Best AI tools for< Scale Efficiently >

STRATxAI is an AI-powered platform that offers custom-built model portfolios for forward-thinking investors. The platform collaborates closely with clients to create bespoke solutions tailored to their unique needs, preferences, and risk profiles. By leveraging artificial intelligence, STRATxAI aims to deliver adaptive multi-factor portfolios that consistently generate superior risk-adjusted returns, enabling investment professionals to drive better client outcomes and excel in today's market.

AI Caller is a robocaller application that leverages AI technology for automated outbound phone calls. It offers hyper-realistic, human-like voice calls to assist in various tasks such as lead qualification, customer feedback, data gathering, and more. The application is designed to scale efficiently, integrate with external systems, and provide actionable insights through call transcripts analysis. AI Caller is customizable for all industries and use cases, making it a versatile tool for businesses looking to streamline their calling processes.

Convex is a fullstack TypeScript development platform that serves as an open-source backend for application builders. It offers a comprehensive set of APIs and tools to build, launch, and scale applications efficiently. With features like real-time collaboration, optimized transactions, and over 80 OAuth integrations, Convex simplifies backend operations and allows developers to focus on delivering value to customers. The platform enables developers to write backend logic in TypeScript, perform database operations with strong consistency, and integrate with various third-party services seamlessly. Convex is praised for its reliability, simplicity, and developer experience, making it a popular choice for modern software development projects.

Proxima is a predictive data intelligence tool that offers custom audiences for paid social, analytics, and tactical benchmarks. It helps businesses lower acquisition costs, increase customer lifetime value, and grow profitably by leveraging AI-powered advertising solutions. With a focus on predictive insights and enterprise-grade analytics, Proxima empowers users to make data-driven decisions that fuel growth and optimize marketing performance.

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.

Prolific is a platform that helps users quickly find research participants they can trust. It offers free representative samples, a participant pool of domain experts, the ability to bring your own participants, and an API for integration. Prolific ensures data quality by verifying participants with bank-grade ID checks, ongoing checks to identify bots, and no AI participants. The platform allows users to easily set up accounts, access rich and comprehensive responses, and scale research projects efficiently.

ScaleGrowth is an AI-powered platform designed to help businesses scale and grow efficiently. It offers a range of tools and features to streamline various aspects of business operations, from marketing to customer service. By leveraging artificial intelligence technology, ScaleGrowth aims to provide data-driven insights and automation to optimize business performance and drive growth.

SysAid is a Next-Gen ITSM Platform that offers a comprehensive IT service management solution with generative AI capabilities. It provides features such as AI chatbot integration, asset management, workflow automation, and performance insights. SysAid aims to streamline IT processes, empower agents with AI, and enhance end-user experience. The platform is designed to help organizations deliver exceptional service efficiently and scale seamlessly.

Hubert is a conversational AI platform designed to revolutionize the recruitment process by automating candidate screening and shortlisting. It offers a modern approach to traditional CV screening, saving time, promoting fairness, and enhancing candidate experience. With Hubert, recruiters can streamline their workflow, eliminate bias, engage candidates effectively, and scale recruitment efforts efficiently. The platform is built on structured interviews and AI technology to identify top candidates accurately and quickly. Hubert is integrated with popular ATS systems and caters to various industries, ensuring a seamless and personalized recruitment experience.

FirstQuadrant is an AI-powered B2B sales platform that offers fully-automated sales solutions using cutting-edge artificial intelligence technology. It provides a comprehensive suite of AI tools for inbound, outbound, and nurturing sales, enabling businesses to grow exponentially with predictable and autonomous sales processes. The platform automates lead sourcing, lead enrichment, email deliverability, personalized messaging, objection handling, follow-ups, and CRM nurturing. FirstQuadrant also offers extensive analytics to track sales performance and initiate autopilot campaigns. It is designed for modern sales organizations to scale sales efforts efficiently and effectively.

Bounti Labs is an AI-powered platform that blends AI efficiency with human intuition to enhance outreach and prospecting activities. It enables faster, better, and more authentic prospecting by providing AI-generated research, use cases, pitches, and sample messaging to supercharge outreach without the delay of onboarding. Bounti Labs empowers sales, marketing, and customer success teams worldwide to scale quickly and efficiently with its autonomous AI teammate.

Backend.AI is an enterprise-scale cluster backend for AI frameworks that offers scalability, GPU virtualization, HPC optimization, and DGX-Ready software products. It provides a fast and efficient way to build, train, and serve AI models of any type and size, with flexible infrastructure options. Backend.AI aims to optimize backend resources, reduce costs, and simplify deployment for AI developers and researchers. The platform integrates seamlessly with existing tools and offers fractional GPU usage and pay-as-you-play model to maximize resource utilization.

Allcancode is a platform that helps individuals and companies bring their product ideas to market quickly and efficiently. From idea-stage startups to established companies, Allcancode transforms ideas into marketable products by providing a devoted tech team, shortest time to market, staying on budget, and giving users access to their product's source code. The platform follows a lean process in 4 steps: Discovery & Design Phase, Development Phase, Delivery Phase, and Evolution Phase. Allcancode's secret sauce is its product development platform, offering development superpowers, the use of latest technologies, fully open source code, and easy and fast changes. Users can use the platform for free without limitations, ensuring full source code ownership.

Instant Flow is a powerful AI tool designed to help users manage their Instagram profiles efficiently. With features like Instagram automation, content planning, and AI agents, Instant Flow allows users to send DMs, schedule content, and manage conversations using artificial intelligence. The tool is trusted by over 3000 users worldwide and offers real profiles targeting, one-click setup, and personalized interactions to connect with ideal customers. Instant Flow is the go-to solution for Instagrammers, agencies, and businesses looking to scale their online presence effortlessly.

Shotstack is a cloud video editing API platform that enables users to create powerful video workflows and applications using AI and programmatic video editing tools. It offers capabilities such as bulk video editing, AI-powered video generation, scaled video rendering, and white-label video editor. Users can automate real estate listing videos, car listing videos, create highlight reels, and personalize videos using merge fields. Shotstack provides API documentation, examples, demos, guides, tutorials, and case studies to help users get started. It aims to simplify video creation processes and empower businesses and developers to scale their video creation efforts efficiently.

SAO (Search Ads Optimization) is an AI optimization platform for Apple Search Ads that automates keyword bid management to help scale revenue, increase installs, and reduce cost per acquisition. It offers in-depth analytics, data visualization, and advanced ASO tools for optimizing and automating Apple Search Ads campaigns. Trusted by app companies worldwide, SAO uses AI automation to run 24/7 with real-time data, allowing users to focus on strategic tasks while the platform manages campaigns efficiently.

Restack is a developer tool and cloud infrastructure platform that enables users to build, launch, and scale AI products quickly and efficiently. With Restack, developers can go from local development to production in seconds, leveraging a variety of languages and frameworks. The platform offers templates, repository connections, and Dockerfile customization for seamless deployment. Restack Cloud provides cost-efficient scaling and GitHub integration for instant deployment. The platform simplifies the complexity of building and scaling AI applications, allowing users to move from code to production faster than ever before.

JFrog ML is an AI platform designed to streamline AI development from prototype to production. It offers a unified MLOps platform to build, train, deploy, and manage AI workflows at scale. With features like Feature Store, LLMOps, and model monitoring, JFrog ML empowers AI teams to collaborate efficiently and optimize AI & ML models in production.

Katalon is a modern, comprehensive quality management platform that helps teams of any size deliver the highest quality digital experiences. It offers a range of features including test authoring, test management, test execution, reporting & analytics, and AI-powered testing. Katalon is suitable for testers of all backgrounds, providing a single platform for testing web, mobile, API, desktop, and packaged apps. With AI capabilities, Katalon simplifies test automation, streamlines testing operations, and scales testing programs for enterprise teams.

Klenty is an AI-powered sales engagement and intelligence platform designed to help sales teams find, engage, and convert prospects into pipeline. It combines B2B prospecting database, multi-channel sequencing, and AI capabilities to predictably hit sales targets. Klenty offers features like multi-channel outreach, lead routing, conversation intelligence, prospecting data enrichment, and sales dialer functionalities. With deep integrations with popular CRM platforms and automation tools, Klenty streamlines sales workflows and boosts productivity for sales teams of all sizes.

GuideLLM is a powerful tool for evaluating and optimizing the deployment of large language models (LLMs). By simulating real-world inference workloads, GuideLLM helps users gauge the performance, resource needs, and cost implications of deploying LLMs on various hardware configurations. This approach ensures efficient, scalable, and cost-effective LLM inference serving while maintaining high service quality. Key features include performance evaluation, resource optimization, cost estimation, and scalability testing.

TPI-LLM (Tensor Parallelism Inference for Large Language Models) is a system designed to bring LLM functions to low-resource edge devices, addressing privacy concerns by enabling LLM inference on edge devices with limited resources. It leverages multiple edge devices for inference through tensor parallelism and a sliding window memory scheduler to minimize memory usage. TPI-LLM demonstrates significant improvements in TTFT and token latency compared to other models, and plans to support infinitely large models with low token latency in the future.

The NeMo Framework Launcher is a cloud-native tool designed for launching end-to-end NeMo Framework training jobs. It focuses on foundation model training for generative AI models, supporting large language model pretraining with techniques like model parallelism, tensor, pipeline, sequence, distributed optimizer, mixed precision training, and more. The tool scales to thousands of GPUs and can be used for training LLMs on trillions of tokens. It simplifies launching training jobs on cloud service providers or on-prem clusters, generating submission scripts, organizing job results, and supporting various model operations like fine-tuning, evaluation, export, and deployment.

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.

NVIDIA Generative AI Examples are state-of-the-art examples that are easy to deploy, test, and extend. All examples run on the high performance NVIDIA CUDA-X software stack and NVIDIA GPUs. These examples showcase the capabilities of NVIDIA's Generative AI platform, which includes tools, frameworks, and models for building and deploying generative AI applications.

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

Cosdata is a cutting-edge AI data platform designed to power the next generation search pipelines. It features immutability, version control, and excels in semantic search, structured knowledge graphs, hybrid search capabilities, real-time search at scale, and ML pipeline integration. The platform is customizable, scalable, efficient, enterprise-grade, easy to use, and can manage multi-modal data. It offers high performance, indexing, low latency, and high requests per second. Cosdata is designed to meet the demands of modern search applications, empowering businesses to harness the full potential of their data.

llmaz is an easy, advanced inference platform for large language models on Kubernetes. It aims to provide a production-ready solution that integrates with state-of-the-art inference backends. The platform supports efficient model distribution, accelerator fungibility, SOTA inference, various model providers, multi-host support, and scaling efficiency. Users can quickly deploy LLM services with minimal configurations and benefit from a wide range of advanced inference backends. llmaz is designed to optimize cost and performance while supporting cutting-edge researches like Speculative Decoding or Splitwise on Kubernetes.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Wenda is a platform for large-scale language model invocation designed to efficiently generate content for specific environments, considering the limitations of personal and small business computing resources, as well as knowledge security and privacy issues. The platform integrates capabilities such as knowledge base integration, multiple large language models for offline deployment, auto scripts for additional functionality, and other practical capabilities like conversation history management and multi-user simultaneous usage.

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.

AzureOpenAI-with-APIM is a repository that provides a one-button deploy solution for Azure API Management (APIM), Key Vault, and Log Analytics to work seamlessly with Azure OpenAI endpoints. It enables organizations to scale and manage their Azure OpenAI service efficiently by issuing subscription keys via APIM, delivering usage metrics, and implementing policies for access control and cost management. The repository offers detailed guidance on implementing APIM to enhance Azure OpenAI resiliency, scalability, performance, monitoring, and chargeback capabilities.

MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

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.

Falkon is a Python implementation of the Falkon algorithm for large-scale, approximate kernel ridge regression. The code is optimized for scalability to large datasets with tens of millions of points and beyond. Full kernel matrices are never computed explicitly so that you will not run out of memory on larger problems. Preconditioned conjugate gradient optimization ensures that only few iterations are necessary to obtain good results. The basic algorithm is a Nyström approximation to kernel ridge regression, which needs only three hyperparameters: 1. The number of centers M - this controls the quality of the approximation: a higher number of centers will produce more accurate results at the expense of more computation time, and higher memory requirements. 2. The penalty term, which controls the amount of regularization. 3. The kernel function. A good default is always the Gaussian (RBF) kernel (`falkon.kernels.GaussianKernel`).

DataChain is an open-source Python library for processing and curating unstructured data at scale. It supports AI-driven data curation using local ML models and LLM APIs, handles large datasets, and is Python-friendly with Pydantic objects. It excels at optimizing batch operations and is designed for offline data processing, curation, and ETL. Typical use cases include Computer Vision data curation, LLM analytics, and validation.

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