Best AI tools for< Improve Value Propositions >

ValueProp.Dev is an AI-powered tool designed to help businesses create a Value Proposition Canvas based on their company description. The tool assists in identifying customer jobs, pains, and gains, as well as pain relievers and gain creators to develop a compelling value proposition. By leveraging AI technology, ValueProp.Dev streamlines the process of value proposition creation, enabling businesses to better understand and address the needs of their target customers.

Heatseeker is an AI-powered market experimentation tool that helps businesses predict customer preferences, conduct feature tests, and generate value propositions. It enables users to answer critical growth questions about market, audience, and product features through AI-powered experiments. Heatseeker provides insights into market trends, competitor analysis, and helps in making data-driven decisions. The platform offers curated recommendations, competitive intelligence, and continuous testing for refining strategies. It automates ad campaign generation, data collection, and provides recommendations for launching new products. Heatseeker is designed to help businesses optimize their marketing efforts and improve their product offerings.

Technica Industrial AI is a leading AI application provider offering cutting-edge AI solutions tailored to meet the unique needs of businesses. They specialize in AI-driven solutions that accelerate transformation processes and enable paradigm shifts beyond traditional business frameworks. With expertise in AI consulting services, data-driven solutions, and AI transformation, Technica Industrial AI helps companies across various industries solve business challenges and create new value propositions through the integration of AI technologies.

Prompt Genie is a powerful tool that helps you generate high-quality prompts for ChatGPT. With Prompt Genie, you can easily create prompts for a wide variety of tasks, including crafting video hooks, improving video scripts, creating ideal customer profiles, finding value propositions, creating brand identities, marketing plans, copywriting using the PAS Framework, creating lesson outlines, and writing argumentative essays. Prompt Genie is easy to use and affordable, and it can help you save time and improve the quality of your work.

CUJO AI is a global leader in cutting-edge cybersecurity and network intelligence solutions for network operators. The platform offers a range of services including Operator Intelligence, Digital Life Protection, and AI Platform. CUJO AI empowers network operators to enhance digital life protection for their customers both at home and on the go. By leveraging AI-powered cybersecurity, CUJO AI enables operators to improve customer value proposition, monetize networks, and reduce operating complexity and costs.

Kira Systems is a machine learning contract search, review, and analysis software that helps businesses identify, extract, and analyze content in their contracts and documents. It uses patented machine learning technology to extract concepts and data points with high efficiency and accuracy. Kira also has built-in intelligence that streamlines the contract review process with out-of-the-box smart fields. Businesses can also create their own smart fields to find specific data points using Kira's no-code machine learning tool. Kira's adaptive workflows allow businesses to organize, track, and export results. Kira has a partner ecosystem that allows businesses to transform how teams work with their contracts.

1440.io is an Omnichannel Engagement Suite designed for Salesforce, offering a comprehensive set of tools to streamline customer engagement across various channels. It enables businesses to unify conversations across the customer journey, leverage AI-powered chatbots, personalize interactions, and optimize contact centers. The platform is trusted by leading enterprise brands and aims to improve time-to-value by maximizing the 1440 minutes we all have each day. With features like messaging studio, translation studio, reputation studio, and commerce studio, 1440.io empowers customer-facing teams to deliver premium experiences and drive sales through conversational commerce.

Loris is a conversational intelligence platform designed for leading brands to unlock the hidden value of every customer conversation. It combines proven machine learning and generative AI to provide industry-leading conversation intelligence. Loris helps customer service teams be more efficient, improve customer experience, and drive revenue growth by transforming customer conversations into actionable insights. The platform offers features such as automated quality assurance, real-time agent co-pilot, and customer insights to enhance agent performance and increase customer satisfaction.

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.

Utopia Enhance is an AI-powered music intelligence tool that enhances the value of music by generating over 300 metadata tags through advanced audio and lyric analysis. It aims to supercharge the discoverability and searchability of songs, providing users with valuable insights and data to optimize their music experience.

Sports AI is an AI-powered platform that provides the most accurate and profitable sports predictions in the market. It utilizes machine learning algorithms and advanced sports data to offer free daily predictions for a wide range of events. Users can revolutionize their betting strategy with AI-powered value bets across various sports like soccer/football, tennis, basketball, hockey, handball, and volleyball. The platform helps users make better betting decisions by analyzing data, learning from past mistakes, and accurately determining the profitability of certain outcomes.

Radiology Business is an AI tool designed to provide insights and solutions for professionals in the radiology field. The platform covers a wide range of topics including management, imaging, technology, and conferences. It offers news, analysis, and resources to help radiologists stay informed and make informed decisions. Radiology Business aims to leverage artificial intelligence to improve workflow efficiency and enhance the overall experience in the radiology ecosystem.

TheySaid is a Conversational AI Survey tool that helps businesses drive customer value and revenue through AI-powered surveys. It offers a unique approach of engaging audiences with one relevant question at a time, turning feedback into an ongoing dialogue. The AI tool scans websites to generate tailored survey questions, automates follow-ups with customers, and provides actionable insights based on industry standards and best practices. TheySaid's AI digs deeper by asking personalized follow-up questions in real-time, enhancing customer engagement and satisfaction.

Simba is an AI landing page advisor designed for local service businesses. It provides instant feedback and specific action items to improve landing page conversion rates. By utilizing AI text and vision models, Simba offers tailored recommendations to enhance the effectiveness of Google Ad campaigns for businesses in the local service industry.

Navina AI is a clinician-first AI platform designed to streamline patient care by providing key insights and actionable recommendations to healthcare providers, ACOs, MSOs, and health plans. The platform leverages proprietary AI technology to improve clinical decision-making, reduce administrative burden, and enhance quality management and risk adjustment processes. Navina AI offers efficient chart review, accurate risk adjustment, streamlined quality management, robust analytics, and a user-friendly interface that integrates seamlessly into the clinical workflow.

Digital.ai is an AI-powered DevOps platform that helps organizations automate software releases, improve mobile application testing and security, and provide insights across the software lifecycle. The platform includes a suite of products that can be used to manage the complexities of software delivery, including analytics and intelligence, enterprise agile planning, application protection and security, continuous testing, release orchestration, and deployment automation.

Faros AI is an AI-driven platform designed to enhance engineering productivity by providing personalized insights, guidance, and recommendations. It helps technology teams reduce bottlenecks, optimize software delivery, and improve speed and quality. The platform offers a comprehensive BI solution for software engineering, with features like AI guidance, customizable analytics, and high-security data ingestion. Faros AI is built by engineers for engineers, compatible with various data sources, and tailored to meet enterprise-scale requirements.

Greenbids is an AI application designed to minimize inefficiencies and enhance media performance in digital advertising, contributing to decarbonization efforts. By utilizing Machine Learning, Greenbids saves 1000 tons of CO2 every month and drives sustainable media effectiveness across the advertising ecosystem. The platform offers a unique solution to decrease ads' carbon footprint, with an average carbon intensity reduction of 36% and a 27% increase in media effectiveness. Greenbids aims to address the environmental impact of programmatic advertising by providing a more sustainable and efficient alternative.

ZestyAI is an artificial intelligence tool that helps users make brilliant climate and property risk decisions. The tool uses AI to provide insights on property values and risk exposure to natural disasters. It offers products such as Property Insights, Digital Roof, Roof Age, Location Insights, and Climate Risk Models to evaluate and understand property risks. ZestyAI is trusted by top insurers in North America and aims to bring a ten times return on investment to its customers.

RevSure is an AI-powered platform designed for high-growth marketing teams to optimize marketing ROI and attribution. It offers full-funnel attribution, deep funnel optimization, predictive insights, and campaign performance tracking. The platform integrates with various data sources to provide unified funnel reporting and personalized recommendations for improving pipeline health and conversion rates. RevSure's AI engine powers features like campaign spend reallocation, next-best touch analysis, and journey timeline construction, enabling users to make data-driven decisions and accelerate revenue growth.

ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. Key value propositions of ExecuTorch are: * **Portability:** Compatibility with a wide variety of computing platforms, from high-end mobile phones to highly constrained embedded systems and microcontrollers. * **Productivity:** Enabling developers to use the same toolchains and SDK from PyTorch model authoring and conversion, to debugging and deployment to a wide variety of platforms. * **Performance:** Providing end users with a seamless and high-performance experience due to a lightweight runtime and utilizing full hardware capabilities such as CPUs, NPUs, and DSPs.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

SalesGPT is an open-source AI agent designed for sales, utilizing context-awareness and LLMs to work across various communication channels like voice, email, and texting. It aims to enhance sales conversations by understanding the stage of the conversation and providing tools like product knowledge base to reduce errors. The agent can autonomously generate payment links, handle objections, and close sales. It also offers features like automated email communication, meeting scheduling, and integration with various LLMs for customization. SalesGPT is optimized for low latency in voice channels and ensures human supervision where necessary. The tool provides enterprise-grade security and supports LangSmith tracing for monitoring and evaluation of intelligent agents built on LLM frameworks.

This repository provides a hands-on approach to Retrieval-Augmented Generation (RAG) techniques, simplifying advanced concepts into understandable implementations using Python libraries like openai, numpy, and matplotlib. It offers a collection of Jupyter Notebooks with concise explanations, step-by-step implementations, code examples, evaluations, and visualizations for various RAG techniques. The goal is to make RAG more accessible and demystify its workings for educational purposes.

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-System2-Reasoning-LLM repository is dedicated to a survey paper titled 'From System 1 to System 2: A Survey of Reasoning Large Language Models'. It explores the development of reasoning Large Language Models (LLMs), their foundational technologies, benchmarks, and future directions. The repository provides resources and updates related to the research, tracking the latest developments in the field of reasoning LLMs.

Fitten Code AI Programming Assistant for Neovim provides fast completion using AI, asynchronous I/O, and support for various actions like document code, edit code, explain code, find bugs, generate unit test, implement features, optimize code, refactor code, start chat, and more. It offers features like accepting suggestions with Tab, accepting line with Ctrl + Down, accepting word with Ctrl + Right, undoing accepted text, automatic scrolling, and multiple HTTP/REST backends. It can run as a coc.nvim source or nvim-cmp source.

This repository contains community-driven practical examples of building AI applications and solving various tasks with AI using open-source tools and models. Everyone is welcome to contribute, and we value everybody's contribution! There are several ways you can contribute to the Open-Source AI Cookbook: Submit an idea for a desired example/guide via GitHub Issues. Contribute a new notebook with a practical example. Improve existing examples by fixing issues/typos. Before contributing, check currently open issues and pull requests to avoid working on something that someone else is already working on.

The Big Prompt Library repository is a collection of various system prompts, custom instructions, jailbreak prompts, GPT/instructions protection prompts, etc. for various LLM providers and solutions providing educational value in learning about writing system prompts and creating custom GPTs. It includes topics such as articles, custom instructions, system prompts, jailbreak prompts, instructions protections, and learning resources. The content is intended for learning and informational use to improve prompt writing abilities and inform about prompt injection security risks.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=