Alternatives to RunComfy

Our decentralized platform streamlines AI data collection and labeling through a worldwide contributor network. By combining crowdsourcing with blockchain technology, we deliver high-quality, traceable datasets. Platform Highlights: Worldwide Collection: Tap into global contributors for comprehensive data gathering Blockchain Security: Every contribution tracked and verified on-chain Quality Focus: Expert validation ensures exceptional data standards Platform Benefits: Rapid scaling of data collection Complete data providence tracking Validated datasets ready for AI use Cost-efficient global operations Flexible contributor network How It Works: Define Your Needs: Create your data collection task Community Activation: Global contributors notified and start gathering data Quality Control: Human verification layer validates all contributions Sample Review: Get dataset sample for approval Full Delivery: Complete dataset delivered once approved

Your ML model can be served in minutes in any cloud. Unified model packaging format that allows online and offline delivery on any platform. Our micro-batching technology allows for 100x more throughput than a regular flask-based server model server. High-quality prediction services that can speak the DevOps language, and seamlessly integrate with common infrastructure tools. Unified format for deployment. High-performance model serving. Best practices in DevOps are incorporated. The service uses the TensorFlow framework and the BERT model to predict the sentiment of movie reviews. DevOps-free BentoML workflow. This includes deployment automation, prediction service registry, and endpoint monitoring. All this is done automatically for your team. This is a solid foundation for serious ML workloads in production. Keep your team's models, deployments and changes visible. You can also control access via SSO and RBAC, client authentication and auditing logs.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

MimicPC is an AI platform that runs in the cloud, allowing you to avoid the need for high-performance computers or GPUs. Run cutting-edge applications such as Stable Diffusion, ComfyUI, Automatic 111t face Fusion, RVC, Ollama and Fooocus directly from your browser. MimicPC is the perfect tool for anyone who wants to bring their creative visions to life.

DiffusionHub, a dynamic cloud-based platform, uses AI to streamline image and video creation. It offers a 30-minute free trial to allow users to explore the capabilities of the platform before committing. The platform is intuitive and user-friendly, with options such as Automatic1111, ComfyUI and Kohya, which eliminate the need for complicated installations and coding. It offers a comfortable, intuitive workflow interface to create AI art with ease. DiffusionHub has a competitive pricing that starts at $0.99 an hour. It also provides a private and secure session, protecting user confidentiality and preventing other users from accessing models or generations.

Our dashboard allows you to dig deeper into analytics, allowing you to verify the information you need to enter requests into Guardrails. Our library of ready-to-use validators will help you unlock efficiency. Validation for diverse use cases can optimize your workflow. Boost your projects by leveraging a dynamic framework that allows you to create, manage, and reuse custom validators. The versatility of the software is matched by its ease of use, allowing it to be used for a wide range innovative applications. You can quickly generate another output option by indicating the error and verifying it. Assures that the outcomes are in line, with expectations, accuracy, correctness, reliability, and interactions with LLMs.

Spend less time on your IDE and nodes that you cannot run. We manage dependencies, and we offer free GPUs so you can concentrate on building. Do not be limited by a single computer. Our proprietary autoscaling technology scales up and down to meet demand. Comfy UI workflows can be created, shared and scaled in a matter of minutes.

Oumi, a platform open-source, streamlines the lifecycle of foundational models from data preparation to training and evaluation. It supports training and fine tuning models with parameters ranging from 10 millions to 405 billion using state-of the-art techniques like SFT, LoRA QLoRA and DPO. The platform supports text and multimodal models including architectures such as Llama DeepSeek Qwen and Phi. Oumi provides tools for data curation and synthesis, allowing users to efficiently generate and manage training datasets. It integrates with popular engines such as vLLM and SGLang for deployment, ensuring efficient serving of models. The platform provides comprehensive evaluation capabilities to assess model performance using standard benchmarks. Oumi is designed to be flexible and can run in a variety of environments, including local laptops, cloud infrastructures like AWS, Azure GCP, Lambda, etc.

One development environment for all data science workflows. Natively analyze your data without the need to switch between services. Data to training at scale Models can be built and trained 5X faster than traditional notebooks. Scale up model development using simple connectivity to Vertex AI Services. Access to data is simplified and machine learning is made easier with BigQuery Dataproc, Spark and Vertex AI integration. Vertex AI training allows you to experiment and prototype at scale. Vertex AI Workbench allows you to manage your training and deployment workflows for Vertex AI all from one location. Fully managed, scalable and enterprise-ready, Jupyter-based, fully managed, scalable, and managed compute infrastructure with security controls. Easy connections to Google Cloud's Big Data Solutions allow you to explore data and train ML models.

With a single command, you can train and serve large AI models in scale. You can simply point to your S3 bucket. We take care of the rest: orchestration, efficiency and node failures. Simple and scalable. MosaicML allows you to train and deploy large AI model on your data in a secure environment. Keep up with the latest techniques, recipes, and foundation models. Our research team has developed and rigorously tested these recipes. In just a few easy steps, you can deploy your private cloud. Your data and models will never leave the firewalls. You can start in one cloud and continue in another without missing a beat. Own the model trained on your data. Model decisions can be better explained by examining them. Filter content and data according to your business needs. Integrate seamlessly with your existing data pipelines and experiment trackers. We are cloud-agnostic and enterprise-proven.

Graydient AI offers unbeatable value in AI with unlimited image generation and LLM chats. Perfect for beginners and pros alike, it features intuitive tools like preset workflows (e.g., "realistic iPhone photo" or "anime movie poster") for quick, high-definition results, plus deep customization options, including a REST API. With over 10,000 preloaded checkpoints, LoRAs, embeddings, and support for ComfyUI JSON import, pros can push creativity further. Popular models like Flux.1 Dev FP32, Stable Diffusion 3.5, and Meta Llama 3.1 70B come preloaded, and you can train unlimited LoRAs or automate workflows with Recipes via Telegram or the web. Try Graydient AI risk-free with their satisfaction guarantee!

Saagie's cloud data factory allows you to create and manage your data & AI project in a single interface. It can be deployed in just a few seconds. Saagie data factories allows you to develop your AI models and test them in a safe environment. With a single interface, you can get your data and AI project off the ground and centralize your team to make rapid progress. Saagie is the platform for you, no matter what your maturity level. From your first data project, to a data and AI-driven strategy. Unifying your work onto a single platform will simplify your workflows, increase your productivity and help you make better decisions. Orchestrate your data pipelines to transform raw data into powerful insights. Quickly access the information you require to make better decisions. Simplify management and scaleability of your AI and data infrastructure. Accelerate your AI, deep learning, and machine learning models.

Here is where the future of AI development begins. Modular is a composable, integrated suite of tools which simplifies your AI infrastructure, allowing your team to develop, deploy and innovate faster. Modular's inference engines unify AI industry frameworks with hardware. This allows you to deploy into any cloud or on-prem environments with minimal code changes, unlocking unmatched portability, performance and usability. Move your workloads seamlessly to the best hardware without rewriting your models or recompiling them. Avoid lock-in, and take advantage of cloud performance and price improvements without migration costs.

Substrate is a platform for agentic AI. Elegant abstractions, high-performance components such as optimized models, vector databases, code interpreter and model router, as well as vector databases, code interpreter and model router. Substrate was designed to run multistep AI workloads. Substrate will run your task as fast as it can by connecting components. We analyze your workload in the form of a directed acyclic network and optimize it, for example merging nodes which can be run as a batch. Substrate's inference engine schedules your workflow graph automatically with optimized parallelism. This reduces the complexity of chaining several inference APIs. Substrate will parallelize your workload without any async programming. Just connect nodes to let Substrate do the work. Our infrastructure ensures that your entire workload runs on the same cluster and often on the same computer. You won't waste fractions of a sec per task on unnecessary data transport and cross-regional HTTP transport.

YiMeta is an AI tool website platform that helps users create and customize AI-powered tools. The key features are: • One-Click Creation of Websites: YiMeta generates SEO-optimized pages with AI, and they are ready for use. Users can edit the content further to improve website conversion rates. • Rich Collection AI Tools: YiMeta provides over 100 AI tools that are versatile and support unique workflow editing. These tools are integrated with ComfyUI workflows. Users can create tools instantly, whether they are text, image or video-related. • Professional SEO Structure management: YiMeta's SEO experts leverage their extensive experience in creating content for tool websites to ensure that they are successful. • Convenient financial management: YiMeta offers comprehensive analytics of traffic and financial data to enable users to focus on keyword optimization and business growth.

A managed PaaS that includes a low-code visual editor, VectorDB and integrations with apps and models to build, test, and deploy high-performance AI applications on the edge. Eliminate costly and error-prone work. Drag and drop agents, apps, data and models to find the best solution. Deployment in less than 60 seconds, and a 50% reduction in latency. Observe, iterate, and test seamlessly. Visibility and tools are essential for accuracy and reliability. Use data-driven decision making with reports on usage, LLM and request. View real-time traces per node. Experiments allow you to optimize embeddings and prompts, models and more. All you need to launch and iterate at large scale. Community of smart-minded builders who share their insights, experiences & feedback. Distilling the most useful tips, tricks and techniques for AI application developers. A platform that allows you to build agentic systems as if you were a 100-person team. A simple and intuitive frontend for managing AI applications and collaborating with them.

MakerSuite simplifies this process. MakerSuite allows you to easily tune custom models, iterate on prompts and augment your data with synthetic data. MakerSuite allows you to export your prompts as code in your favorite languages, such as Python and Node.js, when you are ready to move on to code.

Simplismart’s fastest inference engine allows you to fine-tune and deploy AI model with ease. Integrate with AWS/Azure/GCP, and many other cloud providers, for simple, scalable and cost-effective deployment. Import open-source models from popular online repositories, or deploy your custom model. Simplismart can host your model or you can use your own cloud resources. Simplismart allows you to go beyond AI model deployment. You can train, deploy and observe any ML models and achieve increased inference speed at lower costs. Import any dataset to fine-tune custom or open-source models quickly. Run multiple training experiments efficiently in parallel to speed up your workflow. Deploy any model to our endpoints, or your own VPC/premises and enjoy greater performance at lower cost. Now, streamlined and intuitive deployments are a reality. Monitor GPU utilization, and all of your node clusters on one dashboard. On the move, detect any resource constraints or model inefficiencies.

NVIDIA Base Command™ is an enterprise-class AI software service that allows businesses and their data scientists accelerate AI development. Base Command Platform, which is part of the NVIDIA DGX™ platform provides centralized, hybrid controls for AI training projects. It is compatible with NVIDIA DGX cloud and NVIDIA DGX superPOD. Base Command Platform in conjunction with NVIDIA's accelerated AI infrastructure provides a cloud hosted solution for AI development. Users can avoid the overheads and pitfalls associated with deploying and operating a DIY platform. Base Command Platform configures and manages AI workflows, provides integrated dataset management and executes them using the right-sized resources, ranging from a single GPU up to large-scale multi-node cloud clusters or on-premises. The platform is constantly updated by NVIDIA engineers and researchers, who rely on it daily.

Generative AI has a profound impact on virtually every industry. It opens up new opportunities for creative workers and knowledge to solve the world's most pressing problems. NVIDIA is empowering generative AI with a powerful suite of cloud services, pretrained foundation models, cutting-edge frameworks and optimized inference engines. NVIDIA AI Foundations is an array of cloud services that enable customization across use cases in areas like text (NVIDIA NeMo™, NVIDIA Picasso), or biology (NVIDIA BIONeMo™. Enjoy the full potential of NeMo, Picasso and BioNeMo cloud-based services powered by NVIDIA DGX™ Cloud, an AI supercomputer. Marketing copy, storyline creation and global translation in many different languages. News, email, meeting minutes and information synthesis.

A simple web API allows you to fine-tune your LLMs and receive completions. No infrastructure is required. Instantly create private AI applications that comply with SOC2-standards. Our developer platform makes it easy to customize models for your specific use case. Select the base model and define the data that you want to teach. We will take care of everything else. With a single API, you can integrate private LLMs with your applications. No more deployment, orchestration or infrastructure headaches. The most powerful OSS available -- highly generalized capabilities with amazing storytelling and reasoning capabilities. Use a fully unlocked LLM for the best internal automation systems in your company.

The Intel Distribution of OpenVINO makes it easy to adopt and maintain your code. Open Model Zoo offers optimized, pre-trained models. Model Optimizer API parameters make conversions easier and prepare them for inferencing. The runtime (inference engines) allows you tune for performance by compiling an optimized network and managing inference operations across specific devices. It auto-optimizes by device discovery, load balancencing, inferencing parallelism across CPU and GPU, and many other functions. You can deploy the same application to multiple host processors and accelerators (CPUs. GPUs. VPUs.) and environments (on-premise or in the browser).

Multi-model AI can help you build a better AI. AI models are an entirely new type of building block. Sieve makes it easy to use these building block to understand audio, create video, and more. The latest models are available in just a few line of code and there is a set of production-ready applications for many different use cases. Import your favorite models like Python packages. Visualize results using auto-generated interfaces created for your entire team. Easily deploy custom code. Define your environment computation in code and deploy it with a single command. Fast, scalable infrastructure with no hassle. Sieve is designed to scale automatically as your traffic grows with no extra configuration. Package models using a simple Python decorator, and deploy them instantly. A fully-featured observability layer that allows you to see what's going on under the hood. Pay only for the seconds you use. Take full control of your costs.

There are options for every business to train deep and machine learning models efficiently. There are AI accelerators that can be used for any purpose, from low-cost inference to high performance training. It is easy to get started with a variety of services for development or deployment. Tensor Processing Units are ASICs that are custom-built to train and execute deep neural network. You can train and run more powerful, accurate models at a lower cost and with greater speed and scale. NVIDIA GPUs are available to assist with cost-effective inference and scale-up/scale-out training. Deep learning can be achieved by leveraging RAPID and Spark with GPUs. You can run GPU workloads on Google Cloud, which offers industry-leading storage, networking and data analytics technologies. Compute Engine allows you to access CPU platforms when you create a VM instance. Compute Engine provides a variety of Intel and AMD processors to support your VMs.

Public datasets can help you improve the accuracy of your machine-learning models. Use curated datasets to save time on data preparation and discovery. These datasets are ready for use in machine-learning workflows and can be accessed from Azure services. Consider real-world factors which can have an impact on business outcomes. By incorporating features of curated datasets in your machine learning model, you can improve the accuracy and reduce the time required for data preparation. Share datasets with the growing community of data analysts and developers. Azure Open Datasets can be used to deliver insights at hyperscale with Azure's machine-learning and data analytics solutions. Open Datasets are free to use. Open Datasets are free to use, but you'll only be charged for the Azure services you consume, such as virtual machines, storage, networking resources and machine learning. Open data that has been curated and made available on Azure.

Steev, an AI assistant for training, manages your training runs. It eliminates the need for constant supervision while improving model performance. It analyzes and reviews your code before the training begins. It identifies potential errors, provides fixes, and suggests better approaches to improve workflow and outcomes. Steev is proactive, adjusting training parameters and resolving issues before they escalate. It goes beyond simple observation. Steev tracks all variables during training and sends notifications instantly when attention is required, eliminating the need for constant progress checks. Steev has everything you need to train smarter, and it's ready to use. Steev's beta program allows you to try it for free.

DagsHub, a collaborative platform for data scientists and machine-learning engineers, is designed to streamline and manage their projects. It integrates code and data, experiments and models in a unified environment to facilitate efficient project management and collaboration. The user-friendly interface includes features such as dataset management, experiment tracker, model registry, data and model lineage and model registry. DagsHub integrates seamlessly with popular MLOps software, allowing users the ability to leverage their existing workflows. DagsHub improves machine learning development efficiency, transparency, and reproducibility by providing a central hub for all project elements. DagsHub, a platform for AI/ML developers, allows you to manage and collaborate with your data, models and experiments alongside your code. DagsHub is designed to handle unstructured data, such as text, images, audio files, medical imaging and binary files.

Langtail is a cloud-based development tool designed to streamline the debugging, testing, deployment, and monitoring of LLM-powered applications. The platform provides a no-code interface for debugging prompts, adjusting model parameters, and conducting thorough LLM tests to prevent unexpected behavior when prompts or models are updated. Langtail is tailored for LLM testing, including chatbot evaluations and ensuring reliable AI test prompts. Key features of Langtail allow teams to: • Perform in-depth testing of LLM models to identify and resolve issues before production deployment. • Easily deploy prompts as API endpoints for smooth integration into workflows. • Track model performance in real-time to maintain consistent results in production environments. • Implement advanced AI firewall functionality to control and protect AI interactions. Langtail is the go-to solution for teams aiming to maintain the quality, reliability, and security of their AI and LLM-based applications.

Transform your business operations with our cutting-edge AI-powered solutions. Harness the potential of historical data to drive innovation, optimize efficiency, and propel your growth – revolutionizing your business processes, one task at a time. At Ever Efficient AI, we understand the value of your historical data and its untapped potential. By analyzing historical data in new and creative ways, we unlock opportunities for process efficiency, enhanced decision-making, waste reduction & drive growth. Ever Efficient AI's task automation is designed to take the strain out of your daily operations. Our AI systems can manage and automate a wide range of tasks, from scheduling to data management, allowing you and your team to focus on what truly matters - your core business.

FieldDay lets you explore the world of AI, Machine Learning and AI right on your smartphone. We've simplified the process of creating machine learning models by turning it into a hands-on, engaging experience that's as easy as using your camera. FieldDay lets you create custom AI apps, and embed them into your favorite tools using only your phone. You can use FieldDay examples as a learning tool and create a custom model that is ready to embed in your app/project. FieldDay machine-learning models are used in a variety of projects and applications. Our range of export and integration options makes it easy to embed a machine learning model into any platform. FieldDay allows you to collect data from your phone camera. Our interface is designed to allow for intuitive and easy annotation during collection. You can create a custom dataset quickly. FieldDay allows you to preview and correct models in real-time.

Fully managed infrastructure, tools and workflows allow you to build, train and deploy models faster. Scale inference and deploy custom AI & LLMs in seconds on any infrastructure. Schedule batch jobs to handle your most demanding tasks, and only pay per second. Optimize costs by utilizing GPUs, spot instances, and automatic failover. YAML simplifies complex infrastructure setups by allowing you to train with a single command. Automate the scaling up of workers during periods of high traffic, and scaling down to zero when inactive. Deploy cutting edge models with persistent endpoints within a serverless environment to optimize resource usage. Monitor system and inference metrics, including worker counts, GPU utilization, throughput, and latency in real-time. Split traffic between multiple models to evaluate.

Emly Labs, an AI framework, is designed to make AI accessible to users of all technical levels via a user-friendly interface. It offers AI project-management with tools that automate workflows for faster execution. The platform promotes team collaboration, innovation, and data preparation without code. It also integrates external data to create robust AI models. Emly AutoML automates model evaluation and data processing, reducing the need for human input. It prioritizes transparency with AI features that are easily explained and robust auditing to ensure compliance. Data isolation, role-based accessibility, and secure integrations are all security measures. Emly's cost effective infrastructure allows for on-demand resource provisioning, policy management and risk reduction.

Vishwa.ai, an AutoOps Platform for AI and ML Use Cases. It offers expert delivery, fine-tuning and monitoring of Large Language Models. Features: Expert Prompt Delivery : Tailored prompts tailored to various applications. Create LLM Apps without Coding: Create LLM workflows with our drag-and-drop UI. Advanced Fine-Tuning : Customization AI models. LLM Monitoring: Comprehensive monitoring of model performance. Integration and Security Cloud Integration: Supports Google Cloud (AWS, Azure), Azure, and Google Cloud. Secure LLM Integration - Safe connection with LLM providers Automated Observability for efficient LLM Management Managed Self Hosting: Dedicated hosting solutions. Access Control and Audits - Ensure secure and compliant operations.

Ray's creators have created a fully-managed platform. The best way to create, scale, deploy, and maintain AI apps on Ray. You can accelerate development and deployment of any AI app, at any scale. Ray has everything you love, but without the DevOps burden. Let us manage Ray for you. Ray is hosted on our cloud infrastructure. This allows you to focus on what you do best: creating great products. Anyscale automatically scales your infrastructure to meet the dynamic demands from your workloads. It doesn't matter if you need to execute a production workflow according to a schedule (e.g. Retraining and updating a model with new data every week or running a highly scalable, low-latency production service (for example. Anyscale makes it easy for machine learning models to be served in production. Anyscale will automatically create a job cluster and run it until it succeeds.

Granica AI efficiency platform lowers costs for storing and accessing data, while maintaining its privacy so that it can be used to train. Granica is native to AWS/GCP, a petabyte-scale platform, and developer-first. Granica makes AI pipelines faster, more efficient, and more performant. Efficiency is a layer of the AI stack. Byte-granular reduction of data uses novel compression algorithms to reduce costs for storing and transferring objects in Amazon S3 or Google Cloud Storage up to 80%, and API costs up to 90%. Estimate your cloud environment in 30 minutes, using a sample of read-only data from your S3/GCS. No need to allocate budgets or perform a total cost of ownership. Granica deploys to your environment and VPC while respecting your security policies. Granica supports many data types for AI/ML/analytics. It also offers lossy and lossless compression options. Detect and protect sensitive information even before it's persisted in your cloud object store.

With a fully automated cloud infrastructure, experts can explore data and write stable codes at the same time. Zerve’s data science environment gives data scientists and ML teams a unified workspace to explore, collaborate and build data science & AI project like never before. Zerve provides true language interoperability. Users can use Python, R SQL or Markdown in the same canvas and connect these code blocks. Zerve offers unlimited parallelization, allowing for code blocks and containers to run in parallel at any stage of development. Analysis artifacts can be automatically serialized, stored and preserved. This allows you to change a step without having to rerun previous steps. Selecting compute resources and memory in a fine-grained manner for complex data transformation.

Composio is a platform for integration that enhances AI agents and Large Language Models by providing seamless connections with over 150 tools. It supports a variety of agentic frameworks, LLM providers and function calling for efficient task completion. Composio provides a wide range of tools including GitHub and Salesforce, file management and code execution environments. This allows AI agents to perform a variety of actions and subscribe to different triggers. The platform offers managed authentication that allows users to manage authentication processes for users and agents through a central dashboard. Composio's core features include a developer first integration approach, built in authentication management, and an expanding catalog with over 90 ready to connect tools. It also includes a 30% reliability increase through simplified JSON structure and improved error handling.

An API that streams 3D scenes data into ComfyUI diffusion based workflows. Our API is accessible via our web editor. This allows image generation in 3D. Support for custom workflows & LoRAs for enterprises & teams using AI in production pipelines. Playbook believes that AI is a powerful tool that can help you do great work. To get there, tight integration between the model, application, or product is required. You own all assets created using our platform as long as you did not violate anyone's copyrights in the process of creating your model. The rise of spatial computing (AR/VR), and the increasing reliance on visual effect (VFX), is a result of the need for a 3D pipeline that can produce real-time content quicker. Playbookengine.com, a diffusion-based rendering engine, reduces the time it takes to create a final image using AI. It is accessible through a web editor or API, and supports scene segmentation and relighting.

SuperAGI SuperCoder combines AI-native development platform & AI agents in order to enable fully autonomous software creation starting with the python programming language & frameworks. SuperCoder 2.0 leverages Large Action Models (LAMs) and LLMs fine-tuned to python code creation leading to one-shot or few-shot python functional programming with significantly higher accuracy on SWE-bench and Codebench SuperCoder 2.0 is an autonomous system that combines software guardrails for Flask & Django development frameworks with SuperAGI's Generally Intelligent Developer Agents in order to deliver complex real-world software systems SuperCoder 2.0 integrates deeply with existing developer stacks such as Jira or Github, Jenkins, CSPs, and QA solutions like BrowserStack/Selenium Clouds, to ensure a seamless experience in software development.

We offer a set of world-class tools and assets to convert ideas into production ready AI solutions. Build and deploy custom Generative AI end-to-end solutions on our unified Platform, and avoid the hassle of tool fragmentation or platform switching. Launch your next AI-based solution using a single API endpoint. It has never been easier to create, maintain, and improve AI systems. Subscribe to models and datasets on aiXplain’s marketplace. Subscribe to models and data sets to use with aiXplain's no-code/low code tools or the SDK.

Llama Stack is a flexible framework designed to simplify the development of applications utilizing Meta’s Llama language models. It features a modular client-server architecture that allows developers to customize their setup by integrating different providers for inference, memory, agents, telemetry, and evaluations. With pre-configured distributions optimized for various deployment scenarios, Llama Stack enables a smooth transition from local development to production. It supports multiple programming languages, including Python, Node.js, Swift, and Kotlin, making it accessible across different tech stacks. Additionally, the framework provides extensive documentation and sample applications to help developers efficiently build and deploy Llama-powered solutions.

Hyperbrowser allows users to run and scale headless browsers within secure, isolated containers. It is designed for web automation, and AI-driven applications. It allows users to automate tasks such as web scraping, form filling and testing, and to scrape web data and structure it at scale for analysis. Hyperbrowser integrates AI agents to enable browsing, data collection and interaction with web apps. It has features like automatic captcha solvers to streamline automation workflows. Stealth mode to avoid bot detection. Session management with logging, bugging, and secure resource separation. The platform supports 10,000 concurrent browsers, with sub-millisecond latencies. This ensures scalable and reliable browsing. Hyperbrowser supports a variety of tech stacks including Python and Node.js and offers both synchronous and non-synchronous clients to ensure seamless integration.

Our auto-scaling AIs allow you to access powerful generative AIs models without any management. API calls are now available for generative AI models such as stable diffusion, dreambooth and pix2pix. Our scalable Rest APIs allow you to build applications on top of generative AI models. They integrate seamlessly and cost a fraction of what other alternatives do. Integrations that are seamless with your existing systems without extensive development. Our APIs are easy to integrate into your workflow, with support for stacks such as CURL, Python Node.js, and PHP. We harness the computing power of millions decentralised crypto mining machines around the world, optimize them for machine-learning and package them with popular AI models such as Stable Diffusion. We can deliver Generative AI through APIs that are easily integrated and scalable by leveraging these decentralized resources.

Compose, test and optimize prompts for the most popular language models and AI platforms. Promptmetheus, an Integrated Development Environment for LLM prompts is designed to help automate workflows and enhance products and services using the mighty GPT and other cutting edge AI models. The transformer architecture has enabled cutting-edge Language Models to reach parity with the human ability in certain narrow cognitive tasks. To effectively leverage their power, however, we must ask the right questions. Promptmetheus is a complete prompt engineering software toolkit that adds composability and traceability to the prompt design to help you discover those questions.

The easiest way to create serverless AI agents with memory. Start building agentic pipes and tools locally first. Deploy serverless in one command. Base AI allows developers to create high-quality AI agents that have memory (RAG) in TypeScript, and then deploy serverless using Langbase's (creators of Base AI) highly scalable API. Base AI is a web-first solution with TypeScript and a familiar API. You can integrate AI into your web stack with ease, using Next.js or Vue or vanilla Node.js. Base AI is a great tool for delivering AI features faster. Create AI features on-premises with no cloud costs. Git is integrated out of the box so you can branch AI models and merge them like code. Complete observability logs allow you to debug AI-like JavaScript and trace data points, decisions, and outputs. It's Chrome DevTools, but for AI.

We are ready to meet all your business needs, whether it is quick engineering, fine-tuning or training. The Together Inference API makes it easy to integrate your new model in your production application. Together AI's elastic scaling and fastest performance allows it to grow with you. To increase accuracy and reduce risks, you can examine how models are created and what data was used. You are the owner of the model that you fine-tune and not your cloud provider. Change providers for any reason, even if the price changes. Store data locally or on our secure cloud to maintain complete data privacy.

Graphlit simplifies the process of building an AI copilot or chatbot or adding LLMs to your existing application. Graphlit is a serverless platform that automates complex data processes, including data ingestion and extraction, LLM conversations. It also integrates webhooks, alerting, semantic search, and alerting. Graphlit's workflow as code approach allows you to programmatically define every step in the workflow. Data ingestion, metadata indexing, data preparation and data enrichment. Integration with your applications is achieved through event-based webhooks, API integrations, and integrations with event-based Webhooks.

Amazon Bedrock is a managed AWS service designed to make building and scaling generative AI applications easier by providing access to a diverse range of foundation models (FMs) from leading providers such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can test, fine-tune, and customize these models to meet specific use cases using advanced techniques like Retrieval Augmented Generation (RAG). The platform allows for the creation of intelligent agents that seamlessly integrate with enterprise systems and data sources, enabling enhanced automation and decision-making. Bedrock’s serverless architecture removes the need for infrastructure management, ensuring high scalability and minimal operational complexity. With a focus on security, data privacy, and responsible AI, Amazon Bedrock empowers organizations to accelerate innovation while maintaining trust and compliance. It represents a powerful tool for businesses aiming to integrate cutting-edge AI solutions into their operations effortlessly.

Tencent Cloud TI Platform, a machine learning platform for AI engineers, is a one stop shop. It supports AI development at every stage, from data preprocessing, to model building, to model training, to model evaluation, as well as model service. It is preconfigured with diverse algorithms components and supports multiple algorithm frameworks for adapting to different AI use-cases. Tencent Cloud TI Platform offers a machine learning experience in a single-stop shop. It covers a closed-loop workflow, from data preprocessing, to model building, training and evaluation. Tencent Cloud TI Platform allows even AI beginners to have their models automatically constructed, making the entire training process much easier. Tencent Cloud TI Platform’s auto-tuning feature can also improve the efficiency of parameter optimization. Tencent Cloud TI Platform enables CPU/GPU resources that can elastically respond with flexible billing methods to different computing power requirements.

Construct your model as a live interactive graph. View data flowing through the architecture of your visualized model. View and edit the model architecture at the atomic level. Graphbook offers X-ray transparency without black boxes. Graphbook checks data type and form in real-time, with clear error messages. This makes model debugging easy. Graphbook abstracts out software dependencies and configuration of the environment, allowing you to focus on your model architecture and data flows with the computing resources required. Cerbrec Graphbook transforms cumbersome AI modeling into a user friendly experience. Graphbook, which is backed by a growing community that includes machine learning engineers and data science experts, helps developers fine-tune their language models like BERT and GPT using text and tabular data. Everything is managed out of box, so you can preview how your model will behave.