Alternatives to Go.AI
Compare Go.AI alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Go.AI in 2026. Compare features, ratings, user reviews, pricing, and more from Go.AI competitors and alternatives in order to make an informed decision for your business.
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Mistral AI
Mistral AI
Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.Starting Price: Free -
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Hedra
Hedra
Hedra is an AI inference and model deployment platform for teams building applications with multimodal and physical AI. Its managed API provides access to image, video, audio, and language models through a unified endpoint and pay-per-use billing, alongside a browser playground, model catalog, API keys, job tracking, webhooks, and team controls. Developers can connect supported assistants through Hedra’s Model Context Protocol server or use its command-line interface to inspect models and submit inference jobs. Hedra also provides model training and inference optimization for custom workloads, with managed cloud, hybrid, and customer-controlled on-premises deployment options. A no-code Studio workspace lets creators generate and edit visual content.Starting Price: $20/month -
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VMware Private AI Foundation
VMware
VMware Private AI Foundation is a joint, on‑premises generative AI platform built on VMware Cloud Foundation (VCF) that enables enterprises to run retrieval‑augmented generation workflows, fine‑tune and customize large language models, and perform inference in their own data centers, addressing privacy, choice, cost, performance, and compliance requirements. It integrates the Private AI Package (including vector databases, deep learning VMs, data indexing and retrieval services, and AI agent‑builder tools) with NVIDIA AI Enterprise (comprising NVIDIA microservices like NIM, NVIDIA’s own LLMs, and third‑party/open source models from places like Hugging Face). It supports full GPU virtualization, monitoring, live migration, and efficient resource pooling on NVIDIA‑certified HGX servers with NVLink/NVSwitch acceleration. Deployable via GUI, CLI, and API, it offers unified management through self‑service provisioning, model store governance, and more. -
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LocalDMS
Goda Software
LocalDMS is a privacy-first, on-premises Document Management System (EDMS) engineered for organizations requiring total data control and zero-telemetry security. Built with a zero-configuration enterprise-scalable database, LocalDMS centralizes file storage, metadata, and review workflows across web and desktop interfaces without cloud dependency. Key Features: 100% On-Premises: Air-gapped deployment behind your local firewall with zero data tracking. Version Control: Revision history with check-in/check-out locks to eliminate file conflicts. Audit Trails & Compliance: Database-bound activity logs, electronic sign-offs, and permission controls. Active Directory Integration: Granular user permissions and HTTPS support. Indexed Search: Rapid retrieval with custom metadata tags and full-text search. Ideal Alternative To: SharePoint, DocuWare, and M-Files for engineering, legal, healthcare, and IT teams. Pricing: 100% free for up to 10 users with full feature accessStarting Price: $0 -
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SambaNova
SambaNova Systems
SambaNova is the leading purpose-built AI system for generative and agentic AI implementations, from chips to models, that gives enterprises full control over their model and private data. We take the best models, optimize them for fast tokens and higher batch sizes, the largest inputs and enable customizations to deliver value with simplicity. The full suite includes the SambaNova DataScale system, the SambaStudio software, and the innovative SambaNova Composition of Experts (CoE) model architecture. These components combine into a powerful platform that delivers unparalleled performance, ease of use, accuracy, data privacy, and the ability to power every use case across the world's largest organizations. We give our customers the optionality to experience through the cloud or on-premise. -
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Motific.ai
Outshift by Cisco
Accelerate your GenAI adoption journey. Configure GenAI assistants powered by your organization’s data with just a few clicks. Roll out GenAI assistants with guardrails for security, trust, compliance, and cost management. Discover how your teams are leveraging AI assistants with data-driven insights. Uncover opportunities to maximize value. Power your GenAI apps with top Large Language Models (LLMs). Seamlessly connect with top GenAI model providers such as Google, Amazon, Mistral, and Azure. Employ safe GenAI on your marcom site that answers press, analysts, and customer questions. Quickly create and deploy GenAI assistants on web portals that offer swift, precise, and policy-controlled responses to questions, using the information in your public content. Leverage safe GenAI to offer swift, correct answers to legal policy questions from your employees. -
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Xinity
Xinity
Xinity is open-source, OpenAI-compatible LLM inference software that lets European enterprises run generative AI entirely on their own servers. The platform installs on existing hardware and exposes an OpenAI-compatible API, so existing applications migrate by changing one base URL. No cloud dependency, no data egress, no exposure to the US CLOUD Act. The core engine is open source under Apache 2.0 and supports open-weight models, including European sovereign models, with automatic model routing, audit trails on every inference request, role-based access control, and multi-node orchestration. Xinity is built in Vienna, Austria for regulated industries such as finance, healthcare, legal, public sector, and media, including fully air-gapped environments, and is designed for GDPR and EU AI Act requirements. -
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Domino Enterprise AI Platform
Domino Data Lab
Domino is an enterprise AI platform designed to help organizations build, deploy, and scale AI systems that deliver real business outcomes. It provides end-to-end support for the AI lifecycle, from data science experimentation to production deployment and governance. The platform enables teams to access data, tools, and compute resources through a self-service environment with built-in IT controls. Domino supports the development of machine learning models, generative AI applications, and AI agents using preferred tools and frameworks. It also includes governance features such as model tracking, audit trails, and policy enforcement to ensure compliance and transparency. With hybrid and multi-cloud capabilities, organizations can run AI workloads across on-premises and cloud environments. Overall, Domino helps enterprises operationalize AI at scale while maintaining control, security, and efficiency. -
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Purpose-built to run AI anywhere on data everywhere. Our solution unlocks the value of your unstructured data, allowing you to access, prepare, train, fine-tune, and drive AI without any limitations. We’ve joined our industry-leading file and object storage portfolio, including PowerScale, ECS, and ObjectScale, with our PowerEdge server and open, modern data lakehouse approach. This gives you the power to bring AI to your unstructured data, on-premises, at the edge, and in any cloud with the highest performance and infinite scale. Access a full team of trained data scientists and industry experts who will help you implement AI use cases that deliver the most value for your business. Protect, detect, and respond to cyber attackers with hardened software and hardware security and real-time threat detection. Train and fine-tune your AI models using a single point of data access and the highest performance, on-premises, at the edge, and in any cloud.
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Quali
Quali
Quali’s CloudShell platform is a cloud automation and infrastructure orchestration product that lets organizations deliver fully functional sandboxes and complex IT environments across on-premises, hybrid, and public cloud infrastructure by eliminating manual provisioning and resource conflicts and boosting productivity with self-service access and reusable components. CloudShell enables users to model infrastructure and application environments using a drag-and-drop blueprint editor to define resources from inventory, set up network connectivity, and automate deployment and teardown workflows, greatly reducing configuration time and standardizing environment delivery. It offers a web-based self-service portal and catalog with inventory management, reservation and scheduling, conflict resolution, role-based access control with directory and SSO integration, and distributed execution engines for high-performance parallel sandbox deployment.Starting Price: Free -
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troveGEN
Intellara Technologies
troveGEN is a retrieval-augmented generation (RAG) and document-search platform for teams building AI products and organizations that need governed access to internal information. It ingests files, scanned documents, web pages and connected sources, then parses, OCRs, chunks, indexes and retrieves relevant passages with hybrid search, reranking, filters and access controls. Applications and AI agents can use its REST API, TypeScript SDK or Model Context Protocol server to search content and receive source-linked results; optional answer generation supports cited responses. Customers can use managed hosting or connect their own vector database, models and content sources, including air-gapped deployments. Use cases include internal knowledge search, customer support, technical documentation, and document workflows across finance, healthcare, legal and government.Starting Price: $25/month -
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NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
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Centific
Centific
Centific’s frontier AI data foundry platform, powered by NVIDIA edge computing, is purpose-built to accelerate AI deployments by increasing flexibility, security, and scalability through comprehensive workflow orchestration. It centralizes AI project management in a unified AI Workbench, overseeing pipelines, model training, deployment, and reporting within a single, streamlined environment, while it handles data ingestion, preprocessing, and transformation. RAG Studio simplifies retrieval-augmented generation workflows, the Product Catalog organizes reusable assets, and Safe AI Studio embeds built-in safeguards to ensure compliance, reduce hallucinations, and protect sensitive data. Its plugin-based modular architecture supports both PaaS and SaaS models with metering to monitor consumption, and a centralized model catalog offers version control, compliance checks, and flexible deployment options. -
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SwarmOne
SwarmOne
SwarmOne is an autonomous infrastructure platform designed to streamline the entire AI lifecycle, from training to deployment, by automating and optimizing AI workloads across any environment. With just two lines of code and a one-click hardware installation, users can initiate instant AI training, evaluation, and deployment. It supports both code and no-code workflows, enabling seamless integration with any framework, IDE, or operating system, and is compatible with any GPU brand, quantity, or generation. SwarmOne's self-setting architecture autonomously manages resource allocation, workload orchestration, and infrastructure swarming, eliminating the need for Docker, MLOps, or DevOps. Its cognitive infrastructure layer and burst-to-cloud engine ensure optimal performance, whether on-premises or in the cloud. By automating tasks that typically hinder AI model development, SwarmOne allows data scientists to focus exclusively on scientific work, maximizing GPU utilization. -
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VDF AI
VDF AI
VDF AI is an enterprise AI agent platform that enables organizations to build, deploy, govern, and operate secure AI agents across on-premises, private-cloud, and cloud environments. The platform combines multi-agent orchestration, private retrieval-augmented generation (RAG), model registration and routing, governed tool execution, policy controls, auditability, and enterprise integrations. Organizations can connect approved local or cloud LLMs, create reusable agents and workflows, isolate data by company, department, or user, and retain control over sensitive information. VDF AI is designed for production use in regulated and data-sensitive environments, supporting human approval steps, role-based access, observability, and controlled deployment through containerized infrastructure. It helps enterprises move from isolated AI pilots to scalable, governed AI operations while reducing vendor lock-in and maintaining data sovereignty. -
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Huawei Cloud ModelArts
Huawei Cloud
ModelArts is a comprehensive AI development platform provided by Huawei Cloud, designed to streamline the entire AI workflow for developers and data scientists. It offers a full-lifecycle toolchain that includes data preprocessing, semi-automated data labeling, distributed training, automated model building, and flexible deployment options across cloud, edge, and on-premises environments. It supports popular open source AI frameworks such as TensorFlow, PyTorch, and MindSpore, and allows for the integration of custom algorithms tailored to specific needs. ModelArts features an end-to-end development pipeline that enhances collaboration across DataOps, MLOps, and DevOps, boosting development efficiency by up to 50%. It provides cost-effective AI computing resources with diverse specifications, enabling large-scale distributed training and inference acceleration. -
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Saturn Cloud
Saturn Cloud
Saturn Cloud is the AI token factory platform for neoclouds, AI Factory operators, and enterprises. It turns GPU infrastructure into managed services for fine-tuning, model serving, and per-token billing, with standard inference endpoints, distributed training, and managed environments. Enterprise security and governance are built in, across public, private, and on-premises environments. Learn more at saturncloud.io. -
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NVIDIA AI Enterprise
NVIDIA
The software layer of the NVIDIA AI platform, NVIDIA AI Enterprise accelerates the data science pipeline and streamlines development and deployment of production AI including generative AI, computer vision, speech AI and more. With over 50 frameworks, pretrained models and development tools, NVIDIA AI Enterprise is designed to accelerate enterprises to the leading edge of AI, while also simplifying AI to make it accessible to every enterprise. The adoption of artificial intelligence and machine learning has gone mainstream, and is core to nearly every company’s competitive strategy. One of the toughest challenges for enterprises is the struggle with siloed infrastructure across the cloud and on-premises data centers. AI requires their environments to be managed as a common platform, instead of islands of compute. -
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Zerve AI
Zerve AI
Zerve is the agentic data workspace designed for anyone who works with data, from solo analysts, data scientists, business users and teams alike. Zerve brings together exploration, advanced analysis, collaboration, and production deployment into a single AI-native environment, so that important data work doesn’t stall, break, or disappear. Zerve’s AI agents understand the full context of a project and actively help plan, build, debug, and iterate across multi-step analyses. Agents assist with tasks like cleaning and transforming data, identifying issues, and testing approaches, reducing the manual effort that slows teams down. This means working at a higher level of abstraction without being slowed by setup or syntax. Zerve can be used as SaaS, self-hosted, or even on-premise for highly regulated environments. Zerve is used by data professionals in companies such as BBC, QVC, Dun & Bradstreet, Airbus, and many others.Starting Price: $0 -
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Pipeshift
Pipeshift
Pipeshift is a modular orchestration platform designed to facilitate the building, deployment, and scaling of open source AI components, including embeddings, vector databases, large language models, vision models, and audio models, across any cloud environment or on-premises infrastructure. The platform offers end-to-end orchestration, ensuring seamless integration and management of AI workloads, and is 100% cloud-agnostic, providing flexibility in deployment. With enterprise-grade security, Pipeshift addresses the needs of DevOps and MLOps teams aiming to establish production pipelines in-house, moving beyond experimental API providers that may lack privacy considerations. Key features include an enterprise MLOps console for managing various AI workloads such as fine-tuning, distillation, and deployment; multi-cloud orchestration with built-in auto-scalers, load balancers, and schedulers for AI models; and Kubernetes cluster management. -
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IBM watsonx.ai
IBM
Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers: End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides. Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice. -
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NVIDIA Base Command
NVIDIA
NVIDIA Base Command™ is a software service for enterprise-class AI training that enables businesses and their data scientists to accelerate AI development. Part of the NVIDIA DGX™ platform, Base Command Platform provides centralized, hybrid control of AI training projects. It works with NVIDIA DGX Cloud and NVIDIA DGX SuperPOD. Base Command Platform, in combination with NVIDIA-accelerated AI infrastructure, provides a cloud-hosted solution for AI development, so users can avoid the overhead and pitfalls of deploying and running a do-it-yourself platform. Base Command Platform efficiently configures and manages AI workloads, delivers integrated dataset management, and executes them on right-sized resources ranging from a single GPU to large-scale, multi-node clusters in the cloud or on-premises. Because NVIDIA’s own engineers and researchers rely on it every day, the platform receives continuous software enhancements. -
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Mistral AI Studio
Mistral AI
Mistral AI Studio is a unified builder-platform that enables organizations and development teams to design, customize, deploy, and manage advanced AI agents, models, and workflows from proof-of-concept through to production. The platform offers reusable blocks, including agents, tools, connectors, guardrails, datasets, workflows, and evaluations, combined with observability and telemetry capabilities so you can track agent performance, trace root causes, and govern production AI operations with visibility. With modules like Agent Runtime to make multi-step AI behaviors repeatable and shareable, AI Registry to catalogue and manage model assets, and Data & Tool Connections for seamless integration with enterprise systems, Studio supports everything from fine-tuning open source models to embedding them in your infrastructure and rolling out enterprise-grade AI solutions.Starting Price: $14.99 per month -
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Anyscale
Anyscale
Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode and Jupyter, automated dependency management, and expert-built app templates. Deployment options are flexible, supporting public clouds, on-premises clusters, and Kubernetes environments. Anyscale Jobs and Services enable reliable production-grade batch processing and scalable web services with features like job queuing, retries, observability, and zero-downtime upgrades. Security and compliance are ensured with private data environments, auditing, access controls, and SOC 2 Type II attestation.Starting Price: $0.00006 per minute -
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Cake AI
Cake AI
Cake AI is a comprehensive AI infrastructure platform that enables teams to build and deploy AI applications using hundreds of pre-integrated open source components, offering complete visibility and control. It provides a curated, end-to-end selection of fully managed, best-in-class commercial and open source AI tools, with pre-built integrations across the full breadth of components needed to move an AI application into production. Cake supports dynamic autoscaling, comprehensive security measures including role-based access control and encryption, advanced monitoring, and infrastructure flexibility across various environments, including Kubernetes clusters and cloud services such as AWS. Its data layer equips teams with tools for data ingestion, transformation, and analytics, leveraging tools like Airflow, DBT, Prefect, Metabase, and Superset. For AI operations, Cake integrates with model catalogs like Hugging Face and supports modular workflows using LangChain, LlamaIndex, and more. -
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NVIDIA Run:ai
NVIDIA
NVIDIA Run:ai is an enterprise platform designed to optimize AI workloads and orchestrate GPU resources efficiently. It dynamically allocates and manages GPU compute across hybrid, multi-cloud, and on-premises environments, maximizing utilization and scaling AI training and inference. The platform offers centralized AI infrastructure management, enabling seamless resource pooling and workload distribution. Built with an API-first approach, Run:ai integrates with major AI frameworks and machine learning tools to support flexible deployment anywhere. It also features a powerful policy engine for strategic resource governance, reducing manual intervention. With proven results like 10x GPU availability and 5x utilization, NVIDIA Run:ai accelerates AI development cycles and boosts ROI. -
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Locai
Locai
Locai is the infrastructure and tooling to run AI off-cloud at scale. Everything runs on your own hardware, on-prem or in private cloud, with your data never leaving your estate. The platform covers the full stack. Locai Link is the inference runtime: deploy LLMs, audio transcription, video processing and image detection on any hardware, from workstations to servers to edge devices. Locai Control is the orchestration plane: manage models, updates and policy across whole fleets of machines from one place, with output from one model flowing into the next for true multimodal data fusion. Locai Workspace gives teams a private AI workspace on top: chat, documents and assistants powered entirely by models running inside your organisation. Locai is hardware agnostic and model flexible, running any GGUF, ONNX or TFLite model. Built in the UK for regulated organisations in financial services, nuclear, defence and critical infrastructure, and free to start. -
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Voxtral Small Transcribe 3
Mistral AI
Voxtral Small Transcribe 3 is a multilingual speech-to-text model for transcribing recorded audio. Mistral provides it through an audio transcription API and documents timestamps, speaker diarization, and context biasing, which allows developers to supply key phrases to help recognize domain-specific terms and names. The model automatically detects supported languages or accepts a language code, and supports more than 50 languages. It is designed for application developers building recorded-audio workflows, including meeting, interview, and call transcription, customer-service systems, and voice-agent pipelines. Mistral also describes self-deployment options for the Voxtral 3 family, including private-cloud and on-premises hosting.Starting Price: $0.004/min -
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AWS Storage Gateway
Amazon
AWS Storage Gateway is a hybrid cloud storage service that gives you on-premises access to virtually unlimited cloud storage. Customers use Storage Gateway to simplify storage management and reduce costs for key hybrid cloud storage use cases. These include moving tape backups to the cloud, reducing on-premises storage with cloud-backed file shares, providing low latency access to data in AWS for on-premises applications, as well as various migration, archiving, processing, and disaster recovery use cases. To support these use cases, the service provides three different types of gateways – Tape Gateway, File Gateway, and Volume Gateway – that seamlessly connect on-premises applications to cloud storage, caching data locally for low-latency access. Your applications connect to the service through a virtual machine or hardware gateway appliance using standard storage protocols, such as NFS, SMB, and iSCSI. -
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Onyx
Onyx
Onyx is an open source AI platform that integrates seamlessly with your company's documents, applications, and personnel, enhancing productivity across various teams. It enables users to find answers across all team applications, and AI assistants powered by your organization's unique knowledge, accessible directly within your workflow. Developers can build custom workflows using open-source APIs, facilitating the creation of AI applications tailored to specific needs. Onyx connects to over 40 applications, including Asana, Google Drive, Slack, and Zendesk, ensuring real-time synchronization with document-level access. The platform supports deployment in various environments, such as fully air-gapped setups within your Virtual Private Cloud (VPC) or on-premise, ensuring data security by preventing information from leaving your deployment. Document-level permissions are automatically inherited from connected sources.Starting Price: $16 per month -
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AI Intelligence Hub
VIDIZMO
AI Intelligence Hub is an agentic AI platform for teams that need to search and act on content, records, and connected systems. It combines a multimodal chatbot that provides answers with citations, autonomous agents, and a visual graph workflow designer. Users can trigger workflows by schedule, webhook, API call, platform event, or chat, with human review and approval steps. The platform supports document and media analysis, including OCR, classification, transcription, translation, and evidence review, and connects content libraries, databases, CMS, and ERP systems through connectors, HTTP/API nodes, and MCP. Use cases include public-safety case-file review, government records responses, financial-document checks, healthcare and education knowledge bots, and media archive search. Deployments run in a customer cloud environment, on-premises, or air-gapped, with provider-hosted or self-hosted language models.Starting Price: $127/month -
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OneSource Cloud
OneSource Cloud
OneSource Cloud designs, builds, and manages sovereign AI infrastructure for organizations in regulated industries that cannot run sensitive workloads on public cloud: healthcare and life sciences, financial services, government and defense, energy, legal, and research. We deliver dedicated GPU compute as a managed service. Scope covers cluster design, hardware procurement, data center colocation, deployment, and ongoing operations. Clusters use NVIDIA GPUs with InfiniBand interconnect for multi-node training and inference, backed by high-performance storage and private networking. Each customer gets an isolated, single-tenant environment, so data and models never share hardware with another tenant. Managed services include capacity planning, provisioning, workload scheduling, monitoring, patching, and support. Environments are configured to the customer's compliance requirements, including NIST 800-171 and data residency controls. We operate 20,000+ GPUs across 96+ DCs -
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Amazon SageMaker provides all the tools and libraries you need to build ML models, the process of iteratively trying different algorithms and evaluating their accuracy to find the best one for your use case. In Amazon SageMaker you can pick different algorithms, including over 15 that are built-in and optimized for SageMaker, and use over 150 pre-built models from popular model zoos available with a few clicks. SageMaker also offers a variety of model-building tools including Amazon SageMaker Studio Notebooks and RStudio where you can run ML models on a small scale to see results and view reports on their performance so you can come up with high-quality working prototypes. Amazon SageMaker Studio Notebooks help you build ML models faster and collaborate with your team. Amazon SageMaker Studio notebooks provide one-click Jupyter notebooks that you can start working within seconds. Amazon SageMaker also enables one-click sharing of notebooks.
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IONOS Cloud AI Model Hub
IONOS
IONOS AI Model Hub is a fully managed cloud platform designed to simplify the integration and deployment of advanced artificial intelligence models within applications and digital services. It provides access to powerful open-source foundation models that can generate text, create images, and support conversational question-and-answer systems through a unified API. It enables developers to build AI-driven applications without needing to manage the underlying infrastructure or specialized hardware required to run large machine learning models. It incorporates technologies such as vector databases and Retrieval-Augmented Generation (RAG), which allow applications to retrieve relevant information from data sources and combine it with generative AI responses to produce more accurate and contextual outputs.Starting Price: $0.17 per 1M tokens -
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Build your deep learning project quickly on Google Cloud: Quickly prototype with a portable and consistent environment for developing, testing, and deploying your AI applications with Deep Learning Containers. These Docker images use popular frameworks and are performance optimized, compatibility tested, and ready to deploy. Deep Learning Containers provide a consistent environment across Google Cloud services, making it easy to scale in the cloud or shift from on-premises. You have the flexibility to deploy on Google Kubernetes Engine (GKE), AI Platform, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm.
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octobrain
Muvon
octobrain is an open-source persistent memory server for AI assistants, delivered as a Rust command-line application and Model Context Protocol (MCP) server. It stores notes, decisions, project context, and indexed documents so compatible assistants can retrieve information across conversations. Features include semantic and hybrid BM25/vector search, linked memories, project-scoped stores, goal consolidation, and a knowledge base that indexes URLs, PDFs, and common document formats. Teams can distribute shared knowledge through Git-backed knowledge boxes. octobrain runs with local embedding models or optional cloud embedding providers, and exposes tools for saving, searching, and deleting memories. It is designed for developers and teams extending MCP-compatible AI assistants with persistent, searchable context; installation and operation are managed on the user's own machine or environment. -
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Seesa
Pentatonic
Seesa is an on-premises AI assistant and agent platform installed and managed by Pentatonic on suitable customer hardware. It connects to supported email, calendars, documents, spreadsheets and messaging systems, organizing information into a shared company memory with per-person access controls. Users ask natural-language questions and receive answers grounded in company records with source references. Seesa also prepares meeting briefs, summaries, follow-ups and recurring-work routines for review. Teams configure what actions it may take and where it must seek approval. Standard deployments include installation, agreed history import, supported connections and permission setup; Pentatonic manages supplied installations. It is designed for organizations using internal records in research, coordination and routine workflows while keeping models, memory and agent execution on premises.Starting Price: £117.75/user/month -
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Keito Discover
Keito
Intelligent on-premise or private-cloud search for enterprise data including contracts, documents, presentations, images and emails without compromising privacy. Modern search interfaces and personalised relevance enables employees to effectively source out on premise data and improves efficiency and better decision making. Take advantage of helpful features like document content previews and intelligent keyword detection. Looking to add centralized content discovery to a high-traffic area of your virtual workplace? Flexible search APIs source information on your intranet and other employee experience platforms, giving a feel of a personal virtual assistant for everyone. Contract searching, sales document searching, enhanced customer support search system, direct customer search from documents, etc. Easy access of data scattered across different locations for improving response times. Discover is a comprehensive stack of solutions for text mining and enterprise search. -
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Origon
Origon
Origon is a full-stack AI agent development and operations platform engineered as a unified “Agentic Operating System” that supports the entire lifecycle of autonomous AI systems from design to deployment and observability. It offers an intuitive Studio for visual, drag-and-drop agent creation and configuration, Sessions for real-time observation, behavior tracing, and debugging, and Insights dashboards for performance analytics, reliability tracking, and outcome measurement in one place. Origon runs natively on dedicated infrastructure optimized for low-latency performance and security, avoiding dependency on external cloud APIs, and includes a built-in knowledge engine that connects agents to contextual memory and domain data so responses stay grounded and consistent. It supports hundreds of connectors and APIs, including chat, voice, WhatsApp, SMS, email, and telephony, and lets agents execute code and interact with real systems with a single click.Starting Price: $200 per month -
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Humiris AI
Humiris AI
Humiris AI is a next-generation AI infrastructure platform that enables developers to build advanced applications by integrating multiple Large Language Models (LLMs). It offers a multi-LLM routing and reasoning layer, allowing users to optimize generative AI workflows with a flexible, scalable infrastructure. Humiris AI supports various use cases, including chatbot development, fine-tuning multiple LLMs simultaneously, retrieval-augmented generation, building super reasoning agents, advanced data analysis, and code generation. The platform's unique data format adapts to all foundation models, facilitating seamless integration and optimization. To get started, users can register for an account, create a project, add LLM provider API keys, and define parameters to generate a mixed model tailored to their specific needs. It allows deployment on users' own infrastructure, ensuring full data sovereignty and compliance with internal and external regulations. -
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Klique
Klique
Klique is an enterprise AI control plane that helps organizations manage AI models, applications, agents, and computing resources through a unified platform. The software combines intelligent model routing, AI service governance, and GPU orchestration to optimize performance, infrastructure utilization, and operational costs. Its smart routing engine directs AI requests to appropriate models based on cost, latency, data sensitivity, and organizational policies. Centralized governance capabilities include token budgets, usage quotas, role-based permissions, single sign-on, and audit logging across AI services. Klique also supports GPU resource pooling, fractional GPU sharing, workload scheduling, and automated allocation of computing resources across cloud and on-premises infrastructure. The platform integrates with Kubernetes, cloud providers, AI model APIs, and developer tools while supporting self-hosted, hybrid, and air-gapped deployments. -
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Archestra
Archestra
Archestra is an open source, self-hosted AI platform for deploying and governing agents across an organization. It provides agentic chat for non-developers, apps and skills, shared projects, a server-side agent runtime, MCP orchestration, permission-aware RAG, LLM and MCP proxies, security guardrails, and observability in one platform. Users sign in with SSO, and every tool call runs under that person’s own identity rather than a shared service account. Projects keep chats, files, scheduled tasks, and instructions together, while agents run in sandboxed containers and can start from schedules, emails, or webhooks. MCP servers run in the organization’s own Kubernetes environment and move through security-reviewed promotion flows with separate credentials and network policies. Knowledge bases can connect Confluence, Jira, drives, and internal documents while preserving source-system ACLs, so users only retrieve content they are already allowed to access.Starting Price: Free -
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elsai Procure-to-Pay Intelligence is an AI-enabled workflow product for enterprise procurement, finance, and accounts-payable teams. It coordinates purchasing and invoice-to-payment work, including requisition intake, purchase-order creation, invoice capture, matching, exception detection, approvals, payment workflows, reconciliation, and analytics. The product is designed to operate alongside an organization’s existing ERP, procurement, accounts-payable, and treasury systems. Configurable policies support budget and compliance checks, approval thresholds, matching tolerances, and escalation of exceptions for human review. Audit trails record workflow activity and decisions. The vendor describes private-cloud, on-premises, and in-country deployment options for organizations that need control over data location. Use cases include automating document-intensive purchasing and invoice processing while retaining human oversight of decisions and exceptions.
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Amazon SageMaker Studio Lab
Amazon
Amazon SageMaker Studio Lab is a free machine learning (ML) development environment that provides the compute, storage (up to 15GB), and security, all at no cost, for anyone to learn and experiment with ML. All you need to get started is a valid email address, you don’t need to configure infrastructure or manage identity and access or even sign up for an AWS account. SageMaker Studio Lab accelerates model building through GitHub integration, and it comes preconfigured with the most popular ML tools, frameworks, and libraries to get you started immediately. SageMaker Studio Lab automatically saves your work so you don’t need to restart in between sessions. It’s as easy as closing your laptop and coming back later. Free machine learning development environment that provides the computing, storage, and security to learn and experiment with ML. GitHub integration and preconfigured with the most popular ML tools, frameworks, and libraries so you can get started immediately. -
45
ZeusDB
ZeusDB
ZeusDB is a next-generation, high-performance data platform designed to handle the demands of modern analytics, machine learning, real-time insights, and hybrid data workloads. It supports vector, structured, and time-series data in one unified engine, allowing recommendation systems, semantic search, retrieval-augmented generation pipelines, live dashboards, and ML model serving to operate from a single store. The platform delivers ultra-low latency querying and real-time analytics, eliminating the need for separate databases or caching layers. Developers and data engineers can extend functionality with Rust or Python logic, deploy on-premises, hybrid, or cloud, and operate under GitOps/CI-CD patterns with observability built in. With built-in vector indexing (e.g., HNSW), metadata filtering, and powerful query semantics, ZeusDB enables similarity search, hybrid retrieval, filtering, and rapid application iteration. -
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Access Unify | Health
Access
Access Unify | Health is a healthcare data archiving platform designed to help organizations securely store and manage legacy EHR data. It enables hospitals and clinics to retire outdated systems while maintaining access to historical patient and financial records. The platform supports both cloud and on-premise deployment, offering flexibility for different healthcare environments. It ensures compliance with regulations such as HIPAA, CMS, and HITECH through automated retention and security features. Access Unify | Health includes powerful search and reporting tools, allowing users to quickly retrieve and analyze archived data. It also supports workflows for accounts receivable and release of information processes. The system provides secure access with encryption, role-based permissions, and audit logging. Overall, it helps healthcare organizations reduce IT costs while maintaining compliance and data accessibility. -
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Gemini Enterprise Agent Platform Notebooks provide a unified environment for data science workflows, combining the flexibility of Colab Enterprise with the power of Agent Platform Workbench. These notebooks enable users to explore data, build models, and deploy solutions without switching between multiple tools. With seamless integration into Google Cloud services like BigQuery and Apache Spark, users can analyze large datasets directly within the notebook interface. The platform supports rapid prototyping and model development by offering scalable compute resources and AI-powered coding assistance. It allows teams to move from experimentation to production efficiently using end-to-end workflows. Fully managed infrastructure ensures scalability, cost optimization, and minimal operational overhead. Enterprise-grade security features such as single sign-on and access controls provide a safe environment for development.Starting Price: $10 per GB
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IBM watsonx
IBM
IBM watsonx is a powerful suite of AI products designed to accelerate the adoption of generative AI across business workflows. With tools like watsonx.ai for AI application development, watsonx.data for data management, and watsonx.governance for regulatory compliance, businesses can create, manage, and deploy AI solutions seamlessly. The platform provides an integrated developer studio to foster collaboration and optimize the entire AI lifecycle. IBM watsonx also offers tools for automating processes, boosting productivity with AI assistants and agents, and supporting responsible AI through governance and risk management. Trusted by industries worldwide, IBM watsonx enables businesses to unlock the full potential of AI to drive innovation and enhance decision-making. -
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Azure Machine Learning
Microsoft
Accelerate the end-to-end machine learning lifecycle with Azure Machine Learning Studio. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R. -
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nebulaONE
Cloudforce
nebulaONE is a secure, private generative AI gateway built on Microsoft Azure that lets organizations harness leading AI models and build custom AI agents without code, all within their own cloud environment. It aggregates top AI models from providers like OpenAI, Anthropic, Meta, and others into a unified interface so users can safely ingest sensitive data, generate organization-aligned content, and automate routine tasks while keeping data fully under institutional control. Designed to replace insecure public AI tools, nebulaONE emphasizes enterprise-grade security, compliance with regulatory standards such as HIPAA, FERPA, and GDPR, and seamless integration with existing systems. It supports custom AI chatbot creation, no-code development of personalized assistants, and rapid prototyping of new generative use cases, helping educational, healthcare, and enterprise teams accelerate innovation, streamline operations, and enhance productivity.
