AI Agents & Automation

Calendarly transforms your iPhone Lock Screen into an automated, private calendar display. It allows users to see their full daily schedule at a glance without needing to open an app. The tool offers extensive customization options, including various preset layouts, adjustable spacing, custom fonts, and unlimited color combinations, enabling users to personalize their calendar wallpaper. Calendarly operates entirely on-device, ensuring that all calendar data remains private and is never sent to servers or stored in the cloud. It works offline and does not require an account or collect any personal data, making it a privacy-friendly solution for staying organized and focused.

Bunney is a free and cute coupon finder designed to help users save money on their online purchases. It provides verified promo codes and deals for over 10,000 stores, aiming to offer significant discounts without the need for searching. The tool emphasizes a privacy-first approach, positioning itself as an alternative to coupon extensions that might track user data. Bunney is 100% free to use and focuses on delivering sweet deals and verified coupons to make online shopping more affordable and efficient. Users can simply type a shop name or paste a link to find available savings.

MobileVLM is a competent multimodal vision language model (MMVLM) specifically engineered to run efficiently on mobile devices. It integrates a novel architectural design, an improved training scheme tailored for mobile VLMs, and high-quality dataset curation to achieve superior performance. The tool comprises language models at 1.4B and 2.7B parameters, trained from scratch, and a multimodal vision model pre-trained in the CLIP fashion. MobileVLM V2, an enhanced version, demonstrates performance comparable to or exceeding much larger VLMs at the 3B and 7B+ scales, while maintaining state-of-the-art inference speeds on mobile hardware like Qualcomm Snapdragon 888 CPU and NVIDIA Jeston Orin GPU. It is an open-source project, providing training and inference code, along with publicly available weights on HuggingFace.

Keuzehulp Studio is a no-code platform designed to empower businesses to create intelligent decision-making tools, scenarios, and advice modules. It simplifies complex choices for customers by guiding them through structured conversations to personalized outcomes. The platform focuses on clarity and usability, enabling marketing, sales, and service teams to build sophisticated decision support systems without requiring any technical expertise. Users can easily design interactive choice helpers to enhance customer experience and streamline internal processes, making it an ideal solution for improving customer engagement and operational efficiency.

aignosi Brasil provides SIENTIA™, an innovative Industrial AIOps platform that enables companies to rapidly deploy and scale AI models in Operational Technology (OT) environments. The platform focuses on transforming data (DataOps) and model (MLOps) operations, helping businesses move AI proofs of concept (PoCs) into full production 10x faster. SIENTIA™ is already utilized by enterprise clients across various heavy-asset industries, handling millions of inferences per month with low latency. Beyond the platform, aignosi offers complementary services including AI Maturity Assessments, Analytical Transformation, and Analytical Core support to help clients create tailored AI solutions and optimize operational efficiency.

Megatron-LM is an NVIDIA-developed, GPU-optimized library designed for training large transformer models at scale. It comprises two main components: Megatron-LM, which offers pre-configured training scripts for research teams and quick experimentation, and Megatron Core, a composable library providing GPU-optimized building blocks for custom training frameworks. Megatron Core includes transformer building blocks, advanced parallelism strategies (TP, PP, DP, EP, CP), mixed precision support (FP16, BF16, FP8, FP4), and various model architectures. It's ideal for framework developers and ML engineers building custom training pipelines. The library also features Megatron Bridge for bidirectional Hugging Face ↔ Megatron checkpoint conversion, ensuring interoperability and production-ready recipes. It supports training models from 2B to 462B parameters across thousands of GPUs, achieving high Model FLOP Utilization (MFU).

Outside is a versatile tool designed to help individuals and teams organize, track, and share their work efficiently. It manages five distinct data types, with trips being one of them, providing a centralized platform for various organizational needs. This tool aims to simplify work management by consolidating different aspects into a single location, making it easier for both solo users and collaborative teams to stay on top of their projects and information. Its focus on managing multiple data types suggests a broad application for different organizational challenges.

RQ-VAE-Recommender offers a PyTorch implementation of a generative retrieval model, specifically designed for recommender systems. The model operates in two stages: first, it maps items in a corpus to a tuple of semantic IDs by training an RQ-VAE. Second, it tokenizes sequences of these semantic IDs using a frozen RQ-VAE and then trains a transformer-based model to predict the next IDs in the sequence. This approach is based on the research presented in "Recommender Systems with Generative Retrieval." It supports various datasets, including Amazon Reviews (Beauty, Sports, Toys), MovieLens 1M, and MovieLens 32M, and provides both RQ-VAE and decoder-only retrieval model training scripts. Pre-trained checkpoints are available on Hugging Face for Amazon Beauty.

PyTriton is a Flask/FastAPI-like framework designed to streamline the use of NVIDIA's Triton Inference Server within Python environments. It allows developers to serve machine learning models with ease, supporting direct deployment from Python. Key features include native Python support for exposing any Python function as an HTTP/gRPC API, framework-agnostic operation compatible with PyTorch, TensorFlow, or JAX, and performance optimizations like dynamic batching, response caching, and model pipelining. The tool also provides decorators for handling batching and pre-processing, high-level model clients for HTTP/gRPC requests, and alpha support for streaming partial responses.

Sonara is an AI-powered platform designed to streamline and automate the job search process for individuals. It gets to know your skills and preferences, then continuously scans millions of job openings to find the best matches. The tool then automatically applies to these relevant positions, effectively multiplying the number of applications submitted with minimal effort from the user. Sonara aims to reclaim valuable hours for job seekers by handling the tedious grunt work of applications, allowing users to wake up to a curated list of new roles and significantly increase their application volume until they are hired.

ROSA (Robot Operating System Agent) is an AI Agent developed by NASA JPL, designed to facilitate interaction with ROS1- and ROS2-based robotics systems through natural language queries. Built on the Langchain framework, ROSA empowers robot developers to inspect, diagnose, understand, and operate robots more efficiently. It supports custom agent creation, allowing for adaptation to various robots and environments, and offers features like identifying topics with publishers but no subscribers. The tool includes a TurtleSim demo for controlling a simulated robot and is actively developing an IsaacSim extension for direct integration and control within the simulation environment.

MetaMevs provides a comprehensive suite of automated MEV bots engineered to help users capture on-chain profits from DEX transactions. The platform eliminates the need for coding, making advanced trading strategies accessible to a wider audience. Key offerings include the Sandwich Mevbot for reliable smart contract execution, an HFT Futures and Spot Bot for high-frequency trading on platforms like Binance and KuCoin, and a Flashloan Arbitrage Bot that leverages AI and smart contract strategies to profit from price differences in DeFi. Additionally, the MetaMev Sniper bot uses AI, similar to GPT-4, to identify and snipe verified tokens on launchpads and social media. MetaMevs emphasizes cutting-edge technology, unmatched performance with millisecond execution, easy integration, and robust security features, all within customizable solutions.

Data Wizards is an AI consulting firm specializing in helping corporates and ambitious SMEs unlock their business potential through expert AI solutions. They provide comprehensive services including AI strategy development, AI solution and development, and AI education. Data Wizards builds high-performing AI solutions to overcome challenges, streamline operations, and identify new growth opportunities. Their expertise spans various industries such as Automotive, Retail, Pharmaceutical, Manufacturing, Insurance, Financial, Logistics, Energy, Healthcare, Telecommunications, Media, SMEs, Security, Commodity, and Food, offering tailored applications like predictive maintenance, sales forecasts, customer churn analysis, and fraud detection.

Sonata is the official project repository for "Sonata: Self-Supervised Learning of Reliable Point Representations," a CVPR'25 Highlight paper. This open-source tool provides self-supervised pre-trained Point Transformer V3 models specifically designed for various 3D point cloud downstream tasks. Users can leverage Sonata for quick inference and visualization, with easy-to-use installation options for both standalone and package modes. The repository includes pre-trained models, inference code, and visualization demos, making it accessible for researchers and developers. It supports custom data integration and offers a flexible data transformation pipeline, along with options for loading models from Huggingface or local paths, even accommodating environments without FlashAttention.

Streaming is a data streaming library built by MosaicML designed to make training on large datasets from cloud storage as fast, cheap, and scalable as possible. It is specifically optimized for multi-node, distributed training for large models, ensuring correctness, performance, and ease of use. The library supports various data types including images, text, video, and multimodal data, and is compatible with major cloud storage providers like AWS, OCI, GCS, Azure, and any S3 compatible object store. It integrates seamlessly into existing training workflows as a drop-in replacement for PyTorch IterableDataset. Key features include seamless data mixing, true determinism for reproducible training runs, instant mid-epoch resumption, high throughput, and equal convergence compared to local disk solutions.

InsightNext is a Google Cloud Partner specializing in AI/ML and Data Engineering. They offer deep expertise in Google Cloud Platform (GCP) and Google Workspace, helping organizations modernize their infrastructure and secure their workloads with robust governance. Their services focus on implementing AI/ML solutions and advanced data engineering practices to solve complex business challenges. InsightNext aims to drive enterprise data transformation through AI-driven cloud solutions and agentic AI systems, delivering measurable outcomes for their clients.

Synaptic is an open-source JavaScript neural network library designed for both Node.js environments and web browsers. Its core strength lies in its architecture-free algorithm, which allows developers to construct and train virtually any type of first-order or second-order neural network. The library comes equipped with several built-in architectures, including multilayer perceptrons, multilayer long-short term memory networks (LSTM), liquid state machines, and Hopfield networks. Additionally, it features a versatile trainer capable of training any given network, complete with built-in tasks for testing and comparing architectural performance, such as solving XOR problems or completing Distracted Sequence Recall tasks. This makes Synaptic a powerful tool for developers looking to implement and experiment with neural networks in their JavaScript projects.

Flourish Science is an AI-driven mental wellness application designed to promote well-being, motivation, and personal growth. Developed by psychologists, it features Sunnie, an AI wellness buddy available 24/7 to help users manage stress and anxiety, improve focus, and build healthy habits. The app incorporates evidence-based techniques from positive psychology, mindfulness, CBT, and DBT, transforming them into personalized, in-the-moment exercises. Key features include a focus timer, interactive journal, positive affirmations, relaxation exercises, and a smart habit tracker with gamified experiences. Flourish also provides meaningful insights through session notes, emotion charts, and weekly/monthly reports, fostering a supportive community for users.

Exabits.ai serves as the backbone of AI infrastructure, providing a comprehensive network of GPUs designed to accelerate AI development and innovation. Their offerings span from consumer-grade GPUs to high-end NVIDIA models like GB200s, H100s, H200s, and RTX5090s. Exabits is dedicated to refining raw GPU assets from leading manufacturers to deliver the most cost-effective compute solutions available. The platform is obsessed with innovating performance, ensuring that users have access to powerful and sustainable computing infrastructure for their AI applications and web3.0 initiatives. This focus on diverse GPU availability and performance optimization makes Exabits a key player in supporting advanced AI workloads.

Texygen is an open-source benchmarking platform designed to support research in open-domain text generation models. It offers a comprehensive suite of implemented text generation models, alongside a diverse set of metrics for evaluating the diversity, quality, and consistency of generated texts. The platform aims to standardize research in the field of text generation, fostering reproducibility and reliability in future work. By facilitating the sharing of fine-tuned open-source implementations among researchers, Texygen helps advance the development and understanding of text generation technologies. It supports Python 3.6+ and popular libraries like TensorFlow, Numpy, Scipy, and NLTK.

Hilker Consulting is a leading AI consulting firm and academy specializing in AI transformation for B2B decision-makers in the DACH region. They offer certified AI training programs, including AI Manager and AI Consultant courses, which are AZAV and ZFU-certified, ensuring state-recognized quality and maximum funding opportunities. Led by Dr. Claudia Hilker, a renowned AI expert, the academy combines academic rigor with practical experience from over 500 AI projects. The services include strategic AI implementation, AI-driven marketing and sales, and compliance with the EU AI Act. Their unique approach focuses on building AI competence within companies, offering group coaching, and ensuring measurable ROI for businesses looking to gain a competitive edge through AI.

tiny-cuda-nn is a high-performance C++/CUDA neural network framework designed for speed and efficiency in training and querying neural networks. It incorporates a lightning-fast "fully fused" multi-layer perceptron and a versatile multiresolution hash encoding, as detailed in its technical papers. The framework supports various input encodings, losses, and optimizers, making it adaptable for diverse neural network applications. It also offers JIT fusion for significant performance boosts, particularly on newer NVIDIA GPUs, and provides PyTorch bindings for integration into Python workflows, though native CUDA performance remains superior for large batch sizes. The framework is ideal for developers and researchers working on demanding AI tasks requiring optimized computational performance.

Trafilatura is a powerful Python package and command-line tool designed for comprehensive web data extraction. It simplifies the process of converting raw HTML into structured, meaningful data, offering capabilities for web crawling, scraping, and extraction of main texts, metadata, and comments. The tool is highly configurable and robust, balancing precision in limiting noise with recall for including all valid content. It supports sitemaps and feeds for advanced text discovery, efficient processing of online and offline input, and offers multiple output formats including TXT, Markdown, CSV, JSON, HTML, XML, and XML-TEI. Trafilatura is widely adopted by major companies and institutions, and consistently outperforms other open-source libraries in text extraction benchmarks.

Transformer-SSL is an open-source project offering the official implementation for "Self-Supervised Learning with Swin Transformers." This codebase is notable for including Swin Transformer as one of its backbones, enabling the evaluation of learned representations' transferring performance on downstream tasks like object detection and semantic segmentation. It features MoBY, a self-supervised learning approach combining MoCo v2 and BYOL, achieving high accuracy on ImageNet-1K linear evaluation with significantly fewer tricks than previous works. The project provides models and code for self-supervised learning, linear evaluation, and demonstrates strong performance when transferring to object detection and semantic segmentation tasks.