Best AI tools for< Build Streaming Ai Pipelines >
20 - AI tool Sites
SingleStore
SingleStore is a real-time data platform designed for apps, analytics, and gen AI. It offers faster hybrid vector + full-text search, fast-scaling integrations, and a free tier. SingleStore can read, write, and reason on petabyte-scale data in milliseconds. It supports streaming ingestion, high concurrency, first-class vector support, record lookups, and more.
Encord
Encord is a complete data development platform designed for AI applications, specifically tailored for computer vision and multimodal AI teams. It offers tools to intelligently manage, clean, and curate data, streamline labeling and workflow management, and evaluate model performance. Encord aims to unlock the potential of AI for organizations by simplifying data-centric AI pipelines, enabling the building of better models and deploying high-quality production AI faster.
Momentic
Momentic is a purpose-built AI tool for modern software testing, offering automation for E2E, UI, API, and accessibility testing. It leverages AI to streamline testing processes, from element identification to test generation, helping users shorten development cycles and enhance productivity. With an intuitive editor and the ability to describe elements in plain English, Momentic simplifies test creation and execution. It supports local testing without the need for a public URL, smart waiting for in-flight requests, and integration with CI/CD pipelines. Momentic is trusted by numerous companies for its efficiency in writing and maintaining end-to-end tests.
RunPod
RunPod is a cloud platform specifically designed for AI development and deployment. It offers a range of features to streamline the process of developing, training, and scaling AI models, including a library of pre-built templates, efficient training pipelines, and scalable deployment options. RunPod also provides access to a wide selection of GPUs, allowing users to choose the optimal hardware for their specific AI workloads.
Fetcher
Fetcher is an AI candidate sourcing tool designed for recruiters to streamline the talent acquisition process. It leverages advanced AI technology and expert teams to efficiently source high-quality candidate profiles that match specific hiring requirements. The tool also provides smart recruitment analytics, personalized diversity search criteria, and verified contact information to enhance candidate engagement and streamline the recruitment process. With robust technology integrations and a focus on automating processes, Fetcher aims to help companies of all sizes attract top talent and optimize their recruitment strategies.
HireList.io
HireList.io is an AI-driven recruitment software designed to streamline the hiring process for startups. It offers a range of features to help businesses target the right talent, connect with the right candidates, and build their dream team quickly and efficiently. HireList's AI-powered candidate filter narrows down the pool of applicants, highlighting only those who fit the bill. The platform also provides a streamlined hiring pipeline, taking businesses from job posting to welcoming their new hire. With HireList, businesses can create and tailor job postings, review and comment on candidates, and track their progress through the hiring process. The platform also offers communication automation, structured interviews, and performance tracking to help businesses refine their hiring practices.
Wedo AI
Wedo AI is an all-in-one AI-powered platform designed to help businesses attract customers, convert leads, and manage various aspects of online marketing, sales, and delivery. It offers a range of tools such as AI ads, chat bots, social media planner, websites, ecommerce store, memberships, CRM, email marketing, analytics, and more. Wedo AI aims to streamline processes, increase efficiency, and drive revenue growth for entrepreneurs, startups, influencers, non-profits, coaches, contractors, freelancers, and consultants. The platform provides features for managing finances, automating billing, creating funnels, building websites, selling products, engaging with customers, and analyzing data to make informed decisions.
SubSync
SubSync is the #1 CRM for Home Services that leverages AI technology to help home service businesses accelerate their revenue by generating, engaging, and converting new leads. It offers a comprehensive all-in-one platform for lead prospecting, marketing automation, and sales management. SubSync's innovative features streamline the process of finding and connecting with potential customers, empowering sales teams to focus on quality interactions. With SubSync, users can automate time-consuming workflows, track campaign performance, and optimize their sales funnel, ultimately leading to increased efficiency and higher ROI.
AI SDK
The AI SDK is a free open-source library designed to empower developers in building AI-powered products. Developed by the creators of Next.js, it offers a range of features such as a chat-based web development companion, a Unified Provider API for seamless integration with different AI providers, generative UI for creating dynamic interfaces, framework-agnostic compatibility, and streaming AI responses for instant user feedback. The SDK has received positive feedback from developers for its ease of use and efficiency in automating processes.
ai_licia
ai_licia is an AI tool designed to take online communities to the next level by providing a customizable co-host experience for Twitch and Discord platforms. With unique personalities, cross-platform memory, and the ability to hear, write, and speak, ai_licia aims to engage, entertain, and build communities in a personalized way.
LMNT
LMNT is an ultrafast and lifelike AI speech application that offers a developer API for creating conversational apps, agents, and games. It provides lifelike voices with studio-quality voice clones, engineered by an ex-Google team for reliability under pressure. Users can create engaging product marketing videos, build lightning-fast conversational experiences, and simplify content creation at scale. The application features a user-friendly interface, versatile voice cloning options, and downloadable content for easy integration into projects. With Python and Node SDKs, low latency streaming, and robust documentation, LMNT empowers developers to enhance their applications with high-quality voice synthesis.
Outspeed
Outspeed is a platform for Realtime Voice and Video AI applications, providing networking and inference infrastructure to build fast, real-time voice and video AI apps. It offers tools for intelligence across industries, including Voice AI, Streaming Avatars, Visual Intelligence, Meeting Copilot, and the ability to build custom multimodal AI solutions. Outspeed is designed by engineers from Google and MIT, offering robust streaming infrastructure, low-latency inference, instant deployment, and enterprise-ready compliance with regulations such as SOC2, GDPR, and HIPAA.
MarsX
MarsX is an AI-powered development tool that combines AI, NoCode, Code, and MicroApps to revolutionize software development. It offers a wide range of features such as AI-powered landing page builder, Micro-AppStore, NFT marketplace, Uber for X, social network creation, No-Code builder, peer-to-peer marketplace, video streaming portal, photo-sharing app, and over 1000 micro-apps for various purposes. The platform enables developers to save time and resources by leveraging AI technology and pre-built tools for different tasks.
Symbl.ai
Symbl.ai is a real-time voice AI platform that enables businesses to extract insights from unstructured live calls. It offers a range of features, including real-time transcription, sentiment analysis, question detection, and topic tracking. Symbl.ai's platform is powered by Nebula, a proprietary LLM that is specialized in understanding human interactions in streaming mode. This allows Symbl.ai to provide accurate and low-latency insights that can be used to improve customer service, sales, and compliance.
OpenLIT
OpenLIT is an AI application designed as an Observability tool for GenAI and LLM applications. It empowers model understanding and data visualization through an interactive Learning Interpretability Tool. With OpenTelemetry-native support, it seamlessly integrates into projects, offering features like fine-tuning performance, real-time data streaming, low latency processing, and visualizing data insights. The tool simplifies monitoring with easy installation and light/dark mode options, connecting to popular observability platforms for data export. Committed to OpenTelemetry community standards, OpenLIT provides valuable insights to enhance application performance and reliability.
JFrog ML
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.
AI Studio
AI Studio is an advanced AI application that empowers users to build powerful AI systems effortlessly. By combining a variety of top AI tools, AI Studio enables users to tackle their most challenging problems with ease. The platform offers a seamless user experience through a rich web UI and upcoming desktop version. With features like command line tools and comprehensive documentation, AI Studio is designed to streamline the AI development process for both beginners and experts.
Downtobid
Downtobid is an AI-powered bidding software designed for General Contractors. It helps in turning construction plans into Bid Invites in minutes by identifying bid packages in drawings, creating custom subcontractor invite lists, and streamlining bidding processes. The platform offers features like AI-powered scope reviews, smart planroom creation, project-specific sublists, personalized email communication, and real-time contractor data. Downtobid aims to save time, improve bid responses, and enhance project success by leveraging artificial intelligence technology.
Humley
Humley is a Conversational AI platform that allows users to build and launch AI assistants in under an hour. The platform provides a no-code environment for creating self-serve experiences and managing AI outputs. Humley aims to revolutionize customer experiences and boost efficiencies by making Conversational AI accessible and safe for all users. With features like Knowledge Search, Build Flows, Integrate with Systems, Capture Feedback, and Multi-Channel Support, Humley Studio offers a comprehensive toolkit for creating engaging conversational experiences. The platform empowers businesses to deliver exceptional customer service, streamline access to AI models, and improve operational efficiencies.
Realflow.ai
Realflow.ai is an AI-powered platform that offers GPT & AI capabilities for Citizen Developers. It provides a unique Visual Data Pathways Builder, 185 File, Database and SaaS Connectors, and Excel Formula Transforms for data manipulation. The platform simplifies data integration and transformation processes by eliminating the need for scripting languages and SQL queries. Realflow.ai aims to empower users with no-code solutions to build integrations and streamline data workflows across various platforms.
20 - Open Source AI Tools
holoscan-sdk
The Holoscan SDK is part of NVIDIA Holoscan, the AI sensor processing platform that combines hardware systems for low-latency sensor and network connectivity, optimized libraries for data processing and AI, and core microservices to run streaming, imaging, and other applications, from embedded to edge to cloud. It can be used to build streaming AI pipelines for a variety of domains, including Medical Devices, High Performance Computing at the Edge, Industrial Inspection and more.
jina
Jina is a tool that allows users to build multimodal AI services and pipelines using cloud-native technologies. It provides a Pythonic experience for serving ML models and transitioning from local deployment to advanced orchestration frameworks like Docker-Compose, Kubernetes, or Jina AI Cloud. Users can build and serve models for any data type and deep learning framework, design high-performance services with easy scaling, serve LLM models while streaming their output, integrate with Docker containers via Executor Hub, and host on CPU/GPU using Jina AI Cloud. Jina also offers advanced orchestration and scaling capabilities, a smooth transition to the cloud, and easy scalability and concurrency features for applications. Users can deploy to their own cloud or system with Kubernetes and Docker Compose integration, and even deploy to JCloud for autoscaling and monitoring.
pathway
Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.
llm-app-stack
LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.
nnstreamer
NNStreamer is a set of Gstreamer plugins that allow Gstreamer developers to adopt neural network models easily and efficiently and neural network developers to manage neural network pipelines and their filters easily and efficiently.
baml
BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources ![](https://img.shields.io/discord/1119368998161752075.svg?logo=discord&label=Discord%20Community) [Discord Community](https://discord.gg/boundaryml) ![](https://img.shields.io/twitter/follow/boundaryml?style=social) [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience: ![](docs/images/v3/prompt_view.gif) Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux ![](https://img.shields.io/badge/Python-3.8+-default?logo=python)![](https://img.shields.io/badge/Typescript-Node_18+-default?logo=typescript) | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |
mage-ai
Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.
awesome-langchain
LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.
superduperdb
SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.
swiftide
Swiftide is a fast, streaming indexing and query library tailored for Retrieval Augmented Generation (RAG) in AI applications. It is built in Rust, utilizing parallel, asynchronous streams for blazingly fast performance. With Swiftide, users can easily build AI applications from idea to production in just a few lines of code. The tool addresses frustrations around performance, stability, and ease of use encountered while working with Python-based tooling. It offers features like fast streaming indexing pipeline, experimental query pipeline, integrations with various platforms, loaders, transformers, chunkers, embedders, and more. Swiftide aims to provide a platform for data indexing and querying to advance the development of automated Large Language Model (LLM) applications.
ax
Ax is a Typescript library that allows users to build intelligent agents inspired by agentic workflows and the Stanford DSP paper. It seamlessly integrates with multiple Large Language Models (LLMs) and VectorDBs to create RAG pipelines or collaborative agents capable of solving complex problems. The library offers advanced features such as streaming validation, multi-modal DSP, and automatic prompt tuning using optimizers. Users can easily convert documents of any format to text, perform smart chunking, embedding, and querying, and ensure output validation while streaming. Ax is production-ready, written in Typescript, and has zero dependencies.
AI-System-School
AI System School is a curated list of research in machine learning systems, focusing on ML/DL infra, LLM infra, domain-specific infra, ML/LLM conferences, and general resources. It provides resources such as data processing, training systems, video systems, autoML systems, and more. The repository aims to help users navigate the landscape of AI systems and machine learning infrastructure, offering insights into conferences, surveys, books, videos, courses, and blogs related to the field.
llmware
LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.
chronon
Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.
R2R
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.
superduper
superduper.io is a Python framework that integrates AI models, APIs, and vector search engines directly with existing databases. It allows hosting of models, streaming inference, and scalable model training/fine-tuning. Key features include integration of AI with data infrastructure, inference via change-data-capture, scalable model training, model chaining, simple Python interface, Python-first approach, working with difficult data types, feature storing, and vector search capabilities. The tool enables users to turn their existing databases into centralized repositories for managing AI model inputs and outputs, as well as conducting vector searches without the need for specialized databases.
deeplake
Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.
20 - OpenAI Gpts
Relume
An interface for Relume's AI Site Builder, designed to streamline the web design and development process
Centesimus Annus Pro Pontifice GPT
Expert in Church's social doctrine, aiding in understanding and spreading teachings.
Build a Brand
Unique custom images based on your input. Just type ideas and the brand image is created.
Beam Eye Tracker Extension Copilot
Build extensions using the Eyeware Beam eye tracking SDK
Business Model Canvas Strategist
Business Model Canvas Creator - Build and evaluate your business model
League Champion Builder GPT
Build your own League of Legends Style Champion with Abilities, Back Story and Splash Art
RenovaTecno
Your tech buddy helping you refurbish or build a PC from scratch, tailored to your needs, budget, and language.
Gradle Expert
Your expert in Gradle build configuration, offering clear, practical advice.
XRPL GPT
Build on the XRP Ledger with assistance from this GPT trained on extensive documentation and code samples.