Gateward sits in front of every LLM your organization runs — enforcing auth, routing each request to the right model — local or frontier — and cutting token spend. One control plane for the models you host and the ones you call.
It is the single doorway between your applications and your models — so control, cost and compliance stop being an afterthought.
Authenticate, authorize and apply policy before a single token reaches a model. Keys, quotas and rules live in one place.
Send each request to the right model — local for the routine, frontier for the hard calls — by cost, capability, latency or data residency.
Trim context, cache repeats and compress prompts — so every call, especially to frontier models like Claude, costs less. Pay for signal, not overhead.
Everything you need to put governance, routing and economy in front of your models — without slowing your engineers down.
Per-team keys, rate limits, budgets and policy — enforced at the gate, audited by default.
One endpoint, many models. Route by rules and fail over automatically when a provider degrades.
Caching, prompt compression and context trimming that cut spend without touching your app code.
Run entirely inside your network. In sovereign mode, no prompt or response ever leaves your infrastructure.
Every call logged with cost, latency and model — a full, exportable trail for finance and compliance.
Local models and frontier APIs — Claude, GPT and more — behind one OpenAI-compatible endpoint. Route the routine local, escalate the hard calls.
We are hardening Gateward across the full spectrum — from enterprise GPU servers to the new wave of cost-effective local AI hardware. Keep your models and your data in-house, without the hyperscaler bill.
Data-center class racks and existing GPU fleets — Gateward fronts them as one governed endpoint.
ValidatingUnified-memory Mac Studios clustered into a quiet, power-sipping local inference pool.
In testingThe Grace-Blackwell desk-side box — serious local inference without a data-center bill.
In testingStrix-Halo APUs with big unified memory and an on-chip NPU for cost-effective local models.
In testingFrontier labs like Anthropic (Claude) and OpenAI will keep building the strongest models — and for the hardest final decisions, you want them. But most agentic work — the loops, retrieval and routine steps — runs fine on cost-effective hardware you own. Gateward orchestrates both: keep the bulk inside your network, and pass the complex calls through to frontier models in a token-optimized way.
Point your existing SDK at Gateward's OpenAI-compatible URL. No rewrite.
Auth, policy, budgets and rate limits are enforced before the call goes anywhere.
Gateward picks the model, trims and caches tokens, and forwards the request.
Cost, latency and the full trail land in your logs — per team, per model.
Gateward is in private testing with a handful of teams. Share the models you run and the hardware you're considering, and we'll get you a tailored pilot.
Email gateward@digital1.one →