Best AI tools for< Optimize Costs >

cloudNito is an AI-driven platform that specializes in cloud cost optimization and management for businesses using AWS services. The platform offers automated cost optimization, comprehensive insights and analytics, unified cloud management, anomaly detection, cost and usage explorer, recommendations for waste reduction, and resource optimization. By leveraging advanced AI solutions, cloudNito aims to help businesses efficiently manage their AWS cloud resources, reduce costs, and enhance performance.

Keebo is an AI tool designed for Snowflake optimization, offering automated query, cost, and tuning optimization. It is the only fully-automated Snowflake optimizer that dynamically adjusts to save customers 25% and more. Keebo's patented technology, based on cutting-edge research, optimizes warehouse size, clustering, and memory without impacting performance. It learns and adjusts to workload changes in real-time, setting up in just 30 minutes and delivering savings within 24 hours. The tool uses telemetry metadata for optimizations, providing full visibility and adjustability for complex scenarios and schedules.

AWS Docs GPT is an AI-powered search and chat tool designed specifically for AWS Documentation. It utilizes the power of artificial intelligence to enhance the user experience by providing accurate search results and interactive chat support. With Antimetal integration, users can optimize their AWS costs by up to 75% through AI-driven recommendations. The tool aims to streamline the process of navigating and understanding AWS documentation, making it easier for users to find relevant information and troubleshoot issues effectively.

PrimeOrbit is an AI-driven cloud cost optimization platform designed to empower operations and boost ROI for enterprises. The platform focuses on streamlining operations and simplifying cost management by delivering quality-centric solutions. It offers AI-driven optimization recommendations, automated cost allocation, and tailored FinOps for optimal efficiency and control. PrimeOrbit stands out by providing user-centric approach, superior AI recommendations, customization, and flexible enterprise workflow. It supports major cloud providers including AWS, Azure, and GCP, with full support for GCP and Kubernetes coming soon. The platform ensures complete cost allocation across cloud resources, empowering decision-makers to optimize cloud spending efficiently and effectively.

Lunary is an AI developer platform designed to bring AI applications to production. It offers a comprehensive set of tools to manage, improve, and protect LLM apps. With features like Logs, Metrics, Prompts, Evaluations, and Threads, Lunary empowers users to monitor and optimize their AI agents effectively. The platform supports tasks such as tracing errors, labeling data for fine-tuning, optimizing costs, running benchmarks, and testing open-source models. Lunary also facilitates collaboration with non-technical teammates through features like A/B testing, versioning, and clean source-code management.

Looker is a business intelligence platform that offers embedded analytics and AI-powered BI solutions. Leveraging Google's AI-led innovation, Looker delivers intelligent BI by combining foundational AI, cloud-first infrastructure, industry-leading APIs, and a flexible semantic layer. It allows users to build custom data experiences, transform data into integrated experiences, and create deeply integrated dashboards. Looker also provides a universal semantic modeling layer for unified, trusted data sources and offers self-service analytics capabilities through Looker and Looker Studio. Additionally, Looker features Gemini, an AI-powered analytics assistant that accelerates analytical workflows and offers a collaborative and conversational user experience.

PredictModel is an AI tool that specializes in creating custom Machine Learning models tailored to meet unique requirements. The platform offers a comprehensive three-step process, including generating synthetic data, training ML models, and deploying them to AWS. PredictModel helps businesses streamline processes, improve customer segmentation, enhance client interaction, and boost overall business performance. The tool maximizes accuracy through customized synthetic data generation and saves time and money by providing expert ML engineers. With a focus on automated lead prioritization, fraud detection, cost optimization, and planning, PredictModel aims to stay ahead of the curve in the ML industry.

Reality AI Software is an Edge AI software development environment that combines advanced signal processing, machine learning, and anomaly detection on every MCU/MPU Renesas core. The software is underpinned by the proprietary Reality AI ML algorithm that delivers accurate and fully explainable results supporting diverse applications. It enables features like equipment monitoring, predictive maintenance, and sensing user behavior and the surrounding environment with minimal impact on the Bill of Materials (BoM). Reality AI software running on Renesas processors helps deliver endpoint intelligence in products across various markets.

Pump is an AI-powered group buying platform that helps startups save up to 60% on cloud computing costs. By leveraging artificial intelligence, Pump offers discounts previously only available to large companies, making cloud cost savings accessible to smaller businesses. The platform uses automated AI to find and apply the best savings for users, ensuring a seamless and efficient experience. Pump also provides secure AWS protection and innovative support through PumpGPT. With a focus on transparency and customer value, Pump continues to be a free product for its customers, delivering significant savings from day one.

Creatus.AI is an AI-powered platform that provides a range of tools and services to help businesses boost productivity and transform their workplaces. With over 35 AI models and tools, and 90+ business integrations, Creatus.AI offers a comprehensive suite of solutions for businesses of all sizes. The platform's AI-native workspace and autonomous team members enable businesses to automate tasks, improve efficiency, and gain valuable insights from data. Creatus.AI also specializes in custom AI integrations and solutions, helping businesses to tailor AI solutions to their specific needs.

Granica AI is a Training Data Platform designed to make data safe for use with AI while keeping it cost-efficient. It offers state-of-the-art accuracy, cost-efficient data optimization, data visibility insights, and cloud cost savings. The platform helps in protecting data privacy, optimizing data costs, and gaining data visibility for AI teams to achieve big results while minimizing privacy risk.

Salad is a distributed GPU cloud platform that offers fully managed and massively scalable services for AI applications. It provides the lowest priced AI transcription in the market, with features like image generation, voice AI, computer vision, data collection, and batch processing. Salad democratizes cloud computing by leveraging consumer GPUs to deliver cost-effective AI/ML inference at scale. The platform is trusted by hundreds of machine learning and data science teams for its affordability, scalability, and ease of deployment.

IBM MediaCenter is an AI tool designed to provide a wide range of solutions in the fields of corporate marketing, blockchain, data, and AI. The platform offers services related to industry-specific technologies, IoT, security, supply chain management, and systems management. With a focus on Watson AI technology, IBM MediaCenter aims to help businesses modernize, collect, organize, analyze, and infuse AI into their operations. The platform also offers technical support, developer support, and training programs for various IBM products and solutions.

Rafay is an AI-powered platform that accelerates cloud-native and AI/ML initiatives for enterprises. It provides automation for Kubernetes clusters, cloud cost optimization, and AI workbenches as a service. Rafay enables platform teams to focus on innovation by automating self-service cloud infrastructure workflows.

PoplarML is a platform that enables the deployment of production-ready, scalable ML systems with minimal engineering effort. It offers one-click deploys, real-time inference, and framework agnostic support. With PoplarML, users can seamlessly deploy ML models using a CLI tool to a fleet of GPUs and invoke their models through a REST API endpoint. The platform supports Tensorflow, Pytorch, and JAX models.

Restoke is a restaurant process automation and team management tool designed to streamline restaurant operations. It offers AI-powered food and recipe costing, live inventory and stock management, one-click ordering from suppliers, team management procedures, and integrations for POS, accounting, and rostering. Restoke helps restaurants automate their entire operation, save time and brainpower, and improve efficiency. It is a user-friendly platform that replaces traditional methods like spreadsheets and checklists, making it easy to manage staff, ensure health and safety compliance, and optimize food costs. With over 10,000 hospitality professionals trusting Restoke, it is a comprehensive solution for restaurant management.

Just Walk Out technology is a checkout-free shopping experience that allows customers to enter a store, grab whatever they want, and quickly get back to their day, without having to wait in a checkout line or stop at a cashier. The technology uses camera vision and sensor fusion, or RFID technology which allows them to simply walk away with their items. Just Walk Out technology is designed to increase revenue with cost-optimized technology, maximize space productivity, increase throughput, optimize operational costs, and improve shopper loyalty.

CareFlick is an AI-powered senior living software platform designed to empower caregivers in managing day-to-day caregiving tasks efficiently. It offers personalized recommendations, insights, and coordination tools to enhance the quality of care and streamline operations for senior care companies. CareFlick aims to reduce employee turnover, optimize operational costs, and improve resident and caregiver achievements through innovative AI technologies and smart care management features.

EverSQL is an AI-powered SQL query optimizer and database observability tool that specializes in optimizing PostgreSQL and MySQL databases. It offers automatic SQL query optimization, ongoing performance insights, and cost reduction recommendations. With over 100,000 professionals trusting EverSQL, it aims to save time and improve database performance by making SQL queries faster and more efficient.

OtterTune was a database tuning service start-up founded by Carnegie Mellon University. Unfortunately, the company is no longer operational. The founder, DJ OT, is currently in prison for a parole violation. Despite its closure, OtterTune was known for its innovative approach to database tuning. The website now serves as a research archive and provides access to its GitHub repository.

LLM price compass is an open-source tool for comparing inference costs on different GPUs across various cloud providers. It collects benchmark data to help users select the right GPU, cloud, and provider for their models. The project aims to provide insights into fixed per token costs from different providers, aiding in decision-making for model deployment.

GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks. It can produce detailed, factual, and unbiased research reports with customization options. The tool addresses issues of speed, determinism, and reliability by leveraging parallelized agent work. The main idea involves running 'planner' and 'execution' agents to generate research questions, seek related information, and create research reports. GPT Researcher optimizes costs and completes tasks in around 3 minutes. Features include generating long research reports, aggregating web sources, an easy-to-use web interface, scraping web sources, and exporting reports to various formats.

OptScale is an open-source FinOps and MLOps platform that provides cloud cost optimization for all types of organizations and MLOps capabilities like experiment tracking, model versioning, ML leaderboards.

Cursor Lens is an open-source tool that acts as a proxy between Cursor and various AI providers, logging interactions and providing detailed analytics to help developers optimize their use of AI in their coding workflow. It supports multiple AI providers, captures and logs all requests, provides visual analytics on AI usage, allows users to set up and switch between different AI configurations, offers real-time monitoring of AI interactions, tracks token usage, estimates costs based on token usage and model pricing. Built with Next.js, React, PostgreSQL, Prisma ORM, Vercel AI SDK, Tailwind CSS, and shadcn/ui components.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

AI-Drug-Discovery-Design is a repository focused on Artificial Intelligence-assisted Drug Discovery and Design. It explores the use of AI technology to accelerate and optimize the drug development process. The advantages of AI in drug design include speeding up research cycles, improving accuracy through data-driven models, reducing costs by minimizing experimental redundancies, and enabling personalized drug design for specific patients or disease characteristics.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

BoCoEL is a tool that leverages Bayesian Optimization to efficiently evaluate large language models by selecting a subset of the corpus for evaluation. It encodes individual entries into embeddings, uses Bayesian optimization to select queries, retrieves from the corpus, and provides easily managed evaluations. The tool aims to reduce computation costs during evaluation with a dynamic budget, supporting models like GPT2, Pythia, and LLAMA through integration with Hugging Face transformers and datasets. BoCoEL offers a modular design and efficient representation of the corpus to enhance evaluation quality.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

PromptAgent is a repository for a novel automatic prompt optimization method that crafts expert-level prompts using language models. It provides a principled framework for prompt optimization by unifying prompt sampling and rewarding using MCTS algorithm. The tool supports different models like openai, palm, and huggingface models. Users can run PromptAgent to optimize prompts for specific tasks by strategically sampling model errors, generating error feedbacks, simulating future rewards, and searching for high-reward paths leading to expert prompts.

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

The CryptoToken-Sender-Airdrop-Staking-Liquidity repository provides an ultimate tool for efficient and automated token distribution across blockchain wallets. It is designed for projects, DAOs, and blockchain-based organizations that need to distribute tokens to thousands of wallet addresses with ease. The platform offers advanced integrations with DeFi protocols for staking, liquidity farming, and automated payments. Users can send tokens in bulk, distribute tokens to multiple wallets instantly, optimize gas fees, integrate with DeFi protocols for liquidity provision and staking, set up recurring payments, automate liquidity farming strategies, support multi-chain operations, monitor transactions in real-time, and work with various token standards. The repository includes features for connecting to blockchains, importing and managing wallets, customizing mailing parameters, monitoring transaction status, logging transactions, and providing a user-friendly interface for configuration and operation.

DevOpsGPT is an AI-driven software development automation solution that combines Large Language Models (LLM) with DevOps tools to convert natural language requirements into working software. It improves development efficiency by eliminating the need for tedious requirement documentation, shortens development cycles, reduces communication costs, and ensures high-quality deliverables. The Enterprise Edition offers features like existing project analysis, professional model selection, and support for more DevOps platforms. The tool automates requirement development, generates interface documentation, provides pseudocode based on existing projects, facilitates code refinement, enables continuous integration, and supports software version release. Users can run DevOpsGPT with source code or Docker, and the tool comes with limitations in precise documentation generation and understanding existing project code. The product roadmap includes accurate requirement decomposition, rapid import of development requirements, and integration of more software engineering and professional tools for efficient software development tasks under AI planning and execution.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

FeedGen is an open-source tool that uses Google Cloud's state-of-the-art Large Language Models (LLMs) to improve product titles, generate more comprehensive descriptions, and fill missing attributes in product feeds. It helps merchants and advertisers surface and fix quality issues in their feeds using Generative AI in a simple and configurable way. The tool relies on GCP's Vertex AI API to provide both zero-shot and few-shot inference capabilities on GCP's foundational LLMs. With few-shot prompting, users can customize the model's responses towards their own data, achieving higher quality and more consistent output. FeedGen is an Apps Script based application that runs as an HTML sidebar in Google Sheets, allowing users to optimize their feeds with ease.

SuperAGI is an open-source framework designed to build, manage, and run autonomous AI agents. It enables developers to create production-ready and scalable agents, extend agent capabilities with toolkits, and interact with agents through a graphical user interface. The framework allows users to connect to multiple Vector DBs, optimize token usage, store agent memory, utilize custom fine-tuned models, and automate tasks with predefined steps. SuperAGI also provides a marketplace for toolkits that enable agents to interact with external systems and third-party plugins.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

PEFT (Parameter-Efficient Fine-Tuning) is a collection of state-of-the-art methods that enable efficient adaptation of large pretrained models to various downstream applications. By only fine-tuning a small number of extra model parameters instead of all the model's parameters, PEFT significantly decreases the computational and storage costs while achieving performance comparable to fully fine-tuned models.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

GuideLLM is a powerful tool for evaluating and optimizing the deployment of large language models (LLMs). By simulating real-world inference workloads, GuideLLM helps users gauge the performance, resource needs, and cost implications of deploying LLMs on various hardware configurations. This approach ensures efficient, scalable, and cost-effective LLM inference serving while maintaining high service quality. Key features include performance evaluation, resource optimization, cost estimation, and scalability testing.

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Frost Protection System is an AI bot optimizing open field farming of fruits, vegetables, and flowers, combining real-time data and AI to boost yield, cut costs, and foster sustainable practices in a user-friendly interface.

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