Best AI tools for< Track Data Changes >

Bemi is an Automatic Audit Trail tool designed for PostgreSQL databases. It allows users to track data changes reliably without the need for complex engineering or costly infrastructure. Bemi offers seamless setup, contextualized data integration, default security measures, and storage in PostgreSQL databases. It is trusted by top tech companies and provides features for reliable and contextualized data tracking, audit & compliance, data recovery, observability & troubleshooting, and building activity feed. Bemi ensures data security, customer-level isolation, and integrates with ORM for easy data enrichment. The tool is loved by many users and has received positive testimonials for its efficiency and effectiveness in data tracking and audit trail management.

TruePrep is an AI software designed for tax accounting firms and CPAs to streamline tax planning, projections, and research processes. The AI Assistant within TruePrep helps accountants and financial advisors to quickly identify clients affected by tax changes, create tax projections, and answer complex tax questions in real time. By leveraging AI technology, TruePrep aims to save time, increase accuracy, and improve revenue generation for tax professionals.

Satlas is an AI-powered platform that provides geospatial data generated by AI models. The platform showcases how our planet is changing by revealing insights into marine infrastructure, renewable energy infrastructure, and tree cover. Satlas employs state-of-the-art AI architectures and training algorithms in computer vision to enhance low-resolution satellite imagery and produce high-resolution images on a global scale. The AI-generated geospatial datasets are freely available for offline analysis, along with AI models and training labels. The platform is developed and maintained by PRIOR and colleagues at the Allen Institute for AI, aiming to advance computer vision and create AI systems that understand and reason about the world.

Hexowatch is an AI-powered website monitoring and archiving tool that helps businesses track changes to any website, including visual, content, source code, technology, availability, or price changes. It provides detailed change reports, archives snapshots of pages, and offers side-by-side comparisons and diff reports to highlight changes. Hexowatch also allows users to access monitored data fields as a downloadable CSV file, Google Sheet, RSS feed, or sync any update via Zapier to over 2000 different applications.

Deep Planet is a precision viticulture platform powered by AI that focuses on enhancing sustainability in agriculture. It offers solutions for the wine industry, landowners, farmers, and supply chain companies by providing data-driven insights to maximize potential, optimize nutrient application, and support the transition to achieve net zero targets. The platform leverages AI and satellite imagery to empower users with actionable intelligence for better decision-making in vineyard management and soil health.

Boomerang is an AI-powered sales pipeline tool that helps businesses turn happy customers into revenue opportunities by tracking job changes, automating follow-ups, and generating warm intros. It offers features such as contact tracking, account tracking, warm intros, auto org charts, and CRM data quality. Boomerang outperforms competitors in pipeline conversion and job change tracking speed. The tool is designed to boost revenue growth, increase repeat buyers, and enhance customer engagement through personalized interactions.

Frame AI is a premier Streaming AI Platform powered by STAG, designed to provide proactive insights and tools for every team by continuously querying customer data to detect traits, track trends, and trigger workflows. The platform turns unstructured data into actionable insights, helping teams stay ahead of risks and opportunities. Frame AI's architecture autonomously queries customer data based on user objectives, activating inside existing business tools to provide real-time customer data. With features like enrichments, triggers, alerts, and insights, Frame AI enables better decisions faster by combining predictive signals in customer text into task-specific scores. The platform is suitable for marketing, CX, support, and product teams, offering real-time usability feedback, demographic and psychographic trait detection, and secure data handling. Frame AI is SOC 2 Type II certified and HIPAA compliant, with a team of AI experts leading the development of AI solutions for various organizations.

Loops is an AI tool that empowers data analysts and product managers to make informed decisions based on deep, accurate causal insights. It leverages proprietary causal inference models to identify opportunities for maximizing key performance indicators (KPIs) without the need for traditional A/B testing. By analyzing user behaviors and business metrics, Loops helps companies prioritize efforts efficiently and proactively review impactful opportunities. The tool simplifies the process of understanding causality, providing actionable insights for product teams to drive growth and increase KPIs.

Lushair is an AI-powered platform that offers personalized hair and scalp analysis solutions. It aims to create a digital and intelligent ecosystem for dermatology, providing accurate skin and scalp solutions that are accessible and affordable. Lushair offers services such as personal subscriptions, skin & scalp analysis SAAS, and skin & scalp analysis API for hair care specialists and brands. The platform features historical tracking, multi-node analysis, improved management, AI-generated hair care plans, and an easy-to-use interface. Lushair has received positive feedback for its standardization, customization, and intelligent services in the field of dermatology.

Policy-Insider.AI is an AI-powered web application that revolutionizes public policy monitoring and analysis. It offers real-time, multilingual, and multinational insights by leveraging advanced AI technology. Users can access comprehensive policy documents and analysis in multiple languages, receive instant alerts on policy changes, and gain a global perspective with data from numerous countries and international institutions. The application provides tailored solutions for policy development, advocacy progress measurement, and stakeholder engagement, enhancing public affairs strategies and decision-making processes.

Weekly Github Insights is an AI-powered platform that provides users with a comprehensive summary of their latest GitHub activities from the past 7 days. It aims to keep users informed and motivated by compiling their weekly GitHub journey. The platform is built by @rohan_2502 using @aceternitylabs, @github APIs, and @OpenAI.

CanIRank is an AI-powered SEO software designed for small businesses and startups to improve their Google rankings. It provides specific action recommendations based on AI analysis, offers DIY instructions or the option to delegate to an SEO consultant. CanIRank helps users understand why pages rank where they do, delivers results by suggesting impactful changes, and keeps users informed about new content ideas and ranking changes. The software automates keyword research, provides insights on competitive keywords, and offers a Keyword ROI Score to find the best balance between ranking difficulty and keyword value. CanIRank also offers SERP analysis, rank tracking, and competitive analysis tools to help users optimize their SEO strategies.

New Relic is an AI monitoring platform that offers an all-in-one observability solution for monitoring, debugging, and improving the entire technology stack. With over 30 capabilities and 750+ integrations, New Relic provides the power of AI to help users gain insights and optimize performance across various aspects of their infrastructure, applications, and digital experiences.

Kanlet is an AI-powered tool designed to simplify pipeline generation for sales and marketing teams. It helps users identify warm leads by tracking key contacts, such as buyers, champions, and end-users, as they change jobs. The tool aims to provide users with an unfair advantage in prospecting by surfacing relationship triggers and automating outreach through personalization using Generative AI. Kanlet also offers a relationship-driven pipeline generation strategy, prioritizing high-intent accounts and boosting outbound conversions with former customers. Additionally, it assists in keeping CRM data accurate and clean by flagging departed contacts and updating missing buyer personas.

Persana AI is an AI-powered prospecting tool that helps users find, enrich, and personalize outbound leads using over 75 data sources and AI signals. It enables users to build hyper-relevant and targeted lead lists, automate workflows with a powerful AI agent, create personalized messaging, and stay up to date with AI triggers. The platform offers real-time data enrichment, job change tracking, and technographics to boost sales processes and generate a higher pipeline. Trusted by teams and businesses of all sizes, Persana AI revolutionizes sales prospecting workflows with its AI-driven insights and automation capabilities.

Trudo.ai is an AI-powered workflow automation platform that allows users to build complex workflows using simple English language commands. The platform is backed by Python code and features interactive UI components. Users can create and customize nodes, handle dynamic routing, and benefit from flexible memory allocation. Trudo.ai also offers AI Copilot functionality for non-technical users to generate logic and user interfaces. With support for various data types and no extra frameworks required, Trudo.ai covers a wide range of use cases and provides versions to track workflow changes.

Government Technology provides email newsletters that deliver the latest news and updates on various topics relevant to government leaders, including technology trends, artificial intelligence, cybersecurity, digital communities, emergency management, government business, higher education, and K-12 education. These newsletters aim to keep subscribers informed about critical developments and best practices in their respective fields.

Getactyv is an AI and computer vision assisted health and fitness platform that helps users track their progress, set goals, and stay motivated. The platform uses AI to analyze user data and provide personalized recommendations for workouts, nutrition, and lifestyle changes. Getactyv also offers a community forum where users can connect with others and share their experiences.

PEAR Health Labs is an AI-powered adaptive digital coaching software that offers hyperpersonalized coaching solutions to help individuals move smarter, get healthier, and live happier. The platform utilizes AI technology and physiological science to create personalized fitness experiences based on wearables and biometric feedback. PEAR Training Intelligence aims to change the landscape of preventative care by identifying health issues before they become problems. The software is cost-effective, scalable, and provides guidance on physical activity to improve overall health outcomes.

Edgy Labs is an enterprise AI-enabled SEO platform that focuses on helping brands maintain peak performance in SEO through AI-driven innovations. The platform offers comprehensive solutions for search engine optimization, utilizing AI technology to redefine enterprise SEO strategies and deliver outstanding results for clients. Edgy Labs is dedicated to continuous improvement, innovation, and passion for change, providing a forward-looking mindset and a positive attitude to elevate businesses to new heights.

DVC, or Data Version Control, is a command-line tool and VS Code extension that helps you develop reproducible machine learning projects. With DVC, you can version your data and models, iterate fast with lightweight pipelines, track experiments in your local Git repo, compare any data, code, parameters, model, or performance plots, and share experiments and automatically reproduce anyone's experiment.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

The 'ai-dev-2024-ml-workshop' repository contains materials for the Deploy and Monitor ML Pipelines workshop at the AI_dev 2024 conference in Paris, focusing on deployment designs of machine learning pipelines using open-source applications and free-tier tools. It demonstrates automating data refresh and forecasting using GitHub Actions and Docker, monitoring with MLflow and YData Profiling, and setting up a monitoring dashboard with Quarto doc on GitHub Pages.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

AirCasting is a platform for gathering, visualizing, and sharing environmental data. It aims to provide a central hub for environmental data, making it easier for people to access and use this information to make informed decisions about their environment.

Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. With Flyte, user teams can construct pipelines using the Python SDK, and seamlessly deploy them on both cloud and on-premises environments, enabling distributed processing and efficient resource utilization.

Smartcat is a CLI interface that brings language models into the Unix ecosystem, allowing power users to leverage the capabilities of LLMs in their daily workflows. It features a minimalist design, seamless integration with terminal and editor workflows, and customizable prompts for specific tasks. Smartcat currently supports OpenAI, Mistral AI, and Anthropic APIs, providing access to a range of language models. With its ability to manipulate file and text streams, integrate with editors, and offer configurable settings, Smartcat empowers users to automate tasks, enhance code quality, and explore creative possibilities.

LangGraph Expense tracker is a small project that explores the possibilities of LangGraph. It allows users to send pictures of invoices, which are then structured and categorized into expenses and stored in a database. The project includes functionalities for invoice extraction, database setup, and API configuration. It consists of various modules for categorizing expenses, creating database tables, and running the API. The database schema includes tables for categories, payment methods, and expenses, each with specific columns to track transaction details. The API documentation is available for reference, and the project utilizes LangChain for processing expense data.

ML Contests is a platform that provides a sortable list of public machine learning/data science/AI contests, viewable on mlcontests.com. Users can submit pull requests for any changes or additions to the competitions list by editing the competitions.json file on the GitHub repository. The platform requires mandatory fields such as competition name, URL, type of ML, deadline for submissions, prize information, platform running the competition, and sponsorship details. Optional fields include conference affiliation, conference year, competition launch date, registration deadline, additional URLs, and tags relevant to the challenge type. The platform is transitioning towards assigning multiple tags to competitions for better categorization and searchability.

The Missing Persons 2024 Antifinance Bill Demonstrations Kenya database is an AI-powered platform designed to track and identify individuals who have gone missing during the ongoing protests. It aims to assist in reuniting families by providing a centralized online resource for all Kenyans. The platform allows for crowdsourced information upload, monitoring disappearances, and tracking unidentified bodies to create a comprehensive database. Key features include a user-friendly interface, AI-powered search, real-time updates, secure handling of data, and detailed reporting.

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.

PyTorch Lightning is a framework for training and deploying AI models. It provides a high-level API that abstracts away the low-level details of PyTorch, making it easier to write and maintain complex models. Lightning also includes a number of features that make it easy to train and deploy models on multiple GPUs or TPUs, and to track and visualize training progress. PyTorch Lightning is used by a wide range of organizations, including Google, Facebook, and Microsoft. It is also used by researchers at top universities around the world. Here are some of the benefits of using PyTorch Lightning: * **Increased productivity:** Lightning's high-level API makes it easy to write and maintain complex models. This can save you time and effort, and allow you to focus on the research or business problem you're trying to solve. * **Improved performance:** Lightning's optimized training loops and data loading pipelines can help you train models faster and with better performance. * **Easier deployment:** Lightning makes it easy to deploy models to a variety of platforms, including the cloud, on-premises servers, and mobile devices. * **Better reproducibility:** Lightning's logging and visualization tools make it easy to track and reproduce training results.

AmbuFlow is a mobile application developed using HTML, CSS, JavaScript, and Google API to notify patients of nearby hospitals and provide estimated ambulance arrival times. It offers critical details like patient's location and enhances GPS route management with real-time traffic data for efficient navigation. The app helps users find nearby hospitals, track ambulances in real-time, and manage ambulance routes based on traffic and distance. It ensures quick emergency response, real-time tracking, enhanced communication, resource management, and a user-friendly interface for seamless navigation in high-stress situations.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

Tokencost is a clientside tool for calculating the USD cost of using major Large Language Model (LLMs) APIs by estimating the cost of prompts and completions. It helps track the latest price changes of major LLM providers, accurately count prompt tokens before sending OpenAI requests, and easily integrate to get the cost of a prompt or completion with a single function. Users can calculate prompt and completion costs using OpenAI requests, count tokens in prompts formatted as message lists or string prompts, and refer to a cost table with updated prices for various LLM models. The tool also supports callback handlers for LLM wrapper/framework libraries like LlamaIndex and Langchain.

ClearML is a suite of tools designed to streamline the machine learning workflow. It includes an experiment manager, MLOps/LLMOps, data management, and model serving capabilities. ClearML is open-source and offers a free tier hosting option. It supports various ML/DL frameworks and integrates with Jupyter Notebook and PyCharm. ClearML provides extensive logging capabilities, including source control info, execution environment, hyper-parameters, and experiment outputs. It also offers automation features, such as remote job execution and pipeline creation. ClearML is designed to be easy to integrate, requiring only two lines of code to add to existing scripts. It aims to improve collaboration, visibility, and data transparency within ML teams.

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.

Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

KitOps is a packaging and versioning system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using. KitOps simplifies the handoffs between data scientists, application developers, and SREs working with LLMs and other AI/ML models. KitOps' ModelKits are a standards-based package for models, their dependencies, configurations, and codebases. ModelKits are portable, reproducible, and work with the tools you already use.

Export comparison data from GSC to get a scatter plot of keyword rankings before and after an update.

I track STEPN game system changes daily.

Provides running splits for Strava Routes, accounting for distance and elevation changes

Expert on global biotech crops, policies, and trade data.

I provide monthly salary data in euros, using a structured format for global job roles.

Analyze and interpret datasets on Dutch SaaS companies' employee growth. Created by [E-commercemanagers.com](https://e-commercemanagers.com).

Historical product price tracker with analytical insights

MeepMouse, the advanced computer mouse for developers, displays logs of edits made in a virtual IDE, simulating direct code manipulation.

Assists with CCP clerical tasks.

Crypto Learning GPT

I'm Burning Earth, alarming users about environmental harm and climate change. Powered by Breebs (www.breebs.com)

The pressing environmental issues we face today require novel approaches and technological advancements to effectively mitigate their impacts. GaiaAI offers a range of tools and modes to promote sustainable practices and enhance environmental stewardship.

Advanced sports analyst with real-time data and interactive features

Expert in environmental justice data, with specific response criteria.

A polymath scientist aiding in climate action.

Data Breach Tracker - Latest Data Breach Details and Analysis

Your AI OSINT assistant. Our tool helps you find the data needle in the internet haystack.

Pivots to UUIDs, generates one.

Generates GUIDs with technical precision

I turn Toggl data into insightful visuals. Get your data from Settings (in Toggl Track) -> Data Export -> Export Time Entries. Ask for bonus analyses and plots :)