We design, build, and ship production AI systems on Cloudflare's edge — Workers, Workers AI, Agents SDK, Durable Objects, Vectorize, AI Gateway, R2, D1, Queues, Containers — at sub-50ms latency in 330+ cities.
Per Cast AI's 2026 State of Kubernetes Optimization Report, average GPU utilization is just 5% across 23,000 production clusters. "At 5% utilization, the math doesn't work." Workers AI bills for actual inference — not reserved capacity.
Data centers in 330+ cities deliver ~50ms latency to about 95% of internet users — on the same infrastructure proxying ~20% of the web. Region-pin for sovereignty when federal mission requires it.
Durable Objects give each agent its own SQL database, persistent memory, and hibernation — no separate data tier, no cold start, no glue code. Multi-agent systems become a primitive, not an architecture project.
Hybrid semantic+keyword retrieval, AI-Gateway-fronted models, R2-backed source corpus, audit trail end to end.
Each agent is a Durable Object with its own SQL state and lifecycle. MCP tool surface for clean external integrations. Hibernates when idle. The full agents & MCP playbook →
Kimi k2.6 (1T MoE) as the orchestrator; small Gemma scout workers run decomposed sub-tasks. Derived from MIT CSAIL's Recursive Language Models work (arXiv:2512.24601). This is the HotCopy architecture.
Same Cloudflare primitives, hardened: AI Gateway guardrails, region-pinning for data sovereignty, immutable audit logging, role-based access, FedRAMP-aware deployment patterns.
“Region-pinning” is three concrete controls, not a slogan:
Pins where High and Moderate impact data is processed, without losing edge performance.
Keeps all government data inside the defined FedRAMP region.
Every hop between edge and core, always.
We compose these into the deployment so CUI stays where your authorization says it stays.
Every site and API we serve through Cloudflare is protected against “harvest now, decrypt later” with TLS 1.3 + ML-KEM — automatically, no configuration changes. Post-quantum protection extends to Zero Trust access and the Secure Web Gateway, so encrypted traffic stays inspectable as you migrate. Built ahead of NIST's 2030–2035 deprecation deadlines.
The AI Gateway is the control plane between your application and any model provider:
Prompt injection, model poisoning, and excessive-use abuse, caught at the proxy.
What the user submits and what the model returns, both inspected and redacted.
Accessible servers behind one URL, with OAuth authorization and least-privilege access per agent.
API keys and secrets never touch the client; rotation stays simple.
RAG helps the model know more. MCP helps it do more. The Gateway makes both safe.
Some vendors carve out a special FedRAMP enclave and make you wait for capabilities to land in it. Cloudflare runs the same software in every data center, including the FedRAMP processing locations — so the authorized Cloudflare for Government environment carries nearly the entire platform, not a stripped-down subset. For federal engagements we provision there; commercial engagements run on the standard network. Either way: no rip-and-replace, no capability lag.
This page hits a Truvisory®-deployed Cloudflare Worker on first paint. The latency you see is your latency to the closest of 330+ Cloudflare data centers — typically the same region you live in.
Architecture decisions from active builds on the edge.
Why the Cloudflare Developer Platform is the best default backbone for production AI in 2026 — for mid-market operators and federal buyers. The business case across cost, speed, security, and ownership, with honest limits on where hyperscalers still win.
The pillar of our Cloudflare-vs-hyperscalers series — start here, then go deep on inference, latency, and dollars.
See it, cost it, trust it — instrumenting AI on Cloudflare with AI Gateway, evals, and an audit trail.
Ship an AI feature and you go blind on three things: what the model is doing, what it costs, and whether it's any good. Here's how Cloudflare AI Gateway and native analytics instrument all three.
Start with the observability-cost-evals hub, then go deep on each layer.
Daily-driver builder on Workers, Workers AI, Durable Objects, Vectorize, AI Gateway, R2, D1, Agents SDK, MCP. Production deployments on file (HotCopy, PresEngage). The engineer-on-the-platform claim is true and defensible.
Cloudflare's ASDP designation requires rigorous technical validation of security, performance, and reliability. We're in the process — and we won't surface a partner badge on the site that hasn't been earned. When it lands, you'll see it.
For inference and application workloads — not model training — one integrated edge platform beats stitching together a dozen hyperscaler services. You get pay-per-inference instead of idle-GPU billing, sub-50ms latency in 330+ cities, and state plus compute in one primitive. The math works where 5% average GPU utilization makes reserved capacity a losing bet.
Less than the hyperscaler alternative. Workers are standards-based, R2 is S3-compatible, and model routing is provider-agnostic. The real asterisk is Cloudflare-specific bindings — Durable Objects, D1, Vectorize — which would be a port, not a copy, if you ever leave. We keep your application logic and data model portable and say so up front.
Structurally less for inference and application workloads: zero egress fees, no idle-GPU reservations, and one comprehensible bill instead of charges spread across compute, storage, data transfer, and a separate vector database. For sustained GPU training it's the wrong tool — use a hyperscaler with reserved capacity there.
Yes, incrementally. We typically front your current system with Workers and Hyperdrive to accelerate legacy database access, move the highest-value paths to the edge, and leave the rest in place until it earns the move. No rip-and-replace, and the code lands in your repo at each step.
Daily drivers are Workers, Workers AI, Agents SDK, Durable Objects, Vectorize, AI Gateway, R2, D1, and Queues — with Hyperdrive, Containers, and Workflows where the workload calls for them. The §07 capability matrix lists every primitive we work in with its real use; we pick the smallest set that ships your system.
