Best AI tools for< Aggregate Values >

Optimal AI is an AI platform designed for software engineering teams to measure, optimize, and act on metrics to drive impactful outcomes. It helps in improving engineering efficiency, customer delivery, and prioritizing initiatives that deliver customer value. The platform aggregates and reconciles performance data at the team and project level, providing real-time visibility into delivery and insights to enhance processes and interactions in engineering.

Fritz AI is an AI tool that scans and ranks all AI tools, apps, and websites based on a set of criteria to determine the best and most ethical options. They provide technical guides, reviews, and tutorials to help users get started with machine learning. Fritz AI focuses on ethics, functionality, user experience, and innovation when evaluating tools. Users can contribute tool suggestions and collaborate with the Fritz AI team. The platform also offers beginner-friendly guides, consulting services, and promotes ethical use of AI and machine learning technologies.

Tabula is a visual data analytics tool that uses AI to help businesses get insights from their data. It is easy to use and can be used by anyone, regardless of their technical expertise. Tabula can be used to access and unify data from a variety of sources, standardize and blend datasets, add custom metrics, build stunning reports, and automate repetitive tasks. Tabula is integrated with a variety of data sources and platforms, making it easy to get started.

Double is an AI tool designed to help users find and convert leads with hyper-targeted messages. It automates the process of cleaning, enriching, and qualifying leads using AI technology. By leveraging GPT, Double can research leads on the internet and provide answers to questions, saving users time and effort in manual research tasks. The platform is ideal for sales and marketing teams looking to streamline their lead generation process and improve conversion rates through personalized messaging.

Raijin.ai is an AI-powered Customer Discovery and Intelligence Hub designed to help teams aggregate and extract key insights from customer conversations. It accelerates product development by prioritizing features based on customer feedback. The platform offers features like AI Thematic Analysis, Report Writing, Segmentation, and Tags to streamline qualitative research and analysis processes. Raijin.ai is ideal for user researchers, product analysts, and teams looking to integrate AI seamlessly into their workflow to create customer-centric products and data-driven marketing strategies.

Aomni is an AI-powered sales engagement platform that helps B2B sellers build better buyer relationships and save time on prep work throughout the sales cycle. It uses intelligent automation to aggregate data, identify and contact prospects, and provide insights to help sellers close more deals. Aomni's AI assistant is a B2B sales expert out of the box and is fine-tuned to understand your specific ICPs, competitors, and sales playbooks.

Trustpilot productai.one is an AI tool designed to provide product reviews and ratings. It utilizes artificial intelligence algorithms to analyze and aggregate customer feedback, helping users make informed purchasing decisions. The platform offers a user-friendly interface where consumers can explore and compare various products based on real customer experiences. With Trustpilot productai.one, users can access valuable insights and recommendations to guide their shopping choices.

LogRocket is a session replay, product analytics, and issue detection platform that helps software teams deliver the best web and mobile experiences. With LogRocket, you can see exactly what users experienced on your app, as well as DOM playback, console and network logs, errors, and performance data. You can also surface the most impactful user issues with JavaScript errors, network errors, stack traces, automatic triaging, and alerting. LogRocket also provides product analytics to help you understand how users are interacting with your app, and UX analytics to help you visualize how users experience your app at both the individual and aggregate level.

The website is a B2B research AI agent that automates manual B2B research processes by curating, refining, and enriching lead databases with AI agents. It offers features like source, curate, aggregate data points, templates, and custom AI-powered enrichment. The application helps users gather the right data, speed up research processes, and target relevant companies. It provides a range of pricing plans, compliance with ISO 9001, and a mobile application. The AI agent is used by companies like UBS, Microsoft, and Airbnb, and utilizes technologies like MongoDB, Flutter, and Next.js.

AskJimmy is a platform for AI agents focused on finance and trading. It offers exposure to a diverse range of strategies managed by top-notch AI Agents. The platform allows users to compose autonomous agents and trading strategies with extreme customization. It aims to create a decentralized multi-strategy collaborative hedge-fund powered by AI agents. AskJimmy is designed to aggregate non-correlated autonomous agent strategies into a diversified subnet, shaping the future of multi-strategies decentralized hedge-fund.

AltIndex is an AI-powered investment analysis platform that provides unique AI stock picks, stock alerts, and alternative insights to help users make better investment decisions. The platform goes beyond traditional financial data by integrating various alternative data points such as job postings, website traffic, customer satisfaction, app downloads, and social media trends. AltIndex offers impactful insights and alerts, cutting-edge solutions to stay informed about companies in your portfolio, and advanced algorithms for real-time investment decision-making.

CloudMedx is a healthcare data platform that provides aggregation, automation, and AI solutions. It simplifies decision making for patients, providers, and payers with a single powerful platform. Clinical, operations, and financial results are coordinated and delivered like never before.

LeadFuze is an AI-powered prospecting tool for business leads and candidate sourcing. It offers unlimited and automated lead generation software that sets lead generation on autopilot. LeadFuze aggregates, matches, and verifies information in real-time across 500+ million people. It provides accurate contact and data intelligence for revenue teams and recruiters, with top ratings for ease-of-use, quality of support, and ease-of-setup. The tool is built specifically for sales, marketing, and recruiting use cases, offering hyper-targeted lead searches, complete list building automation, and integration with CRM and workflow tools. LeadFuze's AI capabilities allow users to find new leads, search specific accounts, and automate lead generation workflows effortlessly.

Monterey AI is an AI-powered insights platform that helps businesses understand their customers' needs and build better products. It aggregates, triages, and analyzes user feedback, tickets, conversations, surveys, and transcripts to provide businesses with real-time insights into what their customers are saying and what they want. Monterey AI is used by businesses of all sizes, from startups to Fortune 20 companies, to improve their product development process and build better products that meet the needs of their customers.

CustomerIQ is an AI platform that automatically discovers and quantifies themes across customer feedback channels like calls, surveys, tickets, and transcripts. It aggregates customer feedback, extracts and categorizes feature requests, pain points, preferences, and highlights related to customers. The platform helps align teams, prioritize work, and build a customer-obsessed culture. CustomerIQ accelerates development by scoping project requirements faster and providing actionable insights backed with context.

Sofon is a knowledge aggregation and curation platform that provides users with personalized insights on topics they care about. It aggregates and curates knowledge shared across 1,000+ articles, podcasts, and books, delivering a personalized stream of ideas to users. Sofon uses AI to compare ideas across hundreds of people on any question, saving users thousands of hours of curation. Users can indicate the people they want to learn from, and Sofon will curate insights across all their knowledge. Users can receive an idealetter, which is a unique combination of ideas across all the people they've selected around a common theme, delivered at an interval of their choice.

Quantexa News Intelligence is an AI-powered news data application that provides fast and powerful access to global news content. It offers real-time access to enriched, tagged, and structured news feeds, enabling users to build intelligent news-driven applications and workflows. With features like AI-powered search, data visualizations, and instant insights, Quantexa News API aggregates news from 90,000+ sources and 1.3M NLP-enriched articles daily. It helps users investigate events, enhance risk monitoring processes, and deliver news data to relevant apps and models efficiently.

FluidStack is a leading GPU cloud platform designed for AI and LLM (Large Language Model) training. It offers unlimited scale for AI training and inference, allowing users to access thousands of fully-interconnected GPUs on demand. Trusted by top AI startups, FluidStack aggregates GPU capacity from data centers worldwide, providing access to over 50,000 GPUs for accelerating training and inference. With 1000+ data centers across 50+ countries, FluidStack ensures reliable and efficient GPU cloud services at competitive prices.

Medical Brain is an AI-powered clinical assistant designed for both patients and providers. It engages with users to identify health risks and care gaps early, providing actionable insights and guidance to improve outcomes and intercept high-cost ER visits. The platform monitors patients 24/7, aggregates and understands all patient data, and generates real-time actions based on AI clinical decision support and automation. Medical Brain incorporates evidence-based best practices in various clinical modules and continuously learns from user experiences to enhance efficiency and intelligence.

FindAMeal is an AI-powered search engine that helps users discover nearby restaurants based on their personal preferences. By combining data from various food review providers and utilizing AI technology, FindAMeal simplifies the process of finding the perfect dining spot. Users can make any type of query, from finding a date spot to selecting a fancy restaurant for special occasions. The platform aggregates information from sources like Google, Yelp, and Foursquare to offer tailored recommendations, making it easy for users to explore new dining experiences.

aiostream provides a collection of stream operators for creating asynchronous pipelines of operations. It offers features like operator pipe-lining, repeatability, safe iteration context, simplified execution, slicing and indexing, and concatenation. The stream operators are categorized into creation, transformation, selection, combination, aggregation, advanced, timing, and miscellaneous. Users can combine these operators to perform various asynchronous tasks efficiently.

Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

AIS-catcher: A multi-platform AIS Receiver

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

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.

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs. Aim provides a performant and beautiful UI for exploring and comparing training runs. Additionally, its SDK enables programmatic access to tracked metadata — perfect for automations and Jupyter Notebook analysis. **Aim's mission is to democratize AI dev tools 🎯**

Minic is a chess engine developed for learning about chess programming and modern C++. It is compatible with CECP and UCI protocols, making it usable in various software. Minic has evolved from a one-file code to a more classic C++ style, incorporating features like evaluation tuning, perft, tests, and more. It has integrated NNUE frameworks from Stockfish and Seer implementations to enhance its strength. Minic is currently ranked among the top engines with an Elo rating around 3400 at CCRL scale.

Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

Screen-pipe is a Rust + WASM tool that allows users to turn their screen into actions using Large Language Models (LLMs). It enables users to record their screen 24/7, extract text from frames, and process text and images for tasks like analyzing sales conversations. The tool is still experimental and aims to simplify the process of recording screens, extracting text, and integrating with various APIs for tasks such as filling CRM data based on screen activities. The project is open-source and welcomes contributions to enhance its functionalities and usability.

Kafka-ML is a framework designed to manage the pipeline of Tensorflow/Keras and PyTorch machine learning models on Kubernetes. It enables the design, training, and inference of ML models with datasets fed through Apache Kafka, connecting them directly to data streams like those from IoT devices. The Web UI allows easy definition of ML models without external libraries, catering to both experts and non-experts in ML/AI.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

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

Geopolitical news aggregator and forecaster

Bilingual Canadian news aggregator. Canadian News blocked by Facebook and Google? No problem!

AI news aggregator from top tech sources

Swapzone is a non-custodial instant crypto exchange aggregator that helps users scan the network of registered exchanges globally and gives them a comprehensive list of those that support a particular trading or swap pair.

Retrieve data on DeFi protocols and blockchains

A GPT/AI system designed to collect, analyze, and summarize recent news from established media outlets, emphasizing balance in perspectives and precision in content delivery, with a default focus on top breaking news stories, adaptable to user-specified topics.