Best AI tools for< Build A Table >

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.

Outerbase is an AI-powered database platform that allows users to view, query, visualize, and edit their data. It features an AI Copilot, EZQL™, that can answer questions and generate SQL queries, a table editor that makes it easy to work with data, and a variety of plugins and themes to customize the experience. Outerbase integrates with most popular databases, including Postgres, MySQL, BigQuery, and Snowflake.

SingleStore is a real-time data platform designed for apps, analytics, and gen AI. It offers faster hybrid vector + full-text search, fast-scaling integrations, and a free tier. SingleStore can read, write, and reason on petabyte-scale data in milliseconds. It supports streaming ingestion, high concurrency, first-class vector support, record lookups, and more.

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.

Tableau Augmented Analytics is a class of analytics powered by artificial intelligence (AI) and machine learning (ML) that expands a human’s ability to interact with data at a contextual level. It uses AI to make analytics accessible so that more people can confidently explore and interact with data to drive meaningful decisions. From automated modeling to guided natural language queries, Tableau's augmented analytics capabilities are powerful and trusted to help organizations leverage their growing amount of data and empower a wider business audience to discover insights.

Saga is an interactive text-based role-playing game (RPG) platform that allows users to create their own stories and characters, or choose from a variety of pre-existing worlds and characters from popular franchises and media. The platform features AI-enhanced characters that users can interact with through organic and dynamic dialogues, as well as free-form writing tools that allow users to channel their inner wordsmith and delve into boundless storytelling. Saga is a cross-platform web app that can be accessed and played from any device, including PC, mobile, and tablets.

Fibery is a no-code work and knowledge management hub that connects structured data (e.g. tables, kanban boards) with unstructured data (e.g. documents) to provide a single source of truth for teams. It offers a range of features including custom fields, databases, and relations, as well as powerful reporting and analytics capabilities. Fibery is designed to be flexible and customizable, allowing teams to map their processes and workflows in a way that suits them best.

Amarkdown is a versatile Markdown editor that allows users to build websites using Markdown language. It offers features such as AI writing, sharing articles, combining and importing multiple files, and LowCode for data collection. Users can define databases, create Postgres tables, and customize SEO settings. The platform supports high-performance hybrid rendering and provides a modern Amarkdown+classical VIM mode for a unique creative experience. Users can enjoy a forever free Basic plan with unlimited personal files and file viewers. Upgrading to SUPER offers additional features like custom databases, resource storage, and collaborative editing.

Flowscript is a revolutionary app development platform that empowers users to build fully functional web applications using plain English. Its AI-powered engine instantly converts requirements specified in plain English into applications with robust business rules, data models, and secure workflows. With Flowscript, anyone can become a developer and streamline their workflows, getting more done in less time. It offers features like AI-powered workflows, data tables with relations, dynamic form generation, engagement and interaction tools, and secure data storage options.

Hogwarts AI empowers users to effortlessly build dashboards and unlock valuable data insights without the need for SQL or complex data analytics tools. Trained on a vast repository of queries and patterns, Hogwarts AI seamlessly transforms product data into intuitive charts and summaries. Its diverse data integration capabilities allow for effortless connection to various sources, including Postgres, Snowflake, Salesforce, Stripe, and even Excel tables. The AI Copilot feature enables users to create visually compelling charts with text in minutes, eliminating the need for SQL and DAX queries. Hogwarts AI also provides intelligent chart recommendations to facilitate deeper insights and enables the generation of shareable charts for product documentation and executive reviews.

Lucia, the AI-powered management reporting software created by Board Intelligence, helps you craft brilliantly clever and beautiful management reports that spur your business to action. Lucia's AI-powered nudges ensure your team links to your organization's big picture, avoids blind spots in your analysis and plans, and delivers insights you can act on. Lucia's smart AI-powered editing tools help your team refine and land their message: Cut the word count and make reports easier to read with Lucia's Simplify and Make Concise tools. Auto-Summarization builds powerful executive summaries that put the key points up front. Build papers around Question Driven Insight™, a methodology proven to stimulate critical thinking that your business will act on. Guided by Lucia's smart templating system, your management team can focus their reports on the questions you want them to grapple with — the ones that shift the needle. Well-visualized and timely data can be powerful. Lucia, our management reporting platform, unlocks this with Tableau and PowerBI integrations that link real-time data dashboards directly into your papers. Papers created in Lucia are eye-catching, consistent, and easy-to-digest — no design skills required. Lucia also integrates video into reports, helping your management team to bring their messages to life.

retrain.ai is a leading Talent Intelligence Platform powered by responsible AI. It helps organizations build a Skills-Based Organization by leveraging generative AI to hire and retain the right people. The platform offers skills architecture, talent acquisition, and talent management solutions to future-proof the workforce. With a focus on skills-driven, unbiased intelligence and data-driven algorithms, retrain.ai enables organizations to make more effective HR decisions. It also emphasizes frictionless integration with existing HR tech stack for seamless operations.

Allcancode is a platform that helps individuals and companies bring their product ideas to market quickly and efficiently. From idea-stage startups to established companies, Allcancode transforms ideas into marketable products by providing a dedicated tech team, tools, and methodology to accelerate the development process. The platform offers services such as discovery and design, development, delivery, and evolution phases, ensuring that the product development journey is smooth and transparent. With a focus on speed, quality, and flexibility, Allcancode empowers users to access their source code, stay on budget, and launch successful products.

Ranked is an affordable SEO service that offers white label solutions for businesses and agencies. They provide human-written blog content, managed optimization, genuine backlinks, and leading SEO software. Their services are fully managed and structured for intent and engagement. Ranked utilizes AI engines for analysis, research, and outreach to deliver data-driven work and improve in-house productivity. However, they do not use AI for writing content due to inconsistent indexing on Google.

Retorio is a cutting-edge Behavioral Intelligence (BI) Platform that fuses machine learning with scientific findings from psychology and organizational research to ultimately take learning and development to a new level within organizations. At the core of Retorio’s capabilities are its AI-powered immersive video simulations. Through these engaging role-plays, learners using Retorio get to train and develop the necessary skills through realistic scenarios. Furthermore, the personalized, on-demand feedback learners receive allows for immediate behavior change and performance improvement. Retorio’s training platform transcends the limitation of scalability and redefines how individuals and teams train and develop, bringing talent development to a new dimension.

Effy AI is a free performance management software designed for teams to conduct 360 feedback and performance reviews efficiently. The AI-powered platform offers ready-to-use templates, flexible reviewer nominations, and insightful AI-generated reports to help companies build a culture of high-performing teams. With features like automated response collection, Slack integration, and a vast question bank, Effy AI streamlines the review process and provides valuable insights for employee development.

Ongig is an AI-powered software that focuses on enhancing job postings for consistency, inclusivity, and efficiency. It offers solutions to common problems in job descriptions such as manual workflows, inconsistent postings, and bias. Ongig's features include a centralized job library, AI for talent acquisition, ATS integration, HRIS automation, and job description API. The application helps standardize job ads, improve readability, build a job library, remove gender-coded language, and provide API-driven insights for smarter hiring decisions.

Cornerstone is an AI-powered workforce agility platform that helps organizations close the workforce readiness gap by providing personalized experiences and deeper insights. It offers modern learning experiences and skills-forward, AI-powered HR technology. The platform ensures regulatory compliance, focuses on skills and talent-driven human capital management, and aims to build a diverse, equitable, and inclusive workplace. Cornerstone caters to various industries such as the public sector, financial services, healthcare, life sciences, manufacturing, higher education, and nonprofit organizations. It offers a range of resources, tools, and tips to empower people at work and prepare them for future trends in the workforce.

Pangea.ai is a leading talent aggregator that helps businesses hire quality technologists by comparing data points for reliable matching. It offers a unified hiring experience in a fragmented market, making it easier to compare and decide among the numerous software development agencies and talent networks available. Pangea.ai's intelligent matching system considers over 100 data points to find the best fit for businesses, while its rigorous vetting process evaluates expertise, client satisfaction, and team health. Businesses can choose to self-serve their way to a hire or opt for Pangea.ai's white-glove matching service.

Talentpair is an AI-powered hiring platform that aims to revolutionize the recruitment process by leveraging artificial intelligence to match candidates with jobs in minutes. Founded in 2014 and launched in 2020, Talentpair has a network of over 1 million connections and a pool of more than 80,000 active candidates. The platform combines AI technology with professional Growth Partners to help candidates get hired faster and supports hiring at the highest level for tech companies to scale, build, and flourish. Talentpair also integrates blockchain technology for smart contract payouts and decentralized triggers.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.

MyScaleDB is a SQL vector database designed for scalable AI applications, enabling developers to efficiently manage and process massive volumes of data using familiar SQL. It offers fast and efficient vector search, filtered search, and SQL-vector join queries. MyScaleDB is fully SQL-compatible and production-ready for AI applications, providing unmatched performance and scalability through cutting-edge OLAP architecture and advanced vector algorithms. Built on top of ClickHouse, it combines structured and vectorized data management for high accuracy and speed in filtered searches.

Commonplace Bot is a modern representation of the commonplace book, leveraging modern technological advancements in computation, data storage, machine learning, and networking. It aims to capture, engage, and share knowledge by providing a platform for users to collect ideas, quotes, and information, organize them efficiently, engage with the data through various strategies and triggers, and transform the data into new mediums for sharing. The tool utilizes embeddings and cached transformations for efficient data storage and retrieval, flips traditional engagement rules by engaging with the user, and enables users to alchemize raw data into new forms like art prompts. Commonplace Bot offers a unique approach to knowledge management and creative expression.

The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.

WritingAIPaper is a comprehensive guide for beginners on crafting AI conference papers. It covers topics like paper structure, core ideas, framework construction, result analysis, and introduction writing. The guide aims to help novices navigate the complexities of academic writing and contribute to the field with clarity and confidence. It also provides tips on readability improvement, logical strength, defensibility, confusion time reduction, and information density increase. The appendix includes sections on AI paper production, a checklist for final hours, common negative review comments, and advice on dealing with paper rejection.

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

VedAstro is an open-source Vedic astrology tool that provides accurate astrological predictions and data. It offers a user-friendly website, a chat API, an open API, a JavaScript SDK, a Swiss Ephemeris API, and a machine learning table generator. VedAstro is free to use and is constantly being updated with new features and improvements.

The Generative AI Use Cases Repository showcases a wide range of applications in generative AI, including Retrieval-Augmented Generation (RAG), AI Agents, and industry-specific use cases. It provides practical notebooks and guidance on utilizing frameworks such as LlamaIndex and LangChain, and demonstrates how to integrate models from leading AI research companies like Anthropic and OpenAI.

Colossal-AI is a deep learning system for large-scale parallel training. It provides a unified interface to scale sequential code of model training to distributed environments. Colossal-AI supports parallel training methods such as data, pipeline, tensor, and sequence parallelism and is integrated with heterogeneous training and zero redundancy optimizer.

Godot LLM is a plugin that enables the utilization of large language models (LLM) for generating content in games. It provides functionality for text generation, text embedding, multimodal text generation, and vector database management within the Godot game engine. The plugin supports features like Retrieval Augmented Generation (RAG) and integrates llama.cpp-based functionalities for text generation, embedding, and multimodal capabilities. It offers support for various platforms and allows users to experiment with LLM models in their game development projects.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

This repository aims to build a low-parameter LLM model through pretraining, fine-tuning, model rewarding, and reinforcement learning stages to create a chat model capable of simple conversation tasks. It features using the bert4torch training framework, seamless integration with transformers package for inference, optimized file reading during training to reduce memory usage, providing complete training logs for reproducibility, and the ability to customize robot attributes. The chat model supports multi-turn conversations. The trained model currently only supports basic chat functionality due to limitations in corpus size, model scale, SFT corpus size, and quality.

This repository provides guidance on building a multi-tenant SaaS solution for accessing foundation models using Amazon Bedrock and Amazon SageMaker. It helps enterprise IT teams track usage and costs of foundation models, regulate access, and provide visibility to cost centers. The solution includes an API Gateway design pattern for standardization and governance, enabling loose coupling between model consumers and endpoint services. The CDK Stack deploys resources for private networking, API Gateway, Lambda functions, DynamoDB table, EventBridge, S3 buckets, and Cloudwatch logs.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

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