Best AI tools for< Boost Performance >

Allego Conversation Intelligence is an AI-powered platform that helps revenue teams enhance performance and revenue by analyzing sales conversations. The platform enables users to capture, review, coach, and share valuable insights from conversations with customers. It leverages AI-driven analysis to reveal successful outcomes and provides data-driven performance coaching to improve sales performance. Allego Conversation Intelligence allows users to search, filter, and leverage call intelligence to uncover key moments that impact revenue. Trusted by top companies, the platform offers integrations with existing systems and resources for modern sales teams.

Simpleem is an Artificial Emotional Intelligence (AEI) tool that helps users uncover intentions, predict success, and leverage behavior for successful interactions. By measuring all interactions and correlating them with concrete outcomes, Simpleem provides insights into verbal, para-verbal, and non-verbal cues to enhance customer relationships, track customer rapport, and assess team performance. The tool aims to identify win/lose patterns in behavior, guide users on boosting performance, and prevent burnout by promptly identifying red flags. Simpleem uses proprietary AI models to analyze real-world data and translate behavioral insights into concrete business metrics, achieving a high accuracy rate of 94% in success prediction.

EmbedAI is an AI tool designed to enhance websites by enabling JavaScript functionalities. It allows users to embed AI-powered features seamlessly into their web pages, enhancing user experience and interactivity. With EmbedAI, website owners can easily integrate advanced AI capabilities without the need for extensive coding knowledge. The tool streamlines the process of incorporating AI elements, making it accessible to a wider range of users.

More Views AI is an AI tool designed to help YouTube content creators increase their view count by testing different video settings. The tool uses artificial intelligence to analyze video titles, suggest variations, and run A/B tests to determine the best-performing title. It offers features such as automatic A/B toggling, performance tracking, views optimization, AI-generated title suggestions, and thumbnail testing. Users can connect their YouTube account, set up experiments in seconds, and let the algorithm optimize their video titles to attract more views.

Axon is an AI-powered study and test prep platform designed specifically for the USMLE exam. It offers a comprehensive and personalized approach to help students study smarter, not harder. With a focus on efficiency and effectiveness, Axon aims to enhance the learning experience for medical students preparing for their exams. The platform provides a range of study resources, practice questions, and personalized study plans to optimize exam preparation and boost performance.

SweetRush is a corporate training and eLearning company that provides custom learning solutions, talent solutions, XR immersive tech for learning, voiceover services, and support for nonprofits. They specialize in creating engaging and effective learning programs that help businesses thrive. SweetRush has been recognized for its excellence in learning and development, winning numerous awards for its innovative and impactful work.

VoiceLine is an AI-based field sales revenue intelligence tool designed to enhance the efficiency and productivity of field sales teams. It allows users to capture touchpoints using voice commands, automate administrative tasks, and gain actionable insights directly from the field. With advanced speech recognition and offline functionality, VoiceLine offers hands-free operation and superior data quality. The tool integrates seamlessly with various systems, providing customizable automations and actionable insights for better decision-making. VoiceLine prioritizes data security and GDPR compliance, ensuring user privacy and control over their data.

Enthu.AI is a Conversation Intelligence Software designed for Contact Centers to boost agent performance, understand customer sentiment, and improve revenue. The AI-powered tool automates sales monitoring, compliance, and customer experience enhancement by capturing and analyzing customer voice across various communication channels. It provides insights for multiple teams, runs automated Quality Management programs, and coaches sales agents to improve their performance. Enthu.AI helps in driving consistency in revenue and predictability in outcomes for over 100 brands, making call quality monitoring and customer conversation data analysis more efficient and effective.

Spinify is an AI-powered sales gamification platform that injects energy and excitement into daily sales activities by combining the power of Gamification and AI. It helps in turning targets into achievements, quotas into conquests, and challenges into opportunities. Spinify enhances sales performance through quantifiable results, measurable impact, and tangible transformations for diverse businesses. The platform offers features such as SpinifyGPT - Sidekick AI Platform, gamification leaderboards, competitions & visibility, recognition & fun, metrics & targets, and TV, web, & mobile coaching.

Cuecard is an AI-powered sales co-pilot tool designed to revolutionize the sales process by providing AI-driven knowledge and personalized experiences to help sales teams close deals faster. It offers features such as interactive outreach, efficient research, real-time answers, centralized knowledge access, and improved sales velocity. Cuecard is trusted by leading brands of all sizes and offers a live demo for users to experience its innovative features firsthand.

Invoca is a Conversation Intelligence AI Leader that offers a Revenue Execution Platform to help marketing, sales, and contact centers drive more revenue. The platform provides solutions for call tracking, artificial intelligence, and interaction management. It integrates with Google, social advertising platforms, and offers APIs & webhooks. Invoca caters to various industries such as automotive, financial services, healthcare, insurance, retail, telecom, and travel & hospitality. The platform helps optimize ad spend, boost campaign performance, prioritize high-value callers, improve agent performance, and streamline data activation.

Vidalgo is an AI-powered platform that enables users to effortlessly create captivating vertical videos for TikTok. With Vidalgo, users can turn their ideas into viral content without the need for technical skills. The platform simplifies the video creation process by leveraging artificial intelligence to compose scripts, select images, and assemble videos in minutes. Vidalgo offers unmatched ease and speed, boosted creativity, and reduced editing time, making it a valuable tool for content creators looking to enhance their TikTok performance.

Refleta is an AI-powered image enhancement tool designed to transform product photos into high-quality, sales-boosting images for e-commerce businesses. It utilizes advanced AI algorithms to enhance product imagery across various industries, improving SEO, customer engagement, and online sales performance. With features like platform independence, intelligent AI enhancement, and smart image transformation, Refleta helps businesses stand out in search results and increase click-through rates. The tool offers a user-friendly interface, cloud-based service, and a subscription model with flexible pricing options. Refleta also provides enterprise solutions for large-scale operations and personalized support to meet unique business needs.

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.

Nexa is an autonomous AI tool designed for Sales and Marketing teams. It uses AI agents to unify data from various tools, generating valuable insights to enhance sales performance and optimize marketing spend. The platform is built for high-growth startups post Series A funding, offering seamless data integration and instant access to revenue-driving insights. Nexa aims to streamline data analysis processes and boost productivity by providing a user-friendly interface and customizable features.

Gizmo is an AI-powered learning application designed to make studying easy and enjoyable for students of all levels. It offers A.I. quizzes that help users learn and retain information effectively. The app is created by Cambridge alumni and has gained popularity among students for its innovative approach to learning. With features like spaced repetition, active recall, and the ability to turn study materials into flashcards, Gizmo aims to enhance the learning experience and improve academic performance.

ListenUp! is an AI-powered discovery tool designed for busy product teams to streamline the process of collecting and analyzing user feedback. The application automatically centralizes user feedback, orders it, and scales the process with AI technology. It helps product teams understand their users better, make informed decisions, and deliver more value efficiently. ListenUp! offers features such as automated feedback capture, real-time pattern suggestions, and transcribing user interviews with multiple speakers. The tool aims to enhance user understanding, improve product development, and boost team performance.

PricingMix AI is an AI retail application that leverages Artificial Intelligence and Machine Learning-powered insights to deliver accurate pricing strategies. It offers a Custom Pricing Analysis and Recommendation Strategy to ensure Maximum Profit while competing online. The application provides 360 Degree SKU Level Intelligence, real-time competitor pricing data, inventory intelligence, and powerful dashboards for comprehensive insights into pricing and profitability.

NetGeist is an AI tool that offers Natural Language Processing solutions to tackle textual challenges by automating, processing, and summarizing information. It provides various applications such as app review tracking, HR strategy shaping, stock market sentiment analysis, and custom chatbots. NetGeist aims to create tailor-made NLP solutions for different industries, leveraging AI technologies to enhance workflow efficiency and decision-making processes.

Open Tutor App is an AI-powered Homework Helper designed to assist students in solving homework questions efficiently. The app allows users to take a photo of their homework, which is then analyzed by AI to provide step-by-step solutions and explanations. With features like scanning and solving homework questions, Open Tutor App aims to enhance learning experiences and boost academic performance. The application is available for download on Google Play, App Store, and Web platforms.

BentoDiffusion is a BentoML example project that demonstrates how to serve and deploy diffusion models in the Stable Diffusion (SD) family. These models are specialized in generating and manipulating images based on text prompts. The project provides a guide on using SDXL Turbo as an example, along with instructions on prerequisites, installing dependencies, running the BentoML service, and deploying to BentoCloud. Users can interact with the deployed service using Swagger UI or other methods. Additionally, the project offers the option to choose from various diffusion models available in the repository for deployment.

Indexify is an open-source engine for building fast data pipelines for unstructured data (video, audio, images, and documents) using reusable extractors for embedding, transformation, and feature extraction. LLM Applications can query transformed content friendly to LLMs by semantic search and SQL queries. Indexify keeps vector databases and structured databases (PostgreSQL) updated by automatically invoking the pipelines as new data is ingested into the system from external data sources. **Why use Indexify** * Makes Unstructured Data **Queryable** with **SQL** and **Semantic Search** * **Real-Time** Extraction Engine to keep indexes **automatically** updated as new data is ingested. * Create **Extraction Graph** to describe **data transformation** and extraction of **embedding** and **structured extraction**. * **Incremental Extraction** and **Selective Deletion** when content is deleted or updated. * **Extractor SDK** allows adding new extraction capabilities, and many readily available extractors for **PDF**, **Image**, and **Video** indexing and extraction. * Works with **any LLM Framework** including **Langchain**, **DSPy**, etc. * Runs on your laptop during **prototyping** and also scales to **1000s of machines** on the cloud. * Works with many **Blob Stores**, **Vector Stores**, and **Structured Databases** * We have even **Open Sourced Automation** to deploy to Kubernetes in production.

Cleanlab helps you **clean** data and **lab** els by automatically detecting issues in a ML dataset. To facilitate **machine learning with messy, real-world data** , this data-centric AI package uses your _existing_ models to estimate dataset problems that can be fixed to train even _better_ models.

The 'local-talking-llm' repository provides a tutorial on building a voice assistant similar to Jarvis or Friday from Iron Man movies, capable of offline operation on a computer. The tutorial covers setting up a Python environment, installing necessary libraries like rich, openai-whisper, suno-bark, langchain, sounddevice, pyaudio, and speechrecognition. It utilizes Ollama for Large Language Model (LLM) serving and includes components for speech recognition, conversational chain, and speech synthesis. The implementation involves creating a TextToSpeechService class for Bark, defining functions for audio recording, transcription, LLM response generation, and audio playback. The main application loop guides users through interactive voice-based conversations with the assistant.

AI Study Assistant is an app designed to enhance learning experience and boost academic performance. It serves as a personal tutor, lecture summarizer, writer, and question generator powered by Google PaLM 2. Features include interacting with an AI chatbot, summarizing lectures, generating essays, and creating practice questions. The app is built using 100% Kotlin, Jetpack Compose, Clean Architecture, and MVVM design pattern, with technologies like Ktor, Room DB, Hilt, and Kotlin coroutines. AI Study Assistant aims to provide comprehensive AI-powered assistance for students in various academic tasks.

ProX is a lm-based data refinement framework that automates the process of cleaning and improving data used in pre-training large language models. It offers better performance, domain flexibility, efficiency, and cost-effectiveness compared to traditional methods. The framework has been shown to improve model performance by over 2% and boost accuracy by up to 20% in tasks like math. ProX is designed to refine data at scale without the need for manual adjustments, making it a valuable tool for data preprocessing in natural language processing tasks.

XLang™ is a cutting-edge language designed for AI and IoT applications, offering exceptional dynamic and high-performance capabilities. It excels in distributed computing and seamless integration with popular languages like C++, Python, and JavaScript. Notably efficient, running 3 to 5 times faster than Python in AI and deep learning contexts. Features optimized tensor computing architecture for constructing neural networks through tensor expressions. Automates tensor data flow graph generation and compilation for specific targets, enhancing GPU performance by 6 to 10 times in CUDA environments.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

ALMA (Advanced Language Model-based Translator) is a many-to-many LLM-based translation model that utilizes a two-step fine-tuning process on monolingual and parallel data to achieve strong translation performance. ALMA-R builds upon ALMA models with LoRA fine-tuning and Contrastive Preference Optimization (CPO) for even better performance, surpassing GPT-4 and WMT winners. The repository provides ALMA and ALMA-R models, datasets, environment setup, evaluation scripts, training guides, and data information for users to leverage these models for translation tasks.

The Universal Numbers Library is a header-only C++ template library designed for universal number arithmetic, offering alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. It tailors arithmetic types to the application's precision and dynamic range, enabling improved application performance and energy efficiency. The library provides fast implementations of special IEEE-754 formats like quarter precision, half-precision, and quad precision, as well as vendor-specific extensions. It supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval, and adaptive-precision integers, rationals, and floats. The library is suitable for AI, DSP, HPC, and HFT algorithms.

AWQ (Activation-aware Weight Quantization) is a tool designed for efficient and accurate low-bit weight quantization (INT3/4) for Large Language Models (LLMs). It supports instruction-tuned models and multi-modal LMs, providing features such as AWQ search for accurate quantization, pre-computed AWQ model zoo for various LLMs, memory-efficient 4-bit linear in PyTorch, and efficient CUDA kernel implementation for fast inference. The tool enables users to run large models on resource-constrained edge platforms, delivering more efficient responses with LLM/VLM chatbots through 4-bit inference.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

AutoRound is an advanced weight-only quantization algorithm for low-bits LLM inference. It competes impressively against recent methods without introducing any additional inference overhead. The method adopts sign gradient descent to fine-tune rounding values and minmax values of weights in just 200 steps, often significantly outperforming SignRound with the cost of more tuning time for quantization. AutoRound is tailored for a wide range of models and consistently delivers noticeable improvements.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

TensorRT-LLM is an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM contains components to create Python and C++ runtimes that execute those TensorRT engines. It also includes a backend for integration with the NVIDIA Triton Inference Server; a production-quality system to serve LLMs. Models built with TensorRT-LLM can be executed on a wide range of configurations going from a single GPU to multiple nodes with multiple GPUs (using Tensor Parallelism and/or Pipeline Parallelism).

WilmerAI is a middleware system designed to process prompts before sending them to Large Language Models (LLMs). It categorizes prompts, routes them to appropriate workflows, and generates manageable prompts for local models. It acts as an intermediary between the user interface and LLM APIs, supporting multiple backend LLMs simultaneously. WilmerAI provides API endpoints compatible with OpenAI API, supports prompt templates, and offers flexible connections to various LLM APIs. The project is under heavy development and may contain bugs or incomplete code.

LLM4Opt is a collection of references and papers focusing on applying Large Language Models (LLMs) for diverse optimization tasks. The repository includes research papers, tutorials, workshops, competitions, and related collections related to LLMs in optimization. It covers a wide range of topics such as algorithm search, code generation, machine learning, science, industry, and more. The goal is to provide a comprehensive resource for researchers and practitioners interested in leveraging LLMs for optimization tasks.

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