Best AI tools for< Improve Order Efficiency >

Presto is an AI-driven automation tool designed for drive-thru restaurants to improve staff productivity, increase revenue, and enhance the guest experience. With over 15 years of industry experience, Presto is the most popular automation solution for drive-thru restaurants. It offers a powerful spectrum of Voice AI to optimize staff efficiency, supercharge upselling, improve order accuracy, and accelerate service.

Vic.ai is an AI-powered accounting software designed to streamline invoice processing, purchase order matching, approval flows, payments, analytics, and insights. The platform offers autonomous finance solutions that optimize accounts payable processes, achieve lasting ROI, and enable informed decision-making. Vic.ai leverages AI technology to enhance productivity, accuracy, and efficiency in accounting workflows, reducing manual tasks and improving overall financial operations.

Brightpick is an AI-powered order fulfillment solution that revolutionizes warehouse operations by enabling fully automated order picking, consolidation, and dispatch. The Brightpick Autopicker, equipped with AI robots, streamlines the fulfillment process by efficiently picking a wide range of products, from groceries to pharmaceuticals, with precision and speed. Trusted by industry leaders, Brightpick helps businesses cut costs, increase efficiency, and enhance customer service in industries such as Ecommerce, 3PL, E-Grocery, and Medical. With its innovative technology and award-winning solutions, Brightpick is reshaping the future of order fulfillment.

Automaited is an AI application that offers Ada - an AI Agent for automating order processing. Ada handles orders from receipt to ERP entry, extracting, validating, and transferring data to ensure accuracy and efficiency. The application utilizes state-of-the-art AI technology to streamline order processing, saving time, reducing errors, and enabling users to focus on customer satisfaction. With seamless automation, Ada integrates into ERP systems, making order processing effortless, quick, and cost-efficient. Automaited provides tailored automations to make operational processes up to 70% more efficient, enhancing performance and reducing error rates.

SiteRecon is an AI-powered mapping tool designed for landscapers, offering features such as automated takeoffs, site condition reports, job plans, account management, and enhancement proposals. It helps landscapers streamline their sales process, improve productivity, and enhance client relations by providing accurate measurements, detailed site audits, and work reports. SiteRecon aims to revolutionize the landscaping industry by leveraging AI technology to simplify property mapping, estimate generation, and job management, ultimately leading to increased efficiency and profitability for landscaping businesses.

Brilo AI is an AI phone call agent application designed for customer support and sales. It offers human-like AI phone calls to businesses of any size, enabling them to boost customer satisfaction, cut costs, and operate 24/7 without the need for a technical team. The application seamlessly integrates with over 6,000 apps and ensures regulatory compliance for every call. Brilo AI is tailored for various industries such as ecommerce, hospitality, healthcare, real estate, logistics, financial services, and small businesses, providing call automation and efficiency in handling tasks like order tracking, reservations, appointments, and inquiries.

MOM AI Restaurant Assistant is an innovative AI tool designed to transform restaurants by automating ordering processes, enhancing online presence, and providing cost-effective solutions. It offers features such as simple registration, in-store and online deployment, real-time order notifications, and flexible pricing. The application helps restaurants improve efficiency, reduce manual work, and increase customer engagement through AI technology.

Voiceplug.ai is an AI-powered food ordering system designed for restaurants. It offers various AI solutions such as Phone AI, Drive-Thru AI, Kiosk AI, and PizzaVoice, each tailored to enhance customer experience, increase revenue, and boost operational efficiency. The system ensures personalized conversations, efficient order taking, and targeted customer engagement through natural conversations and AI-driven upselling. Voiceplug.ai empowers restaurant owners to streamline their operations, reduce labor costs, and improve customer service by leveraging the capabilities of Voice AI technology.

Prooftiles is a platform designed to help businesses increase their conversion rate and average order value. It offers a suite of tools and features to optimize sales processes and enhance customer experience. With Prooftiles, businesses can access DocsLM to streamline document management and improve efficiency. The platform also provides pricing information, integrations with other tools, and valuable insights through its blog section.

Inspectr is an AI-powered intelligence engine designed for real estate operations. It integrates with existing tech stacks to provide real-time, actionable insights that reduce costs, improve efficiency, and drive higher returns across portfolios. Inspectr turns fragmented data into predictive intelligence, optimizing spend, budgets, and maximizing Net Operating Income (NOI) without disrupting current systems. The platform offers features like real-time strategic intelligence, seamless integrations, and work order enrichment to streamline operations and enhance asset performance.

Locale is an AI-powered platform that enables businesses to automate their business processes using AI agents. It allows users to build AI workflows for various business functions such as marketing, sales, payments, and operations. With features like AI workflow builder, drag-and-drop and SQL builders, and integrations with popular tools like Slack and Zendesk, Locale helps in streamlining processes and increasing team productivity. The platform offers advanced features like AI Copilot, drag-&-drop Workflow Builder, SQL for complex Use Cases, and Human-in-the-loop Steps to enhance automation capabilities. Locale has been successfully used by companies to optimize workflows, reduce manual effort, and improve operational efficiency.

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.

Choco is an AI-powered platform designed for distributors and restaurants to streamline order processing and management. With Choco AI, orders from various sources like voicemails, SMS, emails, and third-party providers are automatically processed into the ERP system within seconds. The platform aims to enhance operational efficiency, reduce manual work and errors, improve customer satisfaction, and minimize waste in the food supply industry. Choco offers features such as digital order processing, AI-CRM solutions, marketing assistance, team management, and access to a comprehensive product catalog.

Kinaxis is an AI-powered platform that offers end-to-end supply chain orchestration solutions for businesses. It helps companies respond with agility by coordinating all parts of the supply chain using artificial intelligence. With features like transparency, collaboration, adaptability, and intelligence, Kinaxis enables users to make faster, smarter, and more confident decisions. The platform offers solutions for supply chain control tower, S&OP, demand planning, inventory management, scheduling, order management, transportation, and returns management. Kinaxis is designed to streamline operations, improve efficiency, and drive sustainable supply chain practices.

Encounter AI is an automated ordering assistant designed specifically for restaurants and retail establishments. It aims to increase staff capacity and productivity by providing a robust voice solution to enhance the drive-thru experience. The AI technology enables operators to optimize existing resources, such as human capital or technology assets, to improve profitability. Encounter AI is 'kaizen' in nature, continuously learning through machine learning to stay updated on menu items and ordering preferences, ultimately enhancing the customer experience.

Five9 is a leading provider of cloud contact center software. We are driven by a passion to transform call and contact centers into customer engagement centers of excellence. Our AI-powered solutions help businesses deliver exceptional customer experiences, improve operational efficiency, and reduce costs. With Five9, you can: * Empower agents to deliver results anywhere * Improve CX with practical AI * Find efficiency with AI & automation * Scale with AI & digital workforce * Realize results with Five9

Sensi is an AI tool that provides care intelligence solutions for the healthcare industry. It offers caregiver oversight, holistic assessment, revenue-boosting insights, and data-backed intelligence to improve client care and business efficiency. Sensi aims to address the challenges faced by older adults, home care providers, and caregivers by leveraging AI technology for proactive care and better decision-making.

ReplyMind is an AI-powered tool that helps businesses automate customer support and sales processes. It uses natural language processing and machine learning algorithms to analyze customer queries and provide accurate responses in real-time. The tool can handle a wide range of tasks, from answering frequently asked questions to processing orders and scheduling appointments. With ReplyMind, businesses can improve efficiency, save time, and enhance customer satisfaction.

FormX.ai is an AI-powered data extraction and conversion tool that automates the process of extracting data from physical documents and converting it into digital formats. It supports a wide range of document types, including invoices, receipts, purchase orders, bank statements, contracts, HR forms, shipping orders, loyalty member applications, annual reports, business certificates, personnel licenses, and more. FormX.ai's pre-configured data extraction models and effortless API integration make it easy for businesses to integrate data extraction into their existing systems and workflows. With FormX.ai, businesses can save time and money on manual data entry and improve the accuracy and efficiency of their data processing.

Checkr is a comprehensive background screening platform for companies, offering a range of services including criminal background checks, employment verification, driving record checks, drug testing, and more. The platform is designed to streamline the hiring process, improve compliance, and enhance the candidate experience. Checkr caters to various industries and company sizes, providing AI-powered solutions and integrations to simplify background screening workflows.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

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.

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.

The 'unilm' repository is a collection of tools, models, and architectures for Foundation Models and General AI, focusing on tasks such as NLP, MT, Speech, Document AI, and Multimodal AI. It includes various pre-trained models, such as UniLM, InfoXLM, DeltaLM, MiniLM, AdaLM, BEiT, LayoutLM, WavLM, VALL-E, and more, designed for tasks like language understanding, generation, translation, vision, speech, and multimodal processing. The repository also features toolkits like s2s-ft for sequence-to-sequence fine-tuning and Aggressive Decoding for efficient sequence-to-sequence decoding. Additionally, it offers applications like TrOCR for OCR, LayoutReader for reading order detection, and XLM-T for multilingual NMT.

The Beta Machine Learning Toolkit is a package containing various algorithms and utilities for implementing machine learning workflows in multiple languages, including Julia, Python, and R. It offers a range of supervised and unsupervised models, data transformers, and assessment tools. The models are implemented entirely in Julia and are not wrappers for third-party models. Users can easily contribute new models or request implementations. The focus is on user-friendliness rather than computational efficiency, making it suitable for educational and research purposes.

Implementation of Double DQN reinforcement learning for OpenAI Gym environments with discrete action spaces. The algorithm aims to improve sample efficiency by using two uncorrelated Q-Networks to prevent overestimation of Q-values. By updating parameters periodically, the model reduces computation time and enhances training performance. The tool is based on the Double DQN method proposed by Hasselt in 2010.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project caches pre-generated model results to reduce response time for similar requests and enhance user experience. It integrates various embedding frameworks and local storage options, offering functionalities like cache-writing, cache-querying, and cache-clearing through RESTful API. The tool supports multi-tenancy, system commands, and multi-turn dialogue, with features for data isolation, database management, and model loading schemes. Future developments include data isolation based on hyperparameters, enhanced system prompt partitioning storage, and more versatile embedding models and similarity evaluation algorithms.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project facilitates sharing and exchanging technologies related to large model semantic cache through open-source collaboration.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

APOLLO is a memory-efficient optimizer designed for large language model (LLM) pre-training and full-parameter fine-tuning. It offers SGD-like memory cost with AdamW-level performance. The optimizer integrates low-rank approximation and optimizer state redundancy reduction to achieve significant memory savings while maintaining or surpassing the performance of Adam(W). Key contributions include structured learning rate updates for LLM training, approximated channel-wise gradient scaling in a low-rank auxiliary space, and minimal-rank tensor-wise gradient scaling. APOLLO aims to optimize memory efficiency during training large language models.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Magic CLI is a command line utility that leverages Large Language Models (LLMs) to enhance command line efficiency. It is inspired by projects like Amazon Q and GitHub Copilot for CLI. The tool allows users to suggest commands, search across command history, and generate commands for specific tasks using local or remote LLM providers. Magic CLI also provides configuration options for LLM selection and response generation. The project is still in early development, so users should expect breaking changes and bugs.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

Eino is an ultimate LLM application development framework in Golang, emphasizing simplicity, scalability, reliability, and effectiveness. It provides a curated list of component abstractions, a powerful composition framework, meticulously designed APIs, best practices, and tools covering the entire development cycle. Eino standardizes and improves efficiency in AI application development by offering rich components, powerful orchestration, complete stream processing, highly extensible aspects, and a comprehensive framework structure.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.

This project focuses on implementing Sparse Autoencoders (SAEs) for mechanistic interpretability in Large Language Models (LLMs) like Llama 3.2-3B. The SAEs aim to untangle superimposed representations in LLMs into separate, interpretable features for each neuron activation. The project provides an end-to-end pipeline for capturing training data, training the SAEs, analyzing learned features, and verifying results experimentally. It includes comprehensive logging, visualization, and checkpointing of SAE training, interpretability analysis tools, and a pure PyTorch implementation of Llama 3.1/3.2 chat and text completion. The project is designed for scalability, efficiency, and maintainability.

Given a set of Parameters, Provides a set of Order Recommendations

Manages office supplies to ensure smooth operations.

Aid in managing and optimizing OEM production orders in the auto industry.

Expert AI Doctor with up to date medical resources and textbooks to help improve your clinical skills.

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Gives you tips and suggestions on how you can improve your application for your users.

Upload a screenshot of your Tinder profile to improve it and get feedback

Improve your Ideas with First Principles Thinking

Offers exercises and techniques to improve memory retention and cognitive functions.

Generates conversation examples and chunks for specified situations. Improve your instantaneous conversational skills through repetitive practice!

Improve your physical & mental health

Analyzes customer churn and provides strategies to improve loyalty and retention.

Improve your curriculum telling chatgpt your cv and the desired job

Agile expert providing practical, step-by-step advice with the agile way of working of your team and organisation. Whether you're looking to improve your Agile skills or find solutions to specific problems. Including Scrum, Kanban and SAFe knowledge.

I improve objects with animals.

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Helps improve language skills through interactive scenarios and feedback.

I improve Dutch sentences, explain errors, and give tips.

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