Build and run AI agents across browsers, computers, AI models, cloud infrastructure, local machines, remote nodes, and distributed environments.
Flushnet connects AI reasoning with real execution: browser and desktop automation, private/local inference, multi-model routing, GPU resources, distributed computing, workflows, files, and connected services.
Concrete AI and compute products built on shared Flushnet infrastructure.
AI agents that use browsers, computers, terminals, files, workflows, applications, and remote nodes. Designed for real execution rather than chat-only assistance.
Open AI RunnerAn autonomous multi-model AI platform designed to choose models and tools, work with files, connect services, use computers, and execute longer end-to-end tasks through one agent experience.
Explore Flushnet AIPrivate and local AI inference across your own computers and nodes, with support for local model runtimes and distributed execution when workloads need more than one machine.
A common routing and control layer for external AI providers, private models, local models, tools, policies, usage, and future credit-based multi-model access.
Provision and coordinate GPU and compute resources for AI inference, model workloads, automation, remote execution, and distributed processing.
APIs, MCP-ready services, connected tools, workflows, job execution, remote nodes, and reusable modules for building AI-powered applications and agents.
Run browser automation, desktop and terminal actions, file operations, AI workflows, remote machine orchestration, sandbox tasks, connected applications, and reusable automation from one web-based operator platform.
AI agents · browser automation · desktop automation · terminal execution · file operations · remote nodes · workflows · computer use · MCP tools
Open Flushnet AI RunnerFlushnet technology extends beyond a single cloud AI service or a single computer.
Connect machines and resources directly across distributed environments for coordinated execution and resilient workloads.
Distribute tasks across local and remote computers, coordinate work between nodes, and use available compute where it is most useful.
Run AI models on user-controlled computers and infrastructure when privacy, cost, locality, or offline operation matters.
Technology developed around peer and distributed operating concepts can combine compute, memory, storage, networking, and execution capacity across machines.
Move workloads closer to devices, users, sites, and data rather than requiring every operation to run in one central cloud location.
Provision and manage GPU-backed workloads alongside local and distributed resources for AI inference and compute-heavy tasks.
Flushnet also brings long-standing media and streaming experience into the wider automation and AI platform.
Technology and infrastructure for real-time video delivery, live events, broadcast workflows, and audience-facing streaming experiences.
Processing, recording, editing, storage, replay, media workflows, and automation around video and audio content.
Experience with online broadcast channels, radio, television, multi-device delivery, and interactive media services.
Combine media workflows with AI generation, transcription, translation, analysis, editing, automation, and publishing tools.
Use remote nodes and distributed compute for media processing, automation, storage, and workload execution.
Web-based audio, video, diagram, document, and creative editing services can be connected to AI and automation workflows.
A broad technology base for AI, automation, infrastructure, media, secure workflows, and customer-facing applications.
Choose cloud AI, private AI, local execution, remote nodes, distributed compute, or external services based on the workload.
Route work to external frontier models when needed while retaining the option to use local, private, or self-hosted models for cost, privacy, control, and availability.
Use cloud services for shared infrastructure while AI Runner and distributed nodes can execute on user-controlled machines and real browser sessions.
Combine autonomous execution with explicit controls, permissions, auditability, status tracking, and operator-driven workflows.
Turn repeated browser, terminal, file, AI, media, and infrastructure tasks into reusable workflows and agent capabilities.
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