AI Agents & Automation

Bodfit Nutrition is an AI-powered platform designed to simplify nutrition tracking and meal planning. It features an AI-powered food scanner for effortless meal logging, allowing users to quickly record their food intake. The tool also provides personalized nutrition coaching, offering insights and guidance to help individuals achieve their health goals. Users can benefit from tailored meal plans that cater to their specific dietary needs and preferences. With calorie tracking capabilities, Bodfit Nutrition helps users monitor their intake and make informed decisions about their diet, fostering healthier eating habits.

ChatGiraffe is an AI financial assistant designed to simplify personal finance management. It allows users to track expenses and forecast budgets through a conversational interface, making financial management as easy as chatting. The tool leverages AI to automatically track expenses, analyze spending patterns, and optimize financial health. ChatGiraffe offers features like smart bookkeeping, data encryption for security, and real-world use cases shared by over a million users. It provides a free plan for basic financial needs and a Pro Plan for more advanced AI chats and multi-dimensional financial insights.

acu is a comprehensive, curated list of resources dedicated to AI agents for computer use. It serves as a central hub for researchers, developers, and enthusiasts looking to explore autonomous programs capable of reasoning, planning, and acting within digital environments. The repository categorizes resources into articles, research papers, surveys, frameworks, models, UI grounding techniques, datasets, benchmarks, and safety considerations. It covers a wide range of topics from foundational models and reinforcement learning approaches to specific applications in web navigation, mobile device control, and GUI automation. This resource is invaluable for understanding the current landscape and future directions of AI agents interacting with computer interfaces.

The Ghostery adblocker is an open-source JavaScript library designed for efficient blocking of ads, trackers, and other annoyances. It boasts strong compatibility, supporting 99% of filters from popular projects like Easylist and uBlock Origin. This library is highly embeddable, allowing developers to integrate adblocking functionality into various environments including Node.js, Puppeteer, Electron, and WebExtension (Chrome and Firefox). It is the core technology powering adblockers from Ghostery and Cliqz, used by millions of users, and has been battle-tested in diverse use cases such as mobile-friendly adblockers in React Native, web extensions, and batch request processing in Node.js. Its innovative algorithms are recognized for their performance, influencing other adblockers like Brave.

AgentField is an open-source control plane designed to build, run, and scale AI agents as production-ready APIs and microservices. It allows developers to write agent logic in Python, Go, or TypeScript, transforming it into robust infrastructure with features like routing, coordination, memory, async execution, and cryptographic audit trails. Every function becomes a REST endpoint, and each agent receives a cryptographic identity, ensuring every decision is traceable. AgentField supports structured AI output, human-in-the-loop approvals, cross-agent calls, and canary deployments. It also offers comprehensive observability, identity and access management, and verifiable credentials for tamper-proof execution receipts.

AgentDock is an open-source, backend-first framework designed for building sophisticated AI agents capable of executing complex tasks with configurable determinism. It comprises AgentDock Core, a framework-agnostic and provider-independent backend, and an Open Source Client, a Next.js application serving as a reference implementation. Built with TypeScript, AgentDock prioritizes simplicity, extensibility, and predictable AI system behavior. Key features include a modular node-based architecture, tools as specialized nodes, and comprehensive type safety. It supports both deterministic workflows and non-deterministic agent behaviors, allowing developers to balance creative AI capabilities with predictable system outcomes. AgentDock Pro, a cloud platform with visual workflow builders and advanced orchestration, is also coming soon.

Acme is a comprehensive library developed by Google DeepMind, designed to serve as a research framework for reinforcement learning (RL). It provides a collection of building blocks and agents that are simple, efficient, and readable, serving as both reference implementations and strong baselines for algorithm performance. The framework is flexible enough to be used as a starting point for novel research and supports running agents at various scales, from single-stream to distributed systems. Acme emphasizes ease of use for researchers, offering detailed working code examples, quickstart notebooks, and extensive documentation to help users get started with implementing and experimenting with RL algorithms.

Lirio is a personalization engine for digital health that leverages behavioral science and AI to power hyper-personalized health experiences. The platform helps organizations orchestrate each person’s unique healthcare journey through dynamic, personalized communications, which they call Precision Nudging®. By understanding and influencing human behavior, Lirio aims to remove barriers to health improvement and support individuals on their path to change. It moves beyond standard demographic segmentation to create highly tailored communications, fostering sustained engagement and healthier populations. The platform continuously learns and adapts behavioral interventions in real-time, helping to close gaps in care and reduce the total cost of care by automating ongoing touchpoints at scale.

DingoDB is an open-source distributed multi-modal vector database designed and developed by DataCanvas. It integrates real-time strong consistency, relational semantics, and vector semantics into a unified platform, offering exceptional horizontal scalability and elastic scaling capabilities to meet enterprise-grade high availability requirements. DingoDB provides comprehensive access interfaces, supporting SQL, SDK, and API, and treats Table and Vector as first-class citizen data models. Key features include built-in data high availability, fully automatic elastic data sharding, scalar-vector hybrid retrieval, and real-time index optimization. It also offers disk-based vector search for massive datasets and dynamic index switching.

AIScriptReader is an automated tool designed to provide professional AI screenplay coverage and feedback in minutes. It leverages industry-leading technology and proprietary algorithms to generate detailed story analysis, character breakdowns, and development notes. The platform specializes in analyzing movie scripts, with plans for future expansion. Users can upload their scripts and receive actionable reports, including comprehensive coverage reports and development notes. An AI Chat Assistant is also included, allowing users to interact with their script analysis for deeper insights into characters, plot, and themes. AIScriptReader aims to save time and money for writers, producers, and production companies by transforming weeks of waiting into minutes of insight.

TinyLLaVA_Factory is an open-source modular codebase designed for building small-scale large multimodal models (LMMs). Implemented in PyTorch and HuggingFace, it emphasizes simplicity, extensibility, and reproducibility. The framework allows users to customize their own LMMs with reduced coding effort and fewer mistakes. It integrates a suite of cutting-edge models and methods, supporting LLMs like OpenELM, TinyLlama, StableLM, Qwen, Gemma, and Phi. For vision towers, it includes CLIP, SigLIP, Dino, and combinations thereof. Connectors such as MLP, Qformer, and Resampler are also supported, alongside various training recipes including Frozen/Fully/Partially tuning and LoRA/QLoRA tuning. The project provides trained models, performance benchmarks, and local demo options for Gradio web and CLI inference.

Grow Easy is an AI-powered mobile application designed to simplify plant care for both beginners and experienced gardeners. The app provides personalized care reminders, ensuring users never miss a watering or feeding schedule. Its plant identification feature helps users quickly identify unknown plants and access detailed care instructions. Grow Easy also offers expert advice to troubleshoot common plant problems and optimize plant health. Available for free download on iOS and Android, it acts as a comprehensive companion for maintaining a thriving garden or collection of houseplants with minimal effort.

YouData.ai provides a developer-first platform for AI data engineering, designed to connect and prepare enterprise data for AI applications. It ingests messy databases, automatically fixes schemas, and syncs data to Vector DBs with sub-50ms latency. The platform features self-healing pipelines that adjust to schema drifts upstream, ensuring no downtime. With over 200 integrations, it connects natively to various data sources like Postgres, Snowflake, and MongoDB. YouData.ai offers an SDK to manage infrastructure, rate limiting, and schema validation, eliminating the need for users to manage Kafka clusters or Airflow instances. It is SOC2 Type II and HIPAA compliant, with deployment options on-premise or in a managed VPC, and granular observability via Datadog and New Relic.

AICommand is a proof-of-concept tool that integrates ChatGPT directly into the Unity Editor, enabling developers to control various aspects of their Unity projects using natural language prompts. This innovative approach aims to streamline game development workflows by allowing users to issue commands in plain English rather than traditional coding or manual interface interactions. While the creator notes it's not yet practical for production due to inconsistencies, it serves as a valuable exploration into the potential of AI in game development, offering insights into both its successes and failures. Developers can experiment with this integration by generating an API key and setting it within Unity's Project Settings, then accessing the AI Command window to input prompts.

Bitstrapped, in collaboration with Google and TELUS Digital, specializes in leveraging AI and automation to help organizations modernize their infrastructure and enhance customer experiences. Their services include Google Cloud migration and management, AI-driven contact center modernization, and the implementation of specialized analytics tools. They offer expertise in CCaaS with Google Contact Center AI (CCAI) and Google Gemini Enterprise for Customer Experience (GECX) solutions, enabling advanced NLU, multimodal customer experiences, and real-time AI assistance for agents. Bitstrapped focuses on delivering scalable, secure solutions that streamline operations, empower teams, and unlock new opportunities across various industries.

Tailo AI v2.0 delivers personalized AI product demos, asks qualifying questions, and automates lead qualification for B2B SaaS companies. This platform is designed to convert passive website visitors into booked meetings by engaging them with interactive product demonstrations. Tailo helps sales teams streamline their sales process by automating the initial stages of lead engagement and qualification, ensuring that only high-quality prospects are passed on for further sales interaction. It aims to boost conversions and accelerate the sales cycle for businesses.

Milo AI is a secure AI data analyst designed for business users to instantly analyze data using natural language. It connects to various databases, data warehouses, and tools like HubSpot and Salesforce, allowing users to ask questions as they would a colleague. Milo understands the query, finds answers across connected data sources, and presents them as charts, answers, and insights. The platform is built on a zero-trust architecture, ensuring data security and privacy with SOC 2, ISO 27001, and GDPR certifications. It supports over 700 integrations and offers enterprise-grade controls, regional data residency, and zero data retention, making it a reliable solution for real-time business intelligence without the need for analysts or complex BI tools.

Alink is an open-source machine learning algorithm platform built on Apache Flink, developed by the PAI team of Alibaba computing platform. It offers a wide array of machine learning algorithms for various tasks, including classification, regression, clustering, and recommendation systems. Alink supports both batch and stream processing, making it suitable for real-time AI applications. The platform provides Python (PyAlink) and Java APIs, allowing developers to integrate it into their existing workflows. It is designed for scalability and efficiency, leveraging Flink's distributed processing capabilities to handle large datasets and complex machine learning models. Alink also includes tools for feature engineering, model training, and deployment, making it a comprehensive solution for data scientists and developers working on AI projects.

AttentionDeepMIL offers a PyTorch implementation of Attention-based Deep Multiple Instance Learning, a technique detailed in the paper "Attention-based Deep Multiple Instance Learning" by Ilse, Tomczak, and Welling. This open-source tool is designed for researchers and developers to explore and apply attention mechanisms within deep learning models, particularly in the context of multiple instance learning. It includes code for running MNIST-BAGS experiments and provides guidance for adapting the model to histopathology datasets like Breast Cancer and Colon Cancer. The implementation features a modified LeNet-5 model with Attention-based MIL pooling and uses the negative log-likelihood of the Bernoulli distribution as its objective function. It's a valuable resource for those looking to replicate or extend research in this specialized area of deep learning.

Auto-Gmail-Creator is an open-source bot designed for the automated and bulk creation of Google (Gmail) accounts. Built with Python, it leverages Selenium and Seleniumwire to simulate user interactions, allowing for efficient account registration. The tool includes features like automatic downloading of necessary webdrivers (Chromedriver or Geckodriver) and options for customizing browser settings (Chrome or Firefox). Users can either manually provide account information via a CSV file or enable automatic generation of usernames and other details. It also supports proxy integration for enhanced anonymity and offers options for running in headless mode. While the script uses sms-activate.org for phone verification, the developer is actively seeking more robust SMS providers and proxy solutions to bypass bot detection.

async-rl offers a practical implementation of asynchronous 1-step Q learning, as detailed in the paper "Asynchronous Methods for Deep Reinforcement Learning." This open-source project leverages Tensorflow and Keras for deep Q network definition and optimization, while integrating with OpenAI's Gym library for interaction with the Atari Learning Environment. A key feature is its use of multiple actor-learner threads, which helps stabilize the learning process without relying on memory-intensive experience replay, making it efficient for machines with less RAM. The repository also includes a work-in-progress asynchronous advantage actor-critic implementation and provides instructions for training, visualizing with TensorBoard, and evaluating models.

Nutrio Ai is an AI-powered smart diet tracker and personalized nutritionist designed to help users achieve their health goals. It offers personalized weight-loss plans tailored to individual needs, providing daily advice and actionable tips. A key feature is its smart calorie and nutrient tracking, allowing users to simply snap a photo of their meal for instant calorie estimates and detailed nutritional information. Users can also chat with an AI nutritionist for instant advice and support. The tool includes progress tracking with detailed charts, a customizable dashboard, and a water consumption tracker to ensure hydration goals are met. It aims to be an affordable and user-friendly alternative to a traditional nutritionist.

ATM (Auto Tune Models) is an open-source AutoML system developed by the Data to AI Lab at MIT, focusing on simplifying machine learning model selection and tuning. It operates as a multi-tenant, multi-data system, allowing users to provide a classification problem and a dataset in CSV format. ATM then automatically searches for and builds the best predictive model. The system supports various data input methods, including local CSV files, AWS S3 buckets, and URLs. It offers a Python API for creating ATM instances, running model searches, and exploring results, including summaries of dataruns, best classifiers, and detailed scores. Users can export and load trained models for making predictions on new data. ATM is built on Python and is designed for both ease of use and scalability.

Puppet Master is an innovative AI tool available on Hugging Face Spaces that enables users to bring static images of dynamic objects to life. By simply uploading an image, users can define specific part-level interactions through an intuitive drag-and-drop interface. The application automatically preprocesses the image, intelligently segments the object, and then animates it according to the user's specifications, culminating in a generated animated GIF. This tool is ideal for quickly creating dynamic visual content from static images, offering a straightforward approach to object animation without requiring complex software or extensive technical skills.