Best AI tools for< Scale Collections >

TrueAccord is an industry-leading recovery and collections platform powered by machine learning and a consumer-friendly digital experience. It offers third-party collection services for better relationships and faster recoveries through engagement, commitment, and resolution. TrueAccord's platform can handle delinquency needs from one day past due through charge off, with features like HeartBeat for better results, self-serve digital experience for consumers, scalability in delinquency infrastructure, and end-to-end personalization. The platform is trusted by market leaders and loved by consumers, providing a full-service digital-first debt collection agency.

SceneDreamer is an AI tool that specializes in generating unbounded 3D scenes from 2D image collections. It utilizes an unconditional generative model to synthesize large-scale 3D landscapes with diverse styles, 3D consistency, well-defined depth, and free camera trajectory. The framework is learned solely from in-the-wild 2D image collections, without the need for 3D annotations. SceneDreamer employs an efficient bird's-eye-view representation, a generative scene parameterization, and a neural volumetric renderer to achieve photorealistic images of vivid and diverse unbounded 3D worlds.

LoomFlows is a user feedback collection tool that allows businesses to collect high-quality feedback from their users through Loom screen recordings and annotated screenshots. It helps businesses streamline feedback collection, identify impactful opportunities, and scale faster by building the right features.

Inferkit AI is an AI tool that offers a cheaper and faster LLM router. It provides users with the ability to generate text content efficiently and cost-effectively. The tool is designed to assist users in creating various types of written content, such as articles, stories, and more, by leveraging advanced language models. Inferkit AI aims to streamline the content creation process and enhance productivity for individuals and businesses alike.

AI Directories is a meticulously curated collection of directories focused on AI tools, designed to facilitate rapid submissions. The platform offers a streamlined path to increase online presence, boost SEO, and connect with a like-minded community. Created by Sergiu, the platform aims to save valuable time, improve SEO, and share a comprehensive list with the community. With over 3000 followers on Twitter and positive customer testimonials, AI Directories has become a go-to resource for indie makers and founders looking to enhance their online visibility and marketing strategies.

Everseen is an AI platform that offers a comprehensive suite of tools for data collection, contextualization, insight discovery, process modeling, video translation, AI reasoning, model engineering, continuous learning, governance, and more. It is designed to help businesses in the retail industry prevent losses, accelerate sales, protect inventory, improve product availability, and ensure process integrity. Everseen's Vision AI Factory supports hyper-scaled applications with value assurance and governance at its core, enabling users to combat retail shrink threats effectively.

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

VideoAsk by Typeform is an interactive video platform that helps streamline conversations and build business relationships at scale. It offers features such as asynchronous interviews, easy scheduling, tagging, gathering contact info, capturing leads, research and feedback, training, customer support, and more. Users can create interactive video forms, conduct async interviews, and engage with their audience through AI-powered video chatbots. The platform is user-friendly, code-free, and integrates with over 1,500 applications through Zapier.

Yoit is a fashion website that offers a wide range of trendy clothing options inspired by celebrities and popular street styles. The platform showcases affordable versions of celebrity outfits, top brand collections, and comfortable shoes. Users can explore the latest fashion trends, shop for clothing and accessories, and get style inspiration from celebrity looks. Yoit also provides fashion tips, newsletters, and curated edits to help users stay fashionable and up-to-date with the latest styles.

MavTools is a platform that offers a curated collection of AI tools and SAAS applications to help individuals and businesses enhance productivity, marketing, design, writing, video, image/photo editing, and voice/audio tasks. Users can explore, discover, and leverage various tools to start and scale their businesses efficiently. The platform provides a user-friendly interface for searching, filtering, and selecting tools based on specific categories and requirements. MavTools aims to empower users with innovative technologies and solutions to streamline their workflows and achieve better results.

Browse AI is a web data extraction and monitoring platform that makes it easy, affordable, and reliable for anyone to collect data from the web at scale. It was founded in 2020 with the mission of making the web more accessible and useful for everyone.

Heights Platform is an AI-powered course creation software that enables creators to build online courses, digital products, and memberships. The platform offers AI guidance and coaching for creators, learner analytics, payment collection, and integration with favorite tools. With Heights Platform, creators can design websites, engage with their audience, and scale their businesses on their own terms. The platform provides a comprehensive solution for turning knowledge into income, with features like lesson editing, flexible content structure, multimedia content support, and secure hosting for videos. Creators can create unlimited courses with modules and lessons, offer various payment methods, and customize their branding and website. Heights Platform also allows creators to build and grow private communities with unlimited channels, offering a unique approach to online learning and business development.

Onyxium is an AI platform that provides a comprehensive collection of AI tools for various tasks such as image recognition, text analysis, and speech recognition. It offers users the ability to access and utilize the latest AI technologies in one place, empowering them to enhance their projects and workflows with advanced AI capabilities. With a user-friendly interface and affordable pricing plans, Onyxium aims to make AI tools accessible to everyone, from individuals to large-scale businesses.

Viso Suite is a no-code computer vision platform that enables users to build, deploy, and scale computer vision applications. It provides a comprehensive set of tools for data collection, annotation, model training, application development, and deployment. Viso Suite is trusted by leading Fortune Global companies and has been used to develop a wide range of computer vision applications, including object detection, image classification, facial recognition, and anomaly detection.

Deformity is an AI-driven platform that offers conversational forms to engage and captivate audiences at scale. It allows users to create forms in seconds, utilize AI for lead generation and qualification, collect feedback, design quizzes and giveaways, and conduct research. With the ability to speak 120+ languages fluently, Deformity provides a seamless experience for global audiences. Users can customize forms to match their brand identity, add logic effortlessly, and access advanced features like submission period control and submission limits. Deformity aims to streamline form creation and data collection processes while offering flexibility and efficiency.

Macgence is an AI training data services platform that offers high-quality off-the-shelf structured training data for organizations to build effective AI systems at scale. They provide services such as custom data sourcing, data annotation, data validation, content moderation, and localization. Macgence combines global linguistic, cultural, and technological expertise to create high-quality datasets for AI models, enabling faster time-to-market across the entire model value chain. With more than 5 years of experience, they support and scale AI initiatives of leading global innovators by designing custom data collection programs. Macgence specializes in handling AI training data for text, speech, image, and video data, offering cognitive annotation services to unlock the potential of unstructured textual data.

Green Cubes is an AI application that provides precise volume, complexity, and biodiversity indication of terrestrial areas at scale for Digital Reality and Sponsorship. It shapes the digital twin of nature, offering transparency and trust through Measure, Report, and Verification (MVR) using data collection, AI computation, and 3D visualization. Green Cubes enables corporations to sponsor nature impact with confidence and transparency, contributing to the preservation of biodiversity.

Restb.ai is a leading provider of visual insights for real estate companies, utilizing computer vision and AI to analyze property images. The application offers solutions for AVMs, iBuyers, investors, appraisals, inspections, property search, marketing, insurance companies, and more. By providing actionable and unique data at scale, Restb.ai helps improve valuation accuracy, automate manual processes, and enhance property interactions. The platform enables users to leverage visual insights to optimize valuations, automate report quality checks, enhance listings, improve data collection, and more.

MonsterImage.AI is an AI-powered tool that allows users to create cool pattern images using Artificial Intelligence. Users can sign in to the platform and receive a link via email to log in. They can write a prompt to describe the image they want to create, select a pattern, specify negative prompts, use a seed for reproduction, adjust guidance scale, controlnet conditioning scale, and inference steps. The tool offers advanced options for creating images and allows users to save their creations in a public collection.

AdaraChatbot is a platform that allows users to build their own chatbot using OpenAI Assistant API. It offers seamless integration for effortlessly incorporating a chatbot into websites. Users can test the chatbot assistant, ask questions, and receive responses powered by OpenAI Assistant API. AdaraChatbot provides features such as building chatbots with OpenAI's assistant, easy integration with websites, user inquiry with lead collection, real-time analytics, file attachments, and compatibility with popular website platforms. The application offers different pricing plans suitable for personal projects, organizations, and tailored solutions for large-scale operations.

Vespa is an open-source search and AI engine that provides a unified platform for building and deploying search and AI applications. Vespa sample applications showcase various use cases and features of Vespa, including basic search, recommendation, semantic search, image search, text ranking, e-commerce search, question answering, search-as-you-type, and ML inference serving.

Zep is a long-term memory service for AI Assistant apps. With Zep, you can provide AI assistants with the ability to recall past conversations, no matter how distant, while also reducing hallucinations, latency, and cost. Zep persists and recalls chat histories, and automatically generates summaries and other artifacts from these chat histories. It also embeds messages and summaries, enabling you to search Zep for relevant context from past conversations. Zep does all of this asyncronously, ensuring these operations don't impact your user's chat experience. Data is persisted to database, allowing you to scale out when growth demands. Zep also provides a simple, easy to use abstraction for document vector search called Document Collections. This is designed to complement Zep's core memory features, but is not designed to be a general purpose vector database. Zep allows you to be more intentional about constructing your prompt: 1. automatically adding a few recent messages, with the number customized for your app; 2. a summary of recent conversations prior to the messages above; 3. and/or contextually relevant summaries or messages surfaced from the entire chat session. 4. and/or relevant Business data from Zep Document Collections.

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.

AceCoder is a tool that introduces a fully automated pipeline for synthesizing large-scale reliable tests used for reward model training and reinforcement learning in the coding scenario. It curates datasets, trains reward models, and performs RL training to improve coding abilities of language models. The tool aims to unlock the potential of RL training for code generation models and push the boundaries of LLM's coding abilities.

WARC-GPT is an experimental retrieval augmented generation pipeline for web archive collections. It allows users to interact with WARC files, extract text, generate text embeddings, visualize embeddings, and interact with a web UI and API. The tool is highly customizable, supporting various LLMs, providers, and embedding models. Users can configure the application using environment variables, ingest WARC files, start the server, and interact with the web UI and API to search for content and generate text completions. WARC-GPT is designed for exploration and experimentation in exploring web archives using AI.

R2R (RAG to Riches) is a fast and efficient framework for serving high-quality Retrieval-Augmented Generation (RAG) to end users. The framework is designed with customizable pipelines and a feature-rich FastAPI implementation, enabling developers to quickly deploy and scale RAG-based applications. R2R was conceived to bridge the gap between local LLM experimentation and scalable production solutions. **R2R is to LangChain/LlamaIndex what NextJS is to React**. A JavaScript client for R2R deployments can be found here. ### Key Features * **🚀 Deploy** : Instantly launch production-ready RAG pipelines with streaming capabilities. * **🧩 Customize** : Tailor your pipeline with intuitive configuration files. * **🔌 Extend** : Enhance your pipeline with custom code integrations. * **⚖️ Autoscale** : Scale your pipeline effortlessly in the cloud using SciPhi. * **🤖 OSS** : Benefit from a framework developed by the open-source community, designed to simplify RAG deployment.

This is the official repository for 'Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing'. Magpie is a tool designed to synthesize high-quality instruction data at scale by extracting it directly from an aligned Large Language Models (LLMs). It aims to democratize AI by generating large-scale alignment data and enhancing the transparency of model alignment processes. Magpie has been tested on various model families and can be used to fine-tune models for improved performance on alignment benchmarks such as AlpacaEval, ArenaHard, and WildBench.

This repository aims to build a low-parameter LLM model through pretraining, fine-tuning, model rewarding, and reinforcement learning stages to create a chat model capable of simple conversation tasks. It features using the bert4torch training framework, seamless integration with transformers package for inference, optimized file reading during training to reduce memory usage, providing complete training logs for reproducibility, and the ability to customize robot attributes. The chat model supports multi-turn conversations. The trained model currently only supports basic chat functionality due to limitations in corpus size, model scale, SFT corpus size, and quality.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

MiniCPM is a series of open-source large models on the client side jointly developed by Face Intelligence and Tsinghua University Natural Language Processing Laboratory. The main language model MiniCPM-2B has only 2.4 billion (2.4B) non-word embedding parameters, with a total of 2.7B parameters. - After SFT, MiniCPM-2B performs similarly to Mistral-7B on public comprehensive evaluation sets (better in Chinese, mathematics, and code capabilities), and outperforms models such as Llama2-13B, MPT-30B, and Falcon-40B overall. - After DPO, MiniCPM-2B also surpasses many representative open-source large models such as Llama2-70B-Chat, Vicuna-33B, Mistral-7B-Instruct-v0.1, and Zephyr-7B-alpha on the current evaluation set MTBench, which is closest to the user experience. - Based on MiniCPM-2B, a multi-modal large model MiniCPM-V 2.0 on the client side is constructed, which achieves the best performance of models below 7B in multiple test benchmarks, and surpasses larger parameter scale models such as Qwen-VL-Chat 9.6B, CogVLM-Chat 17.4B, and Yi-VL 34B on the OpenCompass leaderboard. MiniCPM-V 2.0 also demonstrates leading OCR capabilities, approaching Gemini Pro in scene text recognition capabilities. - After Int4 quantization, MiniCPM can be deployed and inferred on mobile phones, with a streaming output speed slightly higher than human speech speed. MiniCPM-V also directly runs through the deployment of multi-modal large models on mobile phones. - A single 1080/2080 can efficiently fine-tune parameters, and a single 3090/4090 can fully fine-tune parameters. A single machine can continuously train MiniCPM, and the secondary development cost is relatively low.

Awesome GPT Prompt Engineering is a curated list of resources, tools, and shiny things for GPT prompt engineering. It includes roadmaps, guides, techniques, prompt collections, papers, books, communities, prompt generators, Auto-GPT related tools, prompt injection information, ChatGPT plug-ins, prompt engineering job offers, and AI links directories. The repository aims to provide a comprehensive guide for prompt engineering enthusiasts, covering various aspects of working with GPT models and improving communication with AI tools.

Awesome RAG is a curated list of retrieval-augmented generation (RAG) in large language models. It includes papers, surveys, general resources, lectures, talks, tutorials, workshops, tools, and other collections related to retrieval-augmented generation. The repository aims to provide a comprehensive overview of the latest advancements, techniques, and applications in the field of RAG.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

Chinese-Tiny-LLM is a repository containing procedures for cleaning Chinese web corpora and pre-training code. It introduces CT-LLM, a 2B parameter language model focused on the Chinese language. The model primarily uses Chinese data from a 1,200 billion token corpus, showing excellent performance in Chinese language tasks. The repository includes tools for filtering, deduplication, and pre-training, aiming to encourage further research and innovation in language model development.

The GFM-RAG is a graph foundation model-powered pipeline that combines graph neural networks to reason over knowledge graphs and retrieve relevant documents for question answering. It features a knowledge graph index, efficiency in multi-hop reasoning, generalizability to unseen datasets, transferability for fine-tuning, compatibility with agent-based frameworks, and interpretability of reasoning paths. The tool can be used for conducting retrieval and question answering tasks using pre-trained models or fine-tuning on custom datasets.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

KwaiAgents is a series of Agent-related works open-sourced by the [KwaiKEG](https://github.com/KwaiKEG) from [Kuaishou Technology](https://www.kuaishou.com/en). The open-sourced content includes: 1. **KAgentSys-Lite**: a lite version of the KAgentSys in the paper. While retaining some of the original system's functionality, KAgentSys-Lite has certain differences and limitations when compared to its full-featured counterpart, such as: (1) a more limited set of tools; (2) a lack of memory mechanisms; (3) slightly reduced performance capabilities; and (4) a different codebase, as it evolves from open-source projects like BabyAGI and Auto-GPT. Despite these modifications, KAgentSys-Lite still delivers comparable performance among numerous open-source Agent systems available. 2. **KAgentLMs**: a series of large language models with agent capabilities such as planning, reflection, and tool-use, acquired through the Meta-agent tuning proposed in the paper. 3. **KAgentInstruct**: over 200k Agent-related instructions finetuning data (partially human-edited) proposed in the paper. 4. **KAgentBench**: over 3,000 human-edited, automated evaluation data for testing Agent capabilities, with evaluation dimensions including planning, tool-use, reflection, concluding, and profiling.

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

TokenPacker is a novel visual projector that compresses visual tokens by 75%∼89% with high efficiency. It adopts a 'coarse-to-fine' scheme to generate condensed visual tokens, achieving comparable or better performance across diverse benchmarks. The tool includes TokenPacker for general use and TokenPacker-HD for high-resolution image understanding. It provides training scripts, checkpoints, and supports various compression ratios and patch numbers.

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Optimizes production processes for efficient large-scale operations.

S&T Intelligence at Scale

Expert in full-scale app development, coding, and OCR.

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I help you build and scale Silicon Valley-style startups

Sequentially administers Big Five Test with 1-5 scale.

Rate AI-created model portraits on a 1-10 scale.

In-depth CIM analysis with a structured rating scale, offering detailed business evaluations.

I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

Business Angel provides expert startup guidance: funding, growth hacks, and pitch advice. Navigate the startup ecosystem, from seed to scale. Essential for entrepreneurs aiming for success. Master your strategy and launch with confidence. Your startup journey begins here!

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I help you with all your sysadmin tasks, from setting up your server to scaling your already exsisting one. I can help you with understanding the long list of log files and give you solutions to the problems.

Startup Strong Within 180 Days: Tailored advice for launching, promoting, and scaling businesses of all types. It covers all stages from pre-launch to post-launch and develops strategies including market research, branding, promotional tactics, and operational planning unique your business. (v1.8)

Learn Kubernetes by Hands-on Labs and AI

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Startup advisor guiding founders through detailed idea evaluation, product-market-fit, business model, GTM, and scaling.

gpt tools for scala coding