Best AI tools for< scale outreach efforts >

Quicklines is an AI-powered tool designed to revolutionize cold outreach campaigns. It offers lifetime access for a one-time fee of $59, providing users with personalized cold email lines generated by AI. Quicklines is 40x faster and 6x cheaper than traditional methods, helping businesses scale their outreach efforts efficiently. By scraping personalized information from LinkedIn profiles, Quicklines assists in creating natural and authentic first lines that lead to higher reply rates. The tool has received positive reviews for its effectiveness in generating interested leads and improving email deliverability.

Smartlead is an AI-powered cold email outreach tool designed to help businesses scale their outreach efforts seamlessly. With features like unlimited mailboxes, automated warmups, multi-channel infrastructure, and a unified master inbox, Smartlead empowers users to manage their entire revenue cycle in one place. It ensures high email deliverability, personalized interactions, and efficient lead management, making it a valuable asset for lead generation agencies, marketing agencies, sales leaders, and recruiters.

lemlist is an advanced sales engagement platform that revolutionizes prospecting by offering personalized outreach, deliverability solutions, and multi-channel prospecting capabilities. It helps users find buyer-ready prospects, generate personalized multichannel campaigns, and avoid spam filters. With features like AI-generated sequences, warm-up tools, and CRM integrations, lemlist empowers users to automate their outreach efforts and increase reply rates.

Celential.ai is an AI recruiting tool that leverages AI technology to streamline the recruitment process for technical, sales, and diversity hiring. The platform offers features such as hyper-personalized outreach, diversity hiring powered by AI, and deep technical recruiting expertise. Celential.ai helps companies scale their recruitment efforts efficiently by delivering strong pipelines of qualified candidates in a short time frame, resulting in significant cost savings compared to traditional sourcing methods.

Storipress is a blog workflow platform that helps businesses scale content creation, profile readers, and personalize outreach. It offers features such as content creation, workflow management, AI-powered writing assistance, and email personalization. Storipress integrates with various tools and platforms, including CMS, social media, and CRM systems. It is designed to help businesses streamline their content operations and improve their marketing and sales efforts.

Clay is an AI-powered data enrichment and outreach automation tool designed to help go-to-market teams scale personalized outbound campaigns. It combines 75+ data enrichment tools, AI capabilities, and automation features to streamline lead generation, data cleaning, and personalized messaging. With access to 50+ data providers, Clay offers comprehensive coverage of information and enables users to connect, enrich, and sync their CRM data effortlessly. The platform also features AI web scraping, personalized email building, automated inbound and outbound processes, and data formatting functionalities.

Outboundly is a Chrome extension that simplifies cold outreach by leveraging AI to generate personalized prospecting messages. It offers features such as AI-powered email writing, automated workflows, and LinkedIn messaging capabilities. Outboundly helps users create highly personalized emails based on prospect information, resulting in higher response rates. The software transforms the process of creating personalized prospect emails into a quick and effortless task, making it easy to scale cold outreach while maintaining personalization.

Had-a Call is an AI-powered call management platform that revolutionizes customer outreach by breaking down language barriers and building stronger relationships with customers worldwide. It offers multi-language call center software, real-time call performance analytics, and scalable solutions for data-driven customer engagement. With Had-a Call, businesses can effortlessly scale their call center operations and make data-driven decisions to drive customer engagement and improve performance.

Autobound.ai is an AI-powered platform that enables users to write hyper-personalized emails 60-120 times faster than the average seller. The platform offers an AI Email Writer that helps in creating hyper-personalized content, finding and exporting leads, and providing A+ email suggestions on the fly. Autobound also features AI-powered sequencing, personalization API, and a 'Write with AI' button for effortless email drafting. The platform revolutionizes personalized messaging by combining expansive datasets to transform contacts into connections.

Mails.ai is an AI-powered cold email software that helps businesses automate their email campaigns, connect with unlimited email accounts, and maximize their outreach. With its advanced features like AI email writer, email verification, and inbox rotation, Mails.ai ensures high deliverability and increased replies, leading to more revenue and business growth.

QRev is an AI-powered sales tool designed to revolutionize the sales process by automating mundane tasks and allowing salespeople to focus on closing deals. It offers features such as researching prospects, scaling outreach, competitive research, and personalized email campaigns. QRev aims to save time and increase efficiency for sales teams, providing modern CRM capabilities and insights into sales calls. With QRev, users can access leads from a massive database, run research 24/7, and personalize campaign sequences at scale.

folk is a CRM platform designed to help users build real relationships to close winning deals. It offers features such as pipeline management, integrations, messages & sequences, and 1-click enrichment. With workspace templates, customizable pipeline views, and contact sync capabilities, folk aims to simplify CRM organization and streamline user workflows. The platform also provides AI-generated variables, conversation templates, and social signals for personalized outreach and improved sales performance. Trusted by over 2000 award-winning agencies and firms, folk is a comprehensive CRM solution for various roles and workflows.

Reply.io is a sales engagement platform that helps businesses automate and scale their sales outreach, acquire new customers, and grow revenue faster. It offers a range of features including multichannel sales engagement, email deliverability tools, AI sales assistant, B2B contact database, meeting scheduling, and analytics. Reply.io integrates with popular CRMs and other sales tools, making it a comprehensive solution for sales teams.

Persana AI is an AI-powered sales prospecting platform that helps businesses find, enrich, and personalize their outbound outreach at scale. With Persana AI, sales teams can quickly build targeted lead lists from a variety of data sources, including LinkedIn, Apollo, Salesforce, ContactOut, GitHub, and more. Persana AI also offers a suite of AI-powered automations that can help sales teams save time and improve their results. These automations include AI-powered email personalization, lead scoring, and sales triggers.

SaasPedia is a website that provides resources and services to help SaaS businesses grow and scale their traffic, sales, and revenue with organic marketing campaigns and strategies. The website offers a variety of resources, including a blog, ebooks, webinars, and tools, as well as services such as cold outreach, SEO, and content marketing. SaasPedia also has a directory of SaaS companies and a list of SaaS-related podcasts and YouTube channels.

Gan.ai is an AI-powered platform that enables users to create personalized videos at scale. Users can record unlimited videos and easily personalize them to book more meetings, share ideas faster, and close more deals. The platform offers a lifetime-free video recorder, allowing users to record lightning-fast videos using the web app or Chrome Extension. Gan.ai also provides features like personalized subtitles, dynamic website scrolling, personalized landing pages, viewer-level analytics, and integrations with popular tools like Hubspot and Salesforce.

eCold.ai is an AI-powered cold email personalization tool that helps businesses generate personalized sales emails at scale. With eCold.ai, you can upload your prospect list and get personalized email lines tailored to each prospect's LinkedIn profile. This can help you increase your reply rates and close more deals.

ColdIQ is an AI-powered sales prospecting tool that helps B2B companies with revenue above $100k/month to build outbound systems that sell for them. The tool offers end-to-end cold outreach campaign setup and management, email infrastructure setup and warmup, audience research and targeting, data scraping and enrichment, campaigns optimization, sending automation, sales systems implementation, training on tools best practices, sales tools recommendations, free gap analysis, sales consulting, and copywriting frameworks. ColdIQ leverages AI to tailor messaging to each prospect, automate outreach, and flood calendars with opportunities.

SendEngage is a B2B cold email platform that uses AI to read, categorize and route interested replies directly to your sales team, at any scale. It offers features such as unlimited inbox rotation, message variation split testing, automated follow-ups, open/reply/sentiment tracking, and AI reply management. With SendEngage, businesses can create high converting, automated email campaigns, manage replies and engage with interested prospects, and hand off interested leads directly to sales reps' main inboxes and map to CRM records.

HeyGen is an AI-powered video creation platform that allows users to create studio-quality videos with AI-generated avatars and voices. With HeyGen, you can create videos for any need, including sales outreach, content marketing, product marketing, learning and development, and more. HeyGen is easy to use and affordable, making it a great option for businesses of all sizes.

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.

A curated list of Generative AI projects, tools, artworks, and models

Scale's LLM Engine is an open-source Python library, CLI, and Helm chart that provides everything you need to serve and fine-tune foundation models, whether you use Scale's hosted infrastructure or do it in your own cloud infrastructure using Kubernetes.

Colossal-AI is a deep learning system for large-scale parallel training. It provides a unified interface to scale sequential code of model training to distributed environments. Colossal-AI supports parallel training methods such as data, pipeline, tensor, and sequence parallelism and is integrated with heterogeneous training and zero redundancy optimizer.

Bittensor is an internet-scale neural network that incentivizes computers to provide access to machine learning models in a decentralized and censorship-resistant manner. It operates through a token-based mechanism where miners host, train, and procure machine learning systems to fulfill verification problems defined by validators. The network rewards miners and validators for their contributions, ensuring continuous improvement in knowledge output. Bittensor allows anyone to participate, extract value, and govern the network without centralized control. It supports tasks such as generating text, audio, images, and extracting numerical representations.

STaRK is a large-scale semi-structure retrieval benchmark on Textual and Relational Knowledge Bases. It provides natural-sounding and practical queries crafted to incorporate rich relational information and complex textual properties, closely mirroring real-life scenarios. The benchmark aims to assess how effectively large language models can handle the interplay between textual and relational requirements in queries, using three diverse knowledge bases constructed from public sources.

EduChat is a large-scale language model-based chatbot system designed for intelligent education by the EduNLP team at East China Normal University. The project focuses on developing a dialogue-based language model for the education vertical domain, integrating diverse education vertical domain data, and providing functions such as automatic question generation, homework correction, emotional support, course guidance, and college entrance examination consultation. The tool aims to serve teachers, students, and parents to achieve personalized, fair, and warm intelligent education.

EmoLLM is a series of large-scale psychological health counseling models that can support **understanding-supporting-helping users** in the psychological health counseling chain, which is fine-tuned from `LLM` instructions. Welcome everyone to star~⭐⭐. The currently open source `LLM` fine-tuning configurations are as follows:

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.

AgentScope is a multi-agent platform designed to empower developers to build multi-agent applications with large-scale models. It features three high-level capabilities: Easy-to-Use, High Robustness, and Actor-Based Distribution. AgentScope provides a list of `ModelWrapper` to support both local model services and third-party model APIs, including OpenAI API, DashScope API, Gemini API, and ollama. It also enables developers to rapidly deploy local model services using libraries such as ollama (CPU inference), Flask + Transformers, Flask + ModelScope, FastChat, and vllm. AgentScope supports various services, including Web Search, Data Query, Retrieval, Code Execution, File Operation, and Text Processing. Example applications include Conversation, Game, and Distribution. AgentScope is released under Apache License 2.0 and welcomes contributions.

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`).

This repository provides a real-world trace dataset of LLM serving workloads for research and academic purposes. The dataset includes two files, BurstGPT.csv with trace data for 2 months including some failures, and BurstGPT_without_fails.csv without any failures. Users can scale the RPS in the trace, model patterns, and leverage the trace for various evaluations. Future plans include updating the time range of the trace, adding request end times, updating conversation logs, and open-sourcing a benchmark suite for LLM inference. The dataset covers 61 consecutive days, contains 1.4 million lines, and is approximately 50MB in size.

MicroLens is a content-driven micro-video recommendation dataset at scale. It provides a large dataset with multimodal data, including raw text, images, audio, video, and video comments, for tasks such as multi-modal recommendation, foundation model building, and fairness recommendation. The dataset is available in two versions: MicroLens-50K and MicroLens-100K, with extracted features for multimodal recommendation tasks. Researchers can access the dataset through provided links and reach out to the corresponding author for the complete dataset. The repository also includes codes for various algorithms like VideoRec, IDRec, and VIDRec, each implementing different video models and baselines.

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

DeepSeek is a new experimental architecture for a large language model (LLM) powered internet-scale retrieval engine. Unlike current research agents designed as answer engines, DeepSeek aims to process a vast amount of sources to collect a comprehensive list of entities and enrich them with additional relevant data. The end result is a table with retrieved entities and enriched columns, providing a comprehensive overview of the topic. DeepSeek utilizes both standard keyword search and neural search to find relevant content, and employs an LLM to extract specific entities and their associated contents. It also includes a smaller answer agent to enrich the retrieved data, ensuring thoroughness. DeepSeek has the potential to revolutionize research and information gathering by providing a comprehensive and structured way to access information from the vastness of the internet.

LitServe is a high-throughput serving engine for deploying AI models at scale. It generates an API endpoint for a model, handles batching, streaming, autoscaling across CPU/GPUs, and more. Built for enterprise scale, it supports every framework like PyTorch, JAX, Tensorflow, and more. LitServe is designed to let users focus on model performance, not the serving boilerplate. It is like PyTorch Lightning for model serving but with broader framework support and scalability.

LitServe is a high-throughput serving engine designed for deploying AI models at scale. It generates an API endpoint for models, handles batching, streaming, and autoscaling across CPU/GPUs. LitServe is built for enterprise scale with a focus on minimal, hackable code-base without bloat. It supports various model types like LLMs, vision, time-series, and works with frameworks like PyTorch, JAX, Tensorflow, and more. The tool allows users to focus on model performance rather than serving boilerplate, providing full control and flexibility.

SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.

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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