Best AI tools for< Create Dashboards >

Streamlit is a web application framework that allows users to create interactive web applications effortlessly using Python. It enables data scientists and developers to build and deploy data-driven applications quickly and easily. With Streamlit, users can create interactive visualizations, dashboards, and machine learning models without the need for extensive web development knowledge. The platform provides a simple and intuitive way to turn data scripts into shareable web apps, making it ideal for prototyping, showcasing projects, and sharing insights with others.

Streamlit is a web application framework that allows data scientists and machine learning engineers to create interactive web applications quickly and easily. It simplifies the process of building and sharing data-focused applications by providing a simple Python script that can be turned into a shareable web app with just a few lines of code. With Streamlit, users can create interactive visualizations, dashboards, and machine learning models without the need for web development expertise.

Veezoo is a self-service analytics platform that uses AI and a semantic layer to make data accessible and understandable to everyone in an organization. It allows users to ask questions about their data in plain English and get instant insights. Veezoo also provides features such as dashboards, collaboration tools, and data governance to help businesses make better use of their data.

NLSQL is a B2B SaaS tool that empowers employees with an intuitive text interface to inform and speed up business decisions with significant benefits for enterprises. It works as the first NLP to SQL API, which doesn't require any sensitive or confidential data transfer outside the corporate IT ecosystem. NLSQL supports integrations to all main database types and corporate messengers, which helps drive businesses forward faster with data-driven business decisions.

Fluent is an AI-powered data analytics platform that helps businesses explore their data and uncover insights. It uses natural language processing to understand user questions and generate SQL queries to retrieve data from a variety of sources. Fluent also provides visualizations and dashboards to help users understand their data and make informed decisions.

Qubinets is a cloud data environment solutions platform that provides building blocks for building big data, AI, web, and mobile environments. It is an open-source, no lock-in, secured, and private platform that can be used on any cloud, including AWS, Digital Ocean, Google Cloud, and Microsoft Azure. Qubinets makes it easy to plan, build, and run data environments, and it streamlines and saves time and money by reducing the grunt work in setup and provisioning.

Onvo AI is an embedded data visualization platform that allows users to create interactive dashboards and data visualizations using simple AI prompts. It connects to various data sources, enabling users to build insightful charts and visualizations without the need for complex queries or manual data manipulation. Onvo AI offers customization options, allowing users to match their brand's identity and provides secure sharing and embedding features. It also includes analytics capabilities, enabling users to track dashboard usage and user engagement.

Propellor is a data analytics platform that helps businesses unify and activate their data. It offers a variety of features, including dashboards, templates, data apps, and connectors. Propellor is designed to be easy to use, even for non-technical users. It can be used to analyze data from a variety of sources, including webstores, marketing apps, social media, and CRM systems. Propellor can help businesses improve their decision-making, identify growth opportunities, and prove the impact of their marketing campaigns.

Luzmo is a customer-facing analytics platform for SaaS companies. It provides embedded analytics, embedded dashboard editor, and Luzmo AI to help businesses make better decisions with data. Luzmo is easy to use, scalable, and affordable, making it a great choice for businesses of all sizes.

Streamlit is an open-source Python library that makes it easy to create and share beautiful and interactive web apps for data science and machine learning.

Supertype is a full-cycle data science consultancy offering a range of services including computer vision, custom BI development, managed data analytics, programmatic report generation, and more. They specialize in providing tailored solutions for data analytics, business intelligence, and data engineering services. Supertype also offers services for developing custom web dashboards, computer vision research and development, PDF generation, managed analytics services, and LLM development. Their expertise extends to implementing data science in various industries such as e-commerce, mobile apps & games, and financial markets. Additionally, Supertype provides bespoke solutions for enterprises, advisory and consulting services, and an incubator platform for data scientists and engineers to work on real-world projects.

Digital Analyst Team is an AI-powered digital media automation platform that offers a suite of services for digital agencies. The platform provides automation solutions for various digital media operations, including paid search, SEO, social media, website development, campaign management, workflow automation, marketing automation, analytics, and dashboards. With a focus on AI and machine learning capabilities, Digital Analyst Team aims to streamline and optimize digital media campaigns for agencies, allowing them to focus on strategic growth and client satisfaction. The platform also offers custom software development services and resources such as blogs, case studies, and contact information.

Deepnote is an AI-powered analytics and data science notebook platform designed for teams. It allows users to turn notebooks into powerful data apps and dashboards, combining Python, SQL, R, or even working without writing code at all. With Deepnote, users can query various data sources, generate code, explain code, and create interactive visualizations effortlessly. The platform offers features like collaborative workspaces, scheduling notebooks, deploying APIs, and integrating with popular data warehouses and databases. Deepnote prioritizes security and compliance, providing users with control over data access and encryption. It is loved by a community of data professionals and widely used in universities and by data analysts and scientists.

DataBrain is an AI-powered embedded analytics platform that enables product teams to create and share beautiful dashboards with customers, vendors, and partners. It helps generate insights to drive business outcomes by providing self-serve analytics capabilities, reducing ad-hoc reporting requests, and enabling easy access and sharing of insights across various platforms. With features like modular SDK, white-labeled dashboards, and enterprise security, DataBrain offers a comprehensive solution for crafting end-user analytics experiences. The platform prioritizes data security, offering end-to-end encryption and compliance with industry standards like SOC 2 and ISO 27001.

The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.

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BionicGPT is an on-premise replacement for ChatGPT, offering the advantages of Generative AI while maintaining strict data confidentiality. BionicGPT can run on your laptop or scale into the data center.

Preswald is a full-stack platform for building, deploying, and managing interactive data applications in Python. It simplifies the process by combining ingestion, storage, transformation, and visualization into one lightweight SDK. With Preswald, users can connect to various data sources, customize app themes, and easily deploy apps locally. The platform focuses on code-first simplicity, end-to-end coverage, and efficiency by design, making it suitable for prototyping internal tools or deploying production-grade apps with reduced complexity and cost.

ChatOpsLLM is a project designed to empower chatbots with effortless DevOps capabilities. It provides an intuitive interface and streamlined workflows for managing and scaling language models. The project incorporates robust MLOps practices, including CI/CD pipelines with Jenkins and Ansible, monitoring with Prometheus and Grafana, and centralized logging with the ELK stack. Developers can find detailed documentation and instructions on the project's website.

AzureOpenAI-with-APIM is a repository that provides a one-button deploy solution for Azure API Management (APIM), Key Vault, and Log Analytics to work seamlessly with Azure OpenAI endpoints. It enables organizations to scale and manage their Azure OpenAI service efficiently by issuing subscription keys via APIM, delivering usage metrics, and implementing policies for access control and cost management. The repository offers detailed guidance on implementing APIM to enhance Azure OpenAI resiliency, scalability, performance, monitoring, and chargeback capabilities.

Nile is a serverless Postgres database designed for modern SaaS applications. It virtualizes tenants/customers/organizations into Postgres to enable native tenant data isolation, performance isolation, per-tenant backups, and tenant placement on shared or dedicated compute globally. With Nile, you can manage multiple tenants effortlessly, without complex permissions or buggy scripts. Additionally, it offers opt-in user management capabilities, customer-specific vector embeddings, and instant tenant admin dashboards. Built for the cloud, Nile provides a true serverless experience with effortless scaling.

Cube is a semantic layer for building data applications, helping data engineers and application developers access data from modern data stores, organize it into consistent definitions, and deliver it to every application. It works with SQL-enabled data sources, providing sub-second latency and high concurrency for API requests. Cube addresses SQL code organization, performance, and access control issues in data applications, enabling efficient data modeling, access control, and performance optimizations for various tools like embedded analytics, dashboarding, reporting, and data notebooks.

ClearML Serving is a command line utility for model deployment and orchestration, enabling model deployment including serving and preprocessing code to a Kubernetes cluster or custom container based solution. It supports machine learning models like Scikit Learn, XGBoost, LightGBM, and deep learning models like TensorFlow, PyTorch, ONNX. It provides a customizable RestAPI for serving, online model deployment, scalable solutions, multi-model per container, automatic deployment, canary A/B deployment, model monitoring, usage metric reporting, metric dashboard, and model performance metrics. ClearML Serving is modular, scalable, flexible, customizable, and open source.

This repository contains a simple blog application built using Python and Flask framework. It allows users to create, read, update, and delete blog posts. The application uses SQLite database for storing blog data and provides a basic user interface for interacting with the blog. The code is well-organized and easy to understand, making it suitable for beginners looking to learn web development with Python and Flask.

Buster is a modern analytics platform designed with AI in mind, focusing on self-serve experiences powered by Large Language Models. It addresses pain points in existing tools by advocating for AI-centric app development, cost-effective data warehousing, improved CI/CD processes, and empowering data teams to create powerful, user-friendly data experiences. The platform aims to revolutionize AI analytics by enabling data teams to build deep integrations and own their entire analytics stack.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

Mito is a set of Jupyter extensions designed to help users write Python code faster. It consists of Mito AI, providing tools like context-aware AI Chat and error debugging; Mito Spreadsheet, enabling data exploration with interactive spreadsheet features; and Mito for Streamlit and Dash, allowing easy integration of spreadsheets into dashboards with minimal code. Mito is open source and community-driven, with options to purchase Mito Pro for further development support.

CIA is a powerful open-source tool designed for data analysis and visualization. It provides a user-friendly interface for processing large datasets and generating insightful reports. With CIA, users can easily explore data, perform statistical analysis, and create interactive visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, CIA offers a comprehensive set of features to streamline your data analysis workflow and uncover valuable insights.

Azure OpenAI Service is a central capability with Azure API Management, providing guidance and tools for organizations to implement Azure OpenAI in a production environment with an emphasis on cost control, secure access, and usage monitoring. It includes infrastructure-as-code templates, CI/CD pipelines, secure access management, usage monitoring, load balancing, streaming requests, and end-to-end samples like ChatApp and Azure Dashboards.

Middleware is an open-source engineering management tool that helps engineering leaders measure and analyze team effectiveness using DORA metrics. It integrates with CI/CD tools, automates DORA metric collection and analysis, visualizes key performance indicators, provides customizable reports and dashboards, and integrates with project management platforms. Users can set up Middleware using Docker or manually, generate encryption keys, set up backend and web servers, and access the application to view DORA metrics. The tool calculates DORA metrics using GitHub data, including Deployment Frequency, Lead Time for Changes, Mean Time to Restore, and Change Failure Rate. Middleware aims to provide DORA metrics to users based on their Git data, simplifying the process of tracking software delivery performance and operational efficiency.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

Laminar is an all-in-one open-source platform designed for engineering AI products. It allows users to trace, evaluate, label, and analyze LLM data efficiently. The platform offers features such as automatic tracing of common AI frameworks and SDKs, local and online evaluations, simple UI for data labeling, dataset management, and scalability with gRPC communication. Laminar is built with a modern open-source stack including RabbitMQ, Postgres, Clickhouse, and Qdrant for semantic similarity search. It provides fast and beautiful dashboards for traces, evaluations, and labels, making it a comprehensive tool for AI product development.

Langfuse is a powerful tool that helps you develop, monitor, and test your LLM applications. With Langfuse, you can: * **Develop:** Instrument your app and start ingesting traces to Langfuse, inspect and debug complex logs, and manage, version, and deploy prompts from within Langfuse. * **Monitor:** Track metrics (cost, latency, quality) and gain insights from dashboards & data exports, collect and calculate scores for your LLM completions, run model-based evaluations, collect user feedback, and manually score observations in Langfuse. * **Test:** Track and test app behaviour before deploying a new version, test expected in and output pairs and benchmark performance before deploying, and track versions and releases in your application. Langfuse is easy to get started with and offers a generous free tier. You can sign up for Langfuse Cloud or deploy Langfuse locally or on your own infrastructure. Langfuse also offers a variety of integrations to make it easy to connect to your LLM applications.

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