations, a customizable symbol library, data import and export, and presentation mode. EdrawMax is available for Windows, Mac, Linux, iOS, and Android, and it offers a variety of templates to help users get started. With its powerful features and ease of use, EdrawMax is a great choice for anyone who needs to create diagrams.

Context is an AI-powered chat platform designed to transform your existing knowledge base into a 24/7 tech support bot. It offers smart, automated responses to inquiries, eliminates repetition, automates replies to FAQs, and helps you understand user queries for product enhancement. With features like GPT-4 enabled responses, multi-source data import, teammate collaboration, and response ranking, Context aims to streamline customer support processes and enhance user experience.

Postgres.new is an in-browser Postgres sandbox with AI assistance that allows users to spin up unlimited Postgres databases directly in the browser. Each database comes with a large language model (LLM) enabling features like drag-and-drop CSV import, report generation, chart creation, and database diagram building. The tool utilizes PGlite, a WASM version of Postgres, to run databases in the browser and store data in IndexedDB for persistence. The monorepo includes a frontend built with Next.js and a backend serving S3-backed PGlite databases over the PG wire protocol using pg-gateway.

Scira is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for data exploration, cleaning, and modeling. With Scira, users can easily import datasets, perform statistical analysis, create insightful visualizations, and generate reports. The tool supports various data formats and offers a wide range of statistical functions and visualization options. Whether you are a data scientist, researcher, or student, Scira can help you uncover valuable insights from your data and communicate your findings effectively.

OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

Sales & Dungeons is a tool that utilizes thermal printers for creating customizable handouts, quick references, and more for Dungeons and Dragons sessions. It offers extensive templating and random generation systems, supports various connection methods, and allows importing/exporting templates and data sources. Users can access external data sources like Open5e, import data from CSV and other formats, and utilize AI prompt generation and translation. The tool supports cloud sync and is compatible with multiple operating systems and devices.

Financial Datasets is an open-source Python library that allows users to create question and answer financial datasets using Large Language Models (LLMs). With this library, users can easily generate realistic financial datasets from 10-K, 10-Q, PDF, and other financial texts. The library provides three main methods for generating datasets: from any text, from a 10-K filing, or from a PDF URL. Financial Datasets can be used for a variety of tasks, including financial analysis, research, and education.

DataHorse is an open-source tool and Python library that simplifies data science for everyone. It allows users to interact with data in plain English without requiring technical skills. Users can create graphs, modify data, and build machine learning models to make predictions. The tool is designed to help businesses and individuals quickly understand their data and make data-driven decisions with ease.

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.

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.

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

Evidently is an open-source Python library designed for evaluating, testing, and monitoring machine learning (ML) and large language model (LLM) powered systems. It offers a wide range of functionalities, including working with tabular, text data, and embeddings, supporting predictive and generative systems, providing over 100 built-in metrics for data drift detection and LLM evaluation, allowing for custom metrics and tests, enabling both offline evaluations and live monitoring, and offering an open architecture for easy data export and integration with existing tools. Users can utilize Evidently for one-off evaluations using Reports or Test Suites in Python, or opt for real-time monitoring through the Dashboard service.

Promptwright is a Python library designed for generating large synthetic datasets using a local LLM and various LLM service providers. It offers flexible interfaces for generating prompt-led synthetic datasets. The library supports multiple providers, configurable instructions and prompts, YAML configuration for tasks, command line interface for running tasks, push to Hugging Face Hub for dataset upload, and system message control. Users can define generation tasks using YAML configuration or Python code. Promptwright integrates with LiteLLM to interface with LLM providers and supports automatic dataset upload to Hugging Face Hub.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

Lhotse is a Python library designed to make speech and audio data preparation flexible and accessible. It aims to attract a wider community to speech processing tasks by providing a Python-centric design and an expressive command-line interface. Lhotse offers standard data preparation recipes, PyTorch Dataset classes for speech tasks, and efficient data preparation for model training with audio cuts. It supports data augmentation, feature extraction, and feature-space cut mixing. The tool extends Kaldi's data preparation recipes with seamless PyTorch integration, human-readable text manifests, and convenient Python classes.

Open-Source Evaluation for LLM Applications. `continuous-eval` is an open-source package created for granular and holistic evaluation of GenAI application pipelines. It offers modularized evaluation, a comprehensive metric library covering various LLM use cases, the ability to leverage user feedback in evaluation, and synthetic dataset generation for testing pipelines. Users can define their own metrics by extending the Metric class. The tool allows running evaluation on a pipeline defined with modules and corresponding metrics. Additionally, it provides synthetic data generation capabilities to create user interaction data for evaluation or training purposes.

PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

RAGoon is a high-level library designed for batched embeddings generation, fast web-based RAG (Retrieval-Augmented Generation) processing, and quantized indexes processing. It provides NLP utilities for multi-model embedding production, high-dimensional vector visualization, and enhancing language model performance through search-based querying, web scraping, and data augmentation techniques.

Bespoke Curator is an open-source tool for data curation and structured data extraction. It provides a Python library for generating synthetic data at scale, with features like programmability, performance optimization, caching, and integration with HuggingFace Datasets. The tool includes a Curator Viewer for dataset visualization and offers a rich set of functionalities for creating and refining data generation strategies.

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

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.

Hosts a real SQLite database and helps you create tables, make schema changes, and run SQL queries, ideal for all levels of database administration.

“Data Deep Dive”: This is an expert AI tool for Excel and Power BI. Get expert help with DAX, Power Query, VBA, data models, and visualizations. Ideal for all levels: from basic functions to advanced analytics.

Your Stata research assistant

Your go-to guide for STATA

Excel vba Assistant,Press ALT + F11 to paste the code onto the active sheet, and press the triangle play button.

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Translates language text in JSON files.

Import Export Compliance | Tariff Classification | Shipping Queries | Logistics & Supply Chain Solutions

Your Expert and Assistant in International Trade

Worldwide expert in trade logistics and regulations.

Zoll-GPT: Expertise in Zollfragen mit detaillierter und proaktiver Internetrecherche.

专业耐心的外贸CEO顾问。

A personal shopping assistant for international buyers of UK products.

Advises on global business expansion and growth strategies.

AI Assists in learning and troubleshooting Ladybug Tools.

Professionally converts academic bibliographies to RIS, with minimal interaction. The RIS output can then be copied, and pasted into Zotero using Ctrl-Alt-Shift-I.

Create JSON recipes for the MV1

Prepares an exhaustive set of Q/A pairs that can be imported as Anki Flash Cards. Just upload your document and put the number of flashcards you want. No pleasantries required.

Expert in Quebec income tax returns, providing precise, professional advice. (2022 documents will update when 2023 documents are available)