Best AI tools for< Evaluate Value Propositions >
20 - AI tool Sites

RevSure
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.

ZestyAI
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.

Appraiser.AI
Appraiser.AI is an AI-powered appraisal tool designed to help users accurately assess the value of a wide range of collectibles and antiques. By leveraging advanced algorithms and data analysis, the tool provides users with instant appraisals for items such as vintage coins, jewelry, artwork, vinyl records, trading cards, and more. With a user-friendly interface, Appraiser.AI offers a convenient and reliable solution for individuals looking to determine the worth of their possessions quickly and efficiently.

MASCAA
MASCAA is a comprehensive human confidence analysis platform that focuses on evaluating the confidence of users through video and audio during various tasks. It integrates advanced facial expression and voice analysis technologies to provide valuable feedback for students, instructors, individuals, businesses, and teams. MASCAA offers quick and easy test creation, evaluation, and confidence assessment for educational settings, personal use, startups, small organizations, universities, and large organizations. The platform aims to unlock long-term value and enhance customer experience by helping users assess and improve their confidence levels.

Workflos
Workflos is a platform designed to help business leaders discover and explore software solutions across various categories. It provides insights into trending software, customer favorites, and top-rated products based on criteria like ease of use and value for money. With Workflos, users can stay informed about the latest software offerings and make informed decisions to meet their business needs.

AnalyStock.ai
AnalyStock.ai is a financial application leveraging AI to provide users with a next-generation investment toolbox. It helps users better understand businesses, risks, and make informed investment decisions. The platform offers direct access to the stock market, powerful data-driven tools to build top-ranking portfolios, and insights into company valuations and growth prospects. AnalyStock.ai aims to optimize the investment process, offering a reliable strategy with factors like A-Score, factor investing scores for value, growth, quality, volatility, momentum, and yield. Users can discover hidden gems, fine-tune filters, access company scorecards, perform activity analysis, understand industry dynamics, evaluate capital structure, profitability, and peers' valuation. The application also provides adjustable DCF valuation, portfolio management tools, net asset value computation, monthly commentary, and an AI assistant for personalized insights and assistance.

Sacred
Sacred is a tool to configure, organize, log and reproduce computational experiments. It is designed to introduce only minimal overhead, while encouraging modularity and configurability of experiments. The ability to conveniently make experiments configurable is at the heart of Sacred. If the parameters of an experiment are exposed in this way, it will help you to: keep track of all the parameters of your experiment easily run your experiment for different settings save configurations for individual runs in files or a database reproduce your results In Sacred we achieve this through the following main mechanisms: Config Scopes are functions with a @ex.config decorator, that turn all local variables into configuration entries. This helps to set up your configuration really easily. Those entries can then be used in captured functions via dependency injection. That way the system takes care of passing parameters around for you, which makes using your config values really easy. The command-line interface can be used to change the parameters, which makes it really easy to run your experiment with modified parameters. Observers log every information about your experiment and the configuration you used, and saves them for example to a Database. This helps to keep track of all your experiments. Automatic seeding helps controlling the randomness in your experiments, such that they stay reproducible.

Compassionate AI
Compassionate AI is a cutting-edge AI-powered platform that empowers individuals and organizations to create and deploy AI solutions that are ethical, responsible, and aligned with human values. With Compassionate AI, users can access a comprehensive suite of tools and resources to design, develop, and implement AI systems that prioritize fairness, transparency, and accountability.

BenchLLM
BenchLLM is an AI tool designed for AI engineers to evaluate LLM-powered apps by running and evaluating models with a powerful CLI. It allows users to build test suites, choose evaluation strategies, and generate quality reports. The tool supports OpenAI, Langchain, and other APIs out of the box, offering automation, visualization of reports, and monitoring of model performance.

thisorthis.ai
thisorthis.ai is an AI tool that allows users to compare generative AI models and AI model responses. It helps users analyze and evaluate different AI models to make informed decisions. The tool requires JavaScript to be enabled for optimal functionality.

Langtrace AI
Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

Arize AI
Arize AI is an AI Observability & LLM Evaluation Platform that helps you monitor, troubleshoot, and evaluate your machine learning models. With Arize, you can catch model issues, troubleshoot root causes, and continuously improve performance. Arize is used by top AI companies to surface, resolve, and improve their models.

Evidently AI
Evidently AI is an open-source machine learning (ML) monitoring and observability platform that helps data scientists and ML engineers evaluate, test, and monitor ML models from validation to production. It provides a centralized hub for ML in production, including data quality monitoring, data drift monitoring, ML model performance monitoring, and NLP and LLM monitoring. Evidently AI's features include customizable reports, structured checks for data and models, and a Python library for ML monitoring. It is designed to be easy to use, with a simple setup process and a user-friendly interface. Evidently AI is used by over 2,500 data scientists and ML engineers worldwide, and it has been featured in publications such as Forbes, VentureBeat, and TechCrunch.

Maxim
Maxim is an end-to-end AI evaluation and observability platform that empowers modern AI teams to ship products with quality, reliability, and speed. It offers a comprehensive suite of tools for experimentation, evaluation, observability, and data management. Maxim aims to bring the best practices of traditional software development into non-deterministic AI workflows, enabling rapid iteration and deployment of AI models. The platform caters to the needs of AI developers, data scientists, and machine learning engineers by providing a unified framework for evaluation, visual flows for workflow testing, and observability features for monitoring and optimizing AI systems in real-time.

RebeccAi
RebeccAi is an AI-powered business idea evaluation and validation tool that helps users assess the potential of their ideas quickly and intelligently. It offers accurate insights, fast idea refinement, and personalized business plans, revolutionizing the way entrepreneurs validate their business concepts. With over 25,000 reports generated and 5,000 users benefiting from its services, RebeccAi is a trusted platform for turning innovative ideas into successful ventures.

Codei
Codei is an AI-powered platform designed to help individuals land their dream software engineering job. It offers features such as application tracking, question generation, and code evaluation to assist users in honing their technical skills and preparing for interviews. Codei aims to provide personalized support and insights to help users succeed in the tech industry.

Ottic
Ottic is an AI tool designed to empower both technical and non-technical teams to test Language Model (LLM) applications efficiently and accelerate the development cycle. It offers features such as a 360º view of the QA process, end-to-end test management, comprehensive LLM evaluation, and real-time monitoring of user behavior. Ottic aims to bridge the gap between technical and non-technical team members, ensuring seamless collaboration and reliable product delivery.

SuperAnnotate
SuperAnnotate is an AI data platform that simplifies and accelerates model-building by unifying the AI pipeline. It enables users to create, curate, and evaluate datasets efficiently, leading to the development of better models faster. The platform offers features like connecting any data source, building customizable UIs, creating high-quality datasets, evaluating models, and deploying models seamlessly. SuperAnnotate ensures global security and privacy measures for data protection.

SymptomChecker.io
SymptomChecker.io is an AI-powered medical symptom checker that allows users to describe their symptoms in their own words and receive non-reviewed AI-generated responses. It is important to note that this tool is not intended to offer medical advice, diagnosis, or treatment and should not be used as a substitute for professional medical advice. In the case of a medical emergency, please contact your physician or dial 911 immediately.

ELSA
ELSA is an AI-powered English speaking coach that helps you improve your pronunciation, fluency, and confidence. With ELSA, you can practice speaking English in short, fun dialogues and get instant feedback from our proprietary artificial intelligence technology. ELSA also offers a variety of other features, such as personalized lesson plans, progress tracking, and games to help you stay motivated.
20 - Open Source AI Tools

PromptChains
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.

prompt-tuning-playbook
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.

SalesGPT
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.

all-rag-techniques
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.

Awesome-LLM-in-Social-Science
Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

mentals-ai
Mentals AI is a tool designed for creating and operating agents that feature loops, memory, and various tools, all through straightforward markdown syntax. This tool enables you to concentrate solely on the agent’s logic, eliminating the necessity to compose underlying code in Python or any other language. It redefines the foundational frameworks for future AI applications by allowing the creation of agents with recursive decision-making processes, integration of reasoning frameworks, and control flow expressed in natural language. Key concepts include instructions with prompts and references, working memory for context, short-term memory for storing intermediate results, and control flow from strings to algorithms. The tool provides a set of native tools for message output, user input, file handling, Python interpreter, Bash commands, and short-term memory. The roadmap includes features like a web UI, vector database tools, agent's experience, and tools for image generation and browsing. The idea behind Mentals AI originated from studies on psychoanalysis executive functions and aims to integrate 'System 1' (cognitive executor) with 'System 2' (central executive) to create more sophisticated agents.

kvpress
This repository implements multiple key-value cache pruning methods and benchmarks using transformers, aiming to simplify the development of new methods for researchers and developers in the field of long-context language models. It provides a set of 'presses' that compress the cache during the pre-filling phase, with each press having a compression ratio attribute. The repository includes various training-free presses, special presses, and supports KV cache quantization. Users can contribute new presses and evaluate the performance of different presses on long-context datasets.

ping_pong_bench
PingPong is a benchmark designed for role-playing language models, focusing on evaluating conversational abilities through interactions with characters and test situations. The benchmark uses LLMs to emulate users in role-playing conversations, assessing criteria such as character portrayal, entertainment value, and fluency. Users can engage in dialogues with specific characters, like Kurisu, and evaluate the bot's responses based on predefined criteria. PingPong aims to provide a comprehensive evaluation method for language models, moving beyond single-turn interactions to more complex conversational scenarios.

skpro
skpro is a library for supervised probabilistic prediction in python. It provides `scikit-learn`-like, `scikit-base` compatible interfaces to: * tabular **supervised regressors for probabilistic prediction** \- interval, quantile and distribution predictions * tabular **probabilistic time-to-event and survival prediction** \- instance-individual survival distributions * **metrics to evaluate probabilistic predictions** , e.g., pinball loss, empirical coverage, CRPS, survival losses * **reductions** to turn `scikit-learn` regressors into probabilistic `skpro` regressors, such as bootstrap or conformal * building **pipelines and composite models** , including tuning via probabilistic performance metrics * symbolic **probability distributions** with value domain of `pandas.DataFrame`-s and `pandas`-like interface

Awesome-LLM-in-Social-Science
This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

LLM-RGB
LLM-RGB is a repository containing a collection of detailed test cases designed to evaluate the reasoning and generation capabilities of Language Learning Models (LLMs) in complex scenarios. The benchmark assesses LLMs' performance in understanding context, complying with instructions, and handling challenges like long context lengths, multi-step reasoning, and specific response formats. Each test case evaluates an LLM's output based on context length difficulty, reasoning depth difficulty, and instruction compliance difficulty, with a final score calculated for each test case. The repository provides a score table, evaluation details, and quick start guide for running evaluations using promptfoo testing tools.

ollama-grid-search
A Rust based tool to evaluate LLM models, prompts and model params. It automates the process of selecting the best model parameters, given an LLM model and a prompt, iterating over the possible combinations and letting the user visually inspect the results. The tool assumes the user has Ollama installed and serving endpoints, either in `localhost` or in a remote server. Key features include: * Automatically fetches models from local or remote Ollama servers * Iterates over different models and params to generate inferences * A/B test prompts on different models simultaneously * Allows multiple iterations for each combination of parameters * Makes synchronous inference calls to avoid spamming servers * Optionally outputs inference parameters and response metadata (inference time, tokens and tokens/s) * Refetching of individual inference calls * Model selection can be filtered by name * List experiments which can be downloaded in JSON format * Configurable inference timeout * Custom default parameters and system prompts can be defined in settings

eval-scope
Eval-Scope is a framework for evaluating and improving large language models (LLMs). It provides a set of commonly used test datasets, metrics, and a unified model interface for generating and evaluating LLM responses. Eval-Scope also includes an automatic evaluator that can score objective questions and use expert models to evaluate complex tasks. Additionally, it offers a visual report generator, an arena mode for comparing multiple models, and a variety of other features to support LLM evaluation and development.

alignment-attribution-code
This repository provides an original implementation of Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. It includes tools for neuron-level pruning, pruning based on set difference, Wanda/SNIP score dumping, rank-level pruning, and rank removal with orthogonal projection. Users can specify parameters like prune method, datasets, sparsity ratio, model, and save location to evaluate and modify neural networks for safety alignment.

tonic_validate
Tonic Validate is a framework for the evaluation of LLM outputs, such as Retrieval Augmented Generation (RAG) pipelines. Validate makes it easy to evaluate, track, and monitor your LLM and RAG applications. Validate allows you to evaluate your LLM outputs through the use of our provided metrics which measure everything from answer correctness to LLM hallucination. Additionally, Validate has an optional UI to visualize your evaluation results for easy tracking and monitoring.

can-ai-code
Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.
20 - OpenAI Gpts

Competitive Defensibility Analyzer
Evaluates your long-term market position based on value offered and uniqueness against competitors.

Home Inspector
Upload a picture of your home wall, floor, window, driveway, roof, HVAC, and get an instant opinion.

Innovation YRP
An Innovation & R&D Management advisor who can help you turn ideas into new value creation using over 60 methodologies and tools. Attributed to Yann Rousselot-Pailley https://www.linkedin.com/in/yannrousselot/

Antique and Collectible Appraisal GPT
All-encompassing antique and collectible appraisal assistant offering dollar estimates.

AI Market Analyzer
Analyzes markets, offers predictions on commodities, crypto, and companies.

Rate My {{Startup}}
I will score your Mind Blowing Startup Ideas, helping your to evaluate faster.

Stick to the Point
I'll help you evaluate your writing to make sure it's engaging, informative, and flows well. Uses principles from "Made to Stick"

LabGPT
The main objective of a personalized ChatGPT for reading laboratory tests is to evaluate laboratory test results and create a spreadsheet with the evaluation results and possible solutions.

SearchQualityGPT
As a Search Quality Rater, you will help evaluate search engine quality around the world.

Business Model Canvas Strategist
Business Model Canvas Creator - Build and evaluate your business model