Best AI tools for< Implement Architectures >

GoodGist is an AI platform that focuses on customer and partner enablement. It offers autonomous learning, support, and knowledge management powered by AI to help software companies onboard faster, implement better, and support stronger. The platform provides personalized training, reduces support tickets, generates reference architectures, and facilitates collaboration among teams and partners. GoodGist aims to enhance software proficiency, reduce support costs, improve customer satisfaction, and increase partner engagement through hyper-personalized learning experiences and adaptive content support.

Asaria Industries is an AI application that focuses on building intelligent systems to transform industries. They offer system architecture and AI integration services to help modernize enterprise infrastructure and implement intelligent decision systems. With expertise in engineering scalable foundations for complex systems, Asaria Industries aims to turn visions into reality through innovative solutions.

Nebius AI is an AI-centric cloud platform designed to handle intensive workloads efficiently. It offers a range of advanced features to support various AI applications and projects. The platform ensures high performance and security for users, enabling them to leverage AI technology effectively in their work. With Nebius AI, users can access cutting-edge AI tools and resources to enhance their projects and streamline their workflows.

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.

Qlerify is an AI-powered software modeling tool that helps digital transformation teams accelerate the digitalization of enterprise business processes. It allows users to quickly create workflows with AI, generate source code in minutes, and reuse actionable models in various formats. Qlerify supports powerful frameworks like Event Storming, Domain Driven Design, and Business Process Modeling, providing a user-friendly interface for collaborative modeling.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

STELLARWITS is an AI solutions and software platform that empowers users to explore cutting-edge technology and innovation. The platform offers AI models with versatile capabilities, ranging from content generation to data analysis to problem-solving. Users can engage directly with the technology, experiencing its power in real-time. With a focus on transforming ideas into technology, STELLARWITS provides tailored solutions in software and AI development, delivering intelligent systems and machine learning models for innovative and efficient solutions. The platform also features a download hub with a curated selection of solutions to enhance the digital experience. Through blogs and company information, users can delve deeper into the narrative of STELLARWITS, exploring its mission, vision, and commitment to reshaping the tech landscape.

Palo Alto Networks is a cybersecurity company offering advanced security solutions powered by Precision AI to protect modern enterprises from cyber threats. The company provides network security, cloud security, and AI-driven security operations to defend against AI-generated threats in real time. Palo Alto Networks aims to simplify security and achieve better security outcomes through platformization, intelligence-driven expertise, and proactive monitoring of sophisticated threats.

Ringover is an AI-driven conversation platform designed for staffing and sales teams. It offers features such as transcription and call summaries, mood analysis, cloud telephony, multichannel communications, sales prospecting automations, app marketplace integration, and more. The platform aims to centralize all communication channels within a simple interface, empowering users to enhance productivity and streamline conversations with clients and prospects. Ringover also provides advanced analytics, automation, and coaching to boost the productivity of recruiting and sales teams. With seamless integration with various business tools, Ringover offers a comprehensive solution for businesses looking to optimize their communication strategies.

RankSense is an AI-powered SEO tool designed to help users optimize their website's search engine performance efficiently. Created by Hamlet Batista, RankSense enables users to implement immediate changes to SEO meta tags, structured data, and redirects at scale. By leveraging Cloudflare and Google Sheets, users can make SEO changes on thousands of pages with just a few clicks, without the need for developers. The tool also offers features such as monitoring SEO changes, discovering pages that need optimization, and automatically improving search snippets using artificial intelligence.

RIOS is an AI-powered automation tool that revolutionizes American manufacturing by leveraging robotics and AI technology. It offers flexible, reliable, and efficient robotic automation solutions that integrate seamlessly into existing production lines, helping businesses improve productivity, reduce operating expenses, and minimize risks. RIOS provides intelligent agents, machine tending, food handling, and end-of-line packout services, powered by AI and robotics. The tool aims to simplify complex manual processes, ensure total control of operations, and cut costs for businesses facing production inefficiencies and challenges in labor productivity.

Cue AI is an AI research lab dedicated to enhancing the capabilities of cutting-edge models. The lab is committed to pushing the boundaries of AI technology and innovation. While the website currently has limited information, it serves as a platform for sharing updates and developments in the field of artificial intelligence. For inquiries or collaborations, users can reach out via email at [email protected].

Faculty AI is a leading applied AI consultancy and technology provider, specializing in helping customers transform their businesses through bespoke AI consultancy and Frontier, the world's first AI operating system. They offer services such as AI consultancy, generative AI solutions, and AI services tailored to various industries. Faculty AI is known for its expertise in AI governance and safety, as well as its partnerships with top AI platforms like OpenAI, AWS, and Microsoft.

Modulos is a Responsible AI Platform that integrates risk management, data science, legal compliance, and governance principles to ensure responsible innovation and adherence to industry standards. It offers a comprehensive solution for organizations to effectively manage AI risks and regulations, streamline AI governance, and achieve relevant certifications faster. With a focus on compliance by design, Modulos helps organizations implement robust AI governance frameworks, execute real use cases, and integrate essential governance and compliance checks throughout the AI life cycle.

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

Lifestyle Medicine WORKS™ PRO AI is a comprehensive AI-powered platform designed for physicians, healthcare providers, and clinics worldwide. It offers tools and courses to master evidence-based Lifestyle Medicine, reduce team burnout, save time, create new revenue opportunities, and improve chronic diseases patient health outcomes. The platform includes 6 AI Assistants, a 101 Course, business strategies, certification, and more. Lifestyle Medicine WORKS™ PRO AI aims to empower healthcare professionals to seamlessly integrate evidence-based Lifestyle Medicine into their practice and help patients prevent, reduce, and even reverse chronic symptoms.

SentiSight.ai is a machine learning platform for image recognition solutions, offering services such as object detection, image segmentation, image classification, image similarity search, image annotation, computer vision consulting, and intelligent automation consulting. Users can access pre-trained models, background removal, NSFW detection, text recognition, and image recognition API. The platform provides tools for image labeling, project management, and training tutorials for various image recognition models. SentiSight.ai aims to streamline the image annotation process, empower users to build and train their own models, and deploy them for online or offline use.

Demand Spring is a strategic AI implementation platform for B2B marketing leaders. They offer services such as AI advisory for revenue acceleration, AI activation & growth services, training & enablement for AI-first mindset teams, and marketing automation & AI workflow agents. The platform helps B2B marketing leaders leverage AI and marketing automation platforms to transform operations, increase productivity, and create personalized customer engagement. Demand Spring aims to make AI and automation accessible, actionable, and impactful for their clients.

Notice is an AI-powered platform that allows users to create blogs, documents, portfolios, and more with ease. It offers collaborative editing, auto-translation in over 100 languages, and an AI writing assistant. Users can embed their content anywhere on the web using ready-to-use templates that are SEO-friendly. Notice simplifies content creation and publishing, making it accessible to users of all skill levels.

The Transparency Coalition is a platform dedicated to advocating for legislation and transparency in the field of artificial intelligence. It aims to create AI safeguards for the greater good by focusing on training data, accountability, and ethical practices in AI development and deployment. The platform emphasizes the importance of regulating training data to prevent misuse and harm caused by AI systems. Through advocacy and education, the Transparency Coalition seeks to promote responsible AI innovation and protect personal privacy.

Paper-Replications is a repository dedicated to replicating classic and state-of-the-art AI/ML papers and architectures from scratch using PyTorch. It serves as a valuable resource for researchers and enthusiasts looking to understand and implement cutting-edge algorithms in the field of artificial intelligence and machine learning.

Generative-AI-Drug-Discovery is a public repository on GitHub focused on using tensor network machine learning approaches to accelerate GenAI for drug discovery. The repository aims to implement effective architectures and methodologies into Large Language Models (LLMs) to enhance Drug Discovery Generative AI performance.

This repository contains the source code for a GEMM & deep learning hardware accelerator system used to validate proposed systolic array hardware architectures implementing efficient matrix multiplication algorithms to increase performance-per-area limits of GEMM & AI accelerators. Achieved results include up to 3× faster CNN inference, >2× higher mults/multiplier/clock cycle, and low area with high clock frequency. The system is specialized for inference of non-sparse DNN models with fixed-point/quantized inputs, fully accelerating all DNN layers in hardware, and highly optimizing GEMM acceleration.

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

Vision-LLM-Alignment is a repository focused on implementing alignment training for visual large language models (LLMs), including SFT training, reward model training, and PPO/DPO training. It supports various model architectures and provides datasets for training. The repository also offers benchmark results and installation instructions for users.

Hailo TAPPAS is a set of full application examples that implement pipeline elements and pre-trained AI tasks. It demonstrates Hailo's system integration scenarios on predefined systems, aiming to accelerate time to market, simplify integration with Hailo's runtime SW stack, and provide a starting point for customers to fine-tune their applications. The tool supports both Hailo-15 and Hailo-8, offering various example applications optimized for different common hosts. TAPPAS includes pipelines for single network, two network, and multi-stream processing, as well as high-resolution processing via tiling. It also provides example use case pipelines like License Plate Recognition and Multi-Person Multi-Camera Tracking. The tool is regularly updated with new features, bug fixes, and platform support.

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

Bark.cpp is a C/C++ implementation of the Bark model, a real-time, multilingual text-to-speech generation model. It supports AVX, AVX2, and AVX512 for x86 architectures, and is compatible with both CPU and GPU backends. Bark.cpp also supports mixed F16/F32 precision and 4-bit, 5-bit, and 8-bit integer quantization. It can be used to generate realistic-sounding audio from text prompts.

PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

PyTorch Forecasting is a PyTorch-based package designed for state-of-the-art timeseries forecasting using deep learning architectures. It offers a high-level API and leverages PyTorch Lightning for efficient training on GPU or CPU with automatic logging. The package aims to simplify timeseries forecasting tasks by providing a flexible API for professionals and user-friendly defaults for beginners. It includes features such as a timeseries dataset class for handling data transformations, missing values, and subsampling, various neural network architectures optimized for real-world deployment, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. Built on pytorch-lightning, it supports training on CPUs, single GPUs, and multiple GPUs out-of-the-box.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

cellseg-models.pytorch is a Python library built upon PyTorch for 2D cell/nuclei instance segmentation models. It provides multi-task encoder-decoder architectures and post-processing methods for segmenting cell/nuclei instances. The library offers high-level API to define segmentation models, open-source datasets for training, flexibility to modify model components, sliding window inference, multi-GPU inference, benchmarking utilities, regularization techniques, and example notebooks for training and finetuning models with different backbones.

SeerAttention is a novel trainable sparse attention mechanism that learns intrinsic sparsity patterns directly from LLMs through self-distillation at post-training time. It achieves faster inference while maintaining accuracy for long-context prefilling. The tool offers features such as trainable sparse attention, block-level sparsity, self-distillation, efficient kernel, and easy integration with existing transformer architectures. Users can quickly start using SeerAttention for inference with AttnGate Adapter and training attention gates with self-distillation. The tool provides efficient evaluation methods and encourages contributions from the community.

docker-h5ai is a Docker image that provides a modern file indexer for HTTP web servers, enhancing file browsing with different views, a breadcrumb, and a tree overview. It is built on Alpine Linux with Nginx and PHP, supporting h5ai 0.30.0 and enabling PHP 8 JIT compiler. The image supports multiple architectures and can be used to host shared files with customizable configurations. Users can set up authentication using htpasswd and run the image as a real-time service. It is recommended to use HTTPS for data encryption when deploying the service.

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

At Nesa, privacy is a critical objective. Equivariant Encryption (EE) is a solution developed to perform inference on neural networks without exposing input and output data. EE integrates specialized transformations for neural networks, maintaining data privacy while ensuring inference operates correctly on encrypted inputs. It provides the same latency as plaintext inference with no slowdowns and offers strong security guarantees. EE avoids the computational costs of traditional Homomorphic Encryption (HE) by preserving non-linear neural functions. The tool is designed for modern neural architectures, ensuring accuracy, scalability, and compatibility with existing pipelines.

AI Engineering Academy aims to provide a structured learning path for individuals looking to learn Applied AI effectively. The platform offers multiple roadmaps covering topics like Retrieval Augmented Generation, Fine-tuning, and Deployment. Each roadmap equips learners with the knowledge and skills needed to excel in applied GenAI. Additionally, the platform will feature Hands-on End-to-End AI projects in the future.

Guides in designing, implementing, and maintaining technical architecture.

Guides the development and implementation of IT systems architecture.

Designs and manages technical solutions to meet business needs.

Expert in microfrontend architecture, guiding through trends, best practices, and challenges of complex, scalable UI integrations.

Expert in software architecture, ensuring integrity and scalability through best practices.

Japanese-first, young GCP expert with AI diagrams.

A strategic approach of thinking when designing software.

An expert in the technical, organizational, infrastructural and personnel aspects of information security management systems (ISMS)

First discusses assistant details, then implements tailored code solutions.

Expert in data encoding schemes

Your personal Meteor.js dev assistant and consultant

Guides users on Oracle EPM Cloud services and tasks.

Versatile IoT expertise for advice, explanations, and troubleshooting

Expert in backend development and file handling.

Implement specific web applications based on sketches submitted by users

Provides concise GC troubleshooting and method development advice that is easy to implement.

Your proactive virtual CTO, ready to implement requests

Assists in enhancing e-commerce sites for better conversions with tailored, easy-to-implement advice.

Insurance providers collect and process personal health, financial, and property information, making it crucial to implement comprehensive data protection strategies.

Agente de IA especializado em Proteção de Dados