Best AI tools for< Monitor Data Quality >

Lightup is a cloud data quality monitoring tool with AI-powered anomaly detection, incident alerts, and data remediation capabilities for modern enterprise data stacks. It specializes in helping large organizations implement successful and sustainable data quality programs quickly and easily. Lightup's pushdown architecture allows for monitoring data content at massive scale without moving or copying data, providing extreme scalability and optimal automation. The tool empowers business users with democratized data quality checks and enables automatic fixing of bad data at enterprise scale.

Evidently AI is an open-source machine learning (ML) monitoring and observability platform that helps data scientists and ML engineers evaluate, test, and monitor ML models from validation to production. It provides a centralized hub for ML in production, including data quality monitoring, data drift monitoring, ML model performance monitoring, and NLP and LLM monitoring. Evidently AI's features include customizable reports, structured checks for data and models, and a Python library for ML monitoring. It is designed to be easy to use, with a simple setup process and a user-friendly interface. Evidently AI is used by over 2,500 data scientists and ML engineers worldwide, and it has been featured in publications such as Forbes, VentureBeat, and TechCrunch.

SE Ranking is a robust SEO platform that offers a comprehensive suite of tools for agencies, enterprises, SMBs, and entrepreneurs. It provides features such as Rank Tracker, On-Page SEO Checker, Website Audit, Competitor Analysis Tool, and Backlink Checker. SE Ranking is trusted by users worldwide and offers a range of resources including educational content, webinars, and an Agency Hub. The platform also includes an AI Writer for content creation and optimization. With a focus on data quality and user satisfaction, SE Ranking aims to help users improve their SEO performance and online visibility.

MagicLoop is a voice survey tool designed to enhance customer feedback by replacing written feedback with spoken responses. It allows users to gather higher-quality responses through voice surveys, capturing emotions, tones, and nuances for a deeper understanding of participants' feelings and intentions. The tool aims to improve participant engagement and provide detailed insights by encouraging genuine responses. MagicLoop offers a modern approach to surveys, addressing the limitations of traditional methods and providing tailored solutions for various use cases such as user research, satisfaction surveys, NPS, feedback collection, market research, and data monitoring. With features like AI analysis, speech-to-text transcription, and custom branding, MagicLoop streamlines the process of generating insights from voice recordings.

Scale AI is an AI tool that accelerates the development of AI applications for various sectors including enterprise, government, and automotive industries. It offers solutions for training models, fine-tuning, generative AI, and model evaluations. Scale Data Engine and GenAI Platform enable users to leverage enterprise data effectively. The platform collaborates with leading AI models and provides high-quality data for public and private sector applications.

Appen is a leading provider of high-quality data for training AI models. The company's end-to-end platform, flexible services, and deep expertise ensure the delivery of high-quality, diverse data that is crucial for building foundation models and enterprise-ready AI applications. Appen has been providing high-quality datasets that power the world's leading AI models for decades. The company's services enable it to prepare data at scale, meeting the demands of even the most ambitious AI projects. Appen also provides enterprises with software to collect, curate, fine-tune, and monitor traditionally human-driven tasks, creating massive efficiencies through a trustworthy, traceable process.

Innodata Inc. is a global data engineering company that delivers AI-enabled software platforms and managed services for AI data collection/annotation, AI digital transformation, and industry-specific business processes. They provide a full-suite of services and products to power data-centric AI initiatives using artificial intelligence and human expertise. With a 30+ year legacy, they offer the highest quality data and outstanding service to their customers.

Macgence is an AI training data services platform that offers high-quality off-the-shelf structured training data for organizations to build effective AI systems at scale. They provide services such as custom data sourcing, data annotation, data validation, content moderation, and localization. Macgence combines global linguistic, cultural, and technological expertise to create high-quality datasets for AI models, enabling faster time-to-market across the entire model value chain. With more than 5 years of experience, they support and scale AI initiatives of leading global innovators by designing custom data collection programs. Macgence specializes in handling AI training data for text, speech, image, and video data, offering cognitive annotation services to unlock the potential of unstructured textual data.

LangWatch is a monitoring and analytics tool for Generative AI (GenAI) solutions. It provides detailed evaluations of the faithfulness and relevancy of GenAI responses, coupled with user feedback insights. LangWatch is designed for both technical and non-technical users to collaborate and comment on improvements. With LangWatch, you can understand your users, detect issues, and improve your GenAI products.

Pezzo is an open-source platform that enables developers to build, test, monitor, and ship AI features quickly and efficiently. It provides a range of powerful features to streamline the workflow, including prompt management, observability, troubleshooting, and collaboration tools. With Pezzo, teams can deliver impactful AI features in sync and optimize for cost and performance.

BigPanda is an AI-powered ITOps platform that helps teams gain efficiency, improve service quality, and reduce costs. It provides automated detection and alert intelligence, automated investigation and incident intelligence, automated remediation and workflow automation, and unified analytics and ready-to-use dashboards.

Medallia is an AI-powered text analytics software that enables users to uncover high-impact insights and drive actions with real-time, human-centric text analytics. It offers comprehensive feedback capture, role-based reporting, AI & analytics, integrations, and enterprise-grade security. The platform helps organizations analyze unstructured data, derive hidden meanings behind words, create customizable KPIs, and build out-of-the-box topic models for various industries and use cases.

Databricks is a data and AI company that offers a Data Intelligence Platform to help users succeed with AI by developing generative AI applications, democratizing insights, and driving down costs. The platform maintains data lineage, quality, control, and privacy across the entire AI workflow, enabling users to create, tune, and deploy generative AI models. Databricks caters to industry leaders, providing tools and integrations to speed up success in data and AI. The company offers resources such as support, training, and community engagement to help users succeed in their data and AI journey.

Codacy is an AI-powered code quality and security platform designed for developers to efficiently optimize and secure their code. It offers a unified set of AppSec tools, data-driven insights, and seamless integrations across the software development lifecycle. Codacy helps teams monitor and resolve security issues at scale, improve code quality, and prevent breaking changes. With AI suggested fixes and effortless code quality monitoring, Codacy is a valuable tool for businesses and developers alike.

LatenceTech is a tech startup that specializes in network latency monitoring and analysis. The platform offers real-time monitoring, prediction, and in-depth analysis of network latency using AI software. It provides cloud-based network analytics, versatile network applications, and data science-driven network acceleration. LatenceTech focuses on customer satisfaction by providing full customer experience service and expert support. The platform helps businesses optimize network performance, minimize latency issues, and achieve faster network speed and better connectivity.

Inductor is a developer tool for evaluating, ensuring, and improving the quality of your LLM applications – both during development and in production. It provides a fantastic workflow for continuous testing and evaluation as you develop, so that you always know your LLM app’s quality. Systematically improve quality and cost-effectiveness by actionably understanding your LLM app’s behavior and quickly testing different app variants. Rigorously assess your LLM app’s behavior before you deploy, in order to ensure quality and cost-effectiveness when you’re live. Easily monitor your live traffic: detect and resolve issues, analyze usage in order to improve, and seamlessly feed back into your development process. Inductor makes it easy for engineering and other roles to collaborate: get critical human feedback from non-engineering stakeholders (e.g., PM, UX, or subject matter experts) to ensure that your LLM app is user-ready.

Covera Health is a clinical intelligence platform that supports the end-to-end delivery of clinical-grade, AI-powered quality insights for providers and insurers. The platform is seamlessly integrated across the healthcare ecosystem to elevate everything from diagnosis and care coordination to prior authorization and claims administration. Covera Health is certified by AHRQ as a Patient Safety Organization to safeguard access to provider and patient data.

AutoRadiant is an AI-powered audio monitoring tool designed for businesses to enhance customer experience and optimize operations. It provides real-time audio transcription and insightful analytics, enabling efficient business operations accessible anytime and anywhere. With features like AI noise reduction, daily transcription summaries, and instant alerts, AutoRadiant helps businesses focus on meaningful customer interactions, turn conversations into actionable insights, and make data-driven decisions. The tool ensures top-notch security measures, strict privacy protocols, and full legal compliance to protect business and customer data.

BenchLLM is an AI tool designed for AI engineers to evaluate LLM-powered apps by running and evaluating models with a powerful CLI. It allows users to build test suites, choose evaluation strategies, and generate quality reports. The tool supports OpenAI, Langchain, and other APIs out of the box, offering automation, visualization of reports, and monitoring of model performance.

Grain Warehouse AI is an innovative AI tool designed to optimize grain storage management. The application utilizes advanced algorithms and machine learning techniques to analyze grain storage data, predict optimal storage conditions, and recommend inventory management strategies. With Grain Warehouse AI, users can efficiently monitor grain quality, prevent spoilage, and maximize storage capacity. The tool provides real-time insights and actionable recommendations to help grain warehouse operators streamline operations and improve overall efficiency.

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.

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.

The 'airflow-provider-great-expectations' repository contains a set of Airflow operators for Great Expectations, a Python library used for testing and validating data. The operators enable users to run Great Expectations validations and checks within Apache Airflow workflows. The package requires Airflow 2.1.0+ and Great Expectations >=v0.13.9. It provides functionalities to work with Great Expectations V3 Batch Request API, Checkpoints, and allows passing kwargs to Checkpoints at runtime. The repository includes modules for a base operator and examples of DAGs with sample tasks demonstrating the operator's functionality.

Cleanlab helps you **clean** data and **lab** els by automatically detecting issues in a ML dataset. To facilitate **machine learning with messy, real-world data** , this data-centric AI package uses your _existing_ models to estimate dataset problems that can be fixed to train even _better_ models.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

MME-RealWorld is a benchmark designed to address real-world applications with practical relevance, featuring 13,366 high-resolution images and 29,429 annotations across 43 tasks. It aims to provide substantial recognition challenges and overcome common barriers in existing Multimodal Large Language Model benchmarks, such as small data scale, restricted data quality, and insufficient task difficulty. The dataset offers advantages in data scale, data quality, task difficulty, and real-world utility compared to existing benchmarks. It also includes a Chinese version with additional images and QA pairs focused on Chinese scenarios.

Speechless.AI is committed to integrating the superior language processing and deep reasoning capabilities of large language models into practical business applications. By enhancing the model's language understanding, knowledge accumulation, and text creation abilities, and introducing long-term memory, external tool integration, and local deployment, our aim is to establish an intelligent collaborative partner that can independently interact, continuously evolve, and closely align with various business scenarios.

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.

Tonic Validate is a framework for the evaluation of LLM outputs, such as Retrieval Augmented Generation (RAG) pipelines. Validate makes it easy to evaluate, track, and monitor your LLM and RAG applications. Validate allows you to evaluate your LLM outputs through the use of our provided metrics which measure everything from answer correctness to LLM hallucination. Additionally, Validate has an optional UI to visualize your evaluation results for easy tracking and monitoring.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

LabelLLM is an open-source data annotation platform designed to optimize the data annotation process for LLM development. It offers flexible configuration, multimodal data support, comprehensive task management, and AI-assisted annotation. Users can access a suite of annotation tools, enjoy a user-friendly experience, and enhance efficiency. The platform allows real-time monitoring of annotation progress and quality control, ensuring data integrity and timeliness.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

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.

LangCheck is a Python library that provides a suite of metrics and tools for evaluating the quality of text generated by large language models (LLMs). It includes metrics for evaluating text fluency, sentiment, toxicity, factual consistency, and more. LangCheck also provides tools for visualizing metrics, augmenting data, and writing unit tests for LLM applications. With LangCheck, you can quickly and easily assess the quality of LLM-generated text and identify areas for improvement.

Awesome-Lists is a curated index of selected resources spanning various fields including programming languages and theories, web and frontend development, server-side development and infrastructure, cloud computing and big data, data science and artificial intelligence, product design, etc. It includes articles, books, courses, examples, open-source projects, and more. The repository categorizes resources according to the knowledge system of different domains, aiming to provide valuable and concise material indexes for readers. Users can explore and learn from a wide range of high-quality resources in a systematic way.

A specialist in DataOps and Data Observability, aiding in data management and monitoring.

I will create a quality data set for a personality AI, just dive into each module by saying the name of it and do so for all the modules. If you find it useful, share it to your friends

Comprehensive AI for global air quality solutions.

Specializes in providing Homebrew metadata and analytics on casks and formulae.

Guides project success through comprehensive performance monitoring.

Ensures software performance meets organizational standards and expectations.

Scientific expert on humidity, providing detailed and informative guidance.

Travel and Hospitality Industry. Hotels, Airlines, and Travel Agencies collect personal information like travel histories, passport details, and payment information, necessitating robust privacy and security measures.

Advises companies on data privacy laws, performs compliance checks, and implements data protection strategies.

Mon expert en protection des données

Compose BigQuery SQL queries for GA4 and Google Search Console.

Seismic and volcanic monitor with in-depth data and visuals.

Stay informed on AGI - with the latest, most relevant news.

Real-time Ethereum Blockchain Data & Insights (with Etherscan.io)

I analyze your workout data, focusing on brevity and clear visualizations

Frost Protection System is an AI bot optimizing open field farming of fruits, vegetables, and flowers, combining real-time data and AI to boost yield, cut costs, and foster sustainable practices in a user-friendly interface.

Explains data breaches, reasons, impacts, and identifies criminal groups.

Data and Market analysis

BNB data analyzer and predictor for PancakeSwap

Analyzes GSC data and highlights the impact of search updates.