The cloud built for AI workloads
Routed inference. Cached objects. One cloud.
Route AI requests across hosted models, open-source AI services, and private endpoints with automatic fallback, cost controls, observability, and policy-based routing.
Explore AI RouterPut Pipe in front of S3 and serve repeat-heavy objects from the edge. Keep S3 as your source of truth while reducing egress costs and improving delivery performance.
Explore S3Pipe sits between every AI agent and the providers, models, and data they call on. Faster, cheaper, more reliable — without changing how your agent is built.
Works with your favorite AI agent
Two cloud layers are becoming one. Pipe Network is the AI Cloud where data and compute converge
The read layer — the infrastructure layer between your AI workloads and the providers, models, and data they call on.
Modern AI applications depend on reliable model access and fast delivery of large data. Teams need to route requests across providers, serve model files and datasets closer to users, reduce egress costs, and keep applications online when providers degrade.
Pipe brings model routing and edge data delivery into one AI Cloud.
Connect any hosted model, open-source AI service, or private endpoint through one API.
Serve model files, datasets, media, software assets, and S3 objects from a global edge network.
Reduce egress, manage usage, route by policy, and optimize infrastructure spend across providers.
Most teams start with one model provider. Then they add another. Then fallback logic, usage tracking, cost controls, evals, rate limits, private endpoints, and provider-specific SDKs. Eventually, they're maintaining their own AI infrastructure.
Pipe gives teams a managed routing layer for AI traffic, plus the edge delivery layer needed for AI data — so engineering stays focused on the application, not the plumbing.
Route user requests across providers by cost, latency, or quality. One API. No provider lock-in.
Keep Cursor, Claude Code, and your fleet responsive with fallback routing when providers degrade.
Serve weights, checkpoints, datasets, and inference from one global edge — not one cloud region.
Push generated images, video, and model outputs to users from the closest POP.
Centralize provider access, team budgets, audit trails, and private endpoints — across the company.
Use Pipe AI Router to route AI traffic across providers. Use Pipe for S3 to reduce object delivery costs. Bring them together as your AI infrastructure scales.