Best On-Premise AI Development Platforms of 2024

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

Nyckel makes it easy to auto-label images and text using AI. We say ‘easy’ because trying to do classification through complicated AI tools is hard. And confusing. Especially if you don't know machine learning. That’s why Nyckel built a platform that makes image and text classification easy. In just a few minutes, you can train an AI model to identify attributes of any image or text. Our goal is to help anyone spin up an image or text classification model in just minutes, regardless of technical knowledge.

AI agents that interact and answer questions with users and complete tasks using your data and APIs. AI that can answer questions, summarize and extract insights from any long document. Transfer styles and formats, as well as tags and summaries between documents and data sources. Stack AI is used by developer teams to automate customer service, process documents, qualify leads, and search libraries of data. With a single button, you can try multiple LLM architectures and prompts. Collect data, run fine-tuning tasks and build the optimal LLM to fit your product. We host your workflows in APIs, so that your users have access to AI instantly. Compare the fine-tuning services of different LLM providers.

Infrastructure to build, run, and manage autonomous agents Open-source AI framework that allows you to quickly and reliably develop and deploy useful agents.

DeepSpeed is a deep learning optimization library that is open source for PyTorch. It is designed to reduce memory and computing power, and to train large distributed model with better parallelism using existing computer hardware. DeepSpeed is optimized to provide high throughput and low latency training. DeepSpeed can train DL-models with more than 100 billion parameters using the current generation GPU clusters. It can also train as many as 13 billion parameters on a single GPU. DeepSpeed, developed by Microsoft, aims to provide distributed training for large models. It's built using PyTorch which is a data parallelism specialist.

PostgresML is an entire platform that comes as a PostgreSQL Extension. Build simpler, faster and more scalable model right inside your database. Explore the SDK, and test open-source models in our hosted databases. Automate the entire workflow, from embedding creation to indexing and Querying for the easiest (and fastest) knowledge based chatbot implementation. Use multiple types of machine learning and natural language processing models, such as vector search or personalization with embeddings, to improve search results. Time series forecasting can help you gain key business insights. SQL and dozens regression algorithms allow you to build statistical and predictive models. ML at database layer can detect fraud and return results faster. PostgresML abstracts data management overheads from the ML/AI cycle by allowing users to run ML/LLM on a Postgres Database.

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.

Even the most complex requests from users can be fulfilled by our advanced planning engine. Out-of-the-box automation, inside your product. Your users can ask the system to do amazing things by using simple text, such as "Please show me sales from last month and give me some suggestions". OpenCopilot can be integrated into your product by using our chat bubble. No coding knowledge is required. You can also use our SDKs for your copilot to blend in. You can also feed all kinds of data to your copilot and it will be capable of understanding it and offering help to your users. OpenCopilot can be hosted on your own website with a simple make install command. All paid plans come with personal support from our team. Your users can ask complicated questions that require multiple actions to be executed in one go. The single platform for building, managing, and deploying your next AI-powered features. You will be the first to get new features, which is great since we ship so much.

AIxBlock is an end-to-end blockchain-based platform for AI that harnesses unused computing resources of BTC miners, as well as all global consumer GPUs. Our platform's training method is a hybrid machine learning approach that allows simultaneous training on multiple nodes. We use the DeepSpeed-TED method, a three-dimensional hybrid parallel algorithm which integrates data, tensor and expert parallelism. This allows for the training of Mixture of Experts models (MoE) on base models that are 4 to 8x larger than the current state of the art. The platform will identify and add compatible computing resources from the computing marketplace to the existing cluster of training nodes, and distribute the ML model for unlimited computations. This process unfolds dynamically and automatically, culminating in decentralized supercomputers which facilitate AI success.

Langtail is a platform that allows for the rapid development and deployment of Language Model (LLM) applications. It allows companies to quickly experiment, collaborate and launch production-grade LLM applications. The following are the key features: 1. No-code LLM Playground for quick debugging and ideas 2. Collaborative workspaces to share prompts and insights 3. Comprehensive observability suite including logging and analytics 4. Evaluation framework for systematically evaluating prompt performance 5. Deployment infrastructure to serve prompts via API across multiple environments 6. Future fine-tuning features to improve models based on user feedback Langtail enables both technical and nontechnical teams alike to quickly find LLM use cases that are high-value, refine prompts to ensure reliable performance, and deploy apps with ease. It's an all-in-one solution that will take your LLM project from prototype to production quicker than ever.

At competitive prices, you can access dedicated machines that are pre-configured with professional AI development tools. Apolo offers everything from HPC resources to a complete AI platform with a built-in ML toolkit. Apolo is available in a distributed architecture or as a dedicated enterprise cloud. It can also be deployed as a white-label multi-tenant solution that supports dedicated instances or self service cloud. Apolo creates a fully-fledged AI development environment, with all the tools needed at your fingertips. Apolo automates and manages the infrastructure for successful AI development. Apolo's AI services seamlessly integrate your on-prem resources and cloud resources. They also deploy pipelines and integrate your commercial and open-source development tools. Apolo provides enterprises with the resources and tools necessary to achieve breakthroughs when it comes to AI.

NVIDIA Base Command™, Platform is a software platform for enterprise-class AI training. It enables businesses and data scientists to accelerate AI developments. Base Command Platform is part of NVIDIA DGX™. It provides centralized, hybrid management of AI training projects. It can be used with NVIDIA DGX Cloud or NVIDIA DGX SUPERPOD. The Base Command Platform is combined with NVIDIA-accelerated AI infrastructure to provide a cloud-hosted solution that allows users to avoid the overheads and pitfalls of setting up and maintaining a do it yourself platform. Base Command Platform efficiently configures, manages, and executes AI workloads. It also provides integrated data management and executions on the right-sized resources, whether they are on-premises or cloud. The platform is continuously updated by NVIDIA's engineers and researchers.

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.