DEPLOY. SCALE. Route.
SYS.INT is the deterministic deployment layer between your models and your users. Sub-5ms inference. Global edge routing. Full operational control.
Request a DemoHow does a model go from checkpoint to endpoint?
SYS.INT moves a trained checkpoint through five stages, train, package, route, deploy, observe, and puts it behind a live endpoint in under two minutes for a standard-size model. The same pipeline runs whether the checkpoint comes from the open-source catalog or your own fine-tuning job.
Infrastructure built for
raw intelligence
We engineer the substrate layer that sits between your models and your users. No abstractions. No magic. Just deterministic routing, sub-5ms inference, and transparent operational control across every edge node in the network.
Founded by systems engineers who spent a decade building distributed compute at hyperscale. We believe AI infrastructure should be inspectable, auditable, and brutally fast.
What handles routing between your app and the model?
Every request passes through one stateless edge router, then lands on the nearest of 212 inference nodes already holding the requested model in memory. There is no central proxy in the hot path, so a single region outage does not take the rest of the network down with it.
Select your compute tier
All tiers include zero-config deploys, built-in monitoring, and access to the SYS.INT inference API.
Community-grade inference. Rate-limited. No SLA.
Production-grade. Sub-5ms latency. 99.97% uptime SLA.
Air-gapped. On-prem. Full operational control.
What do teams ask before they deploy?
Six questions cover latency, model coverage, regions, pricing, security, and custom checkpoints, the topics that come up most before a team moves from evaluation to production.
01How fast is inference?
Median latency is 3.8ms and the 99th percentile is 11ms, measured from the edge node to the first token. SYS.INT routes each call to the nearest node that already holds the model in memory, so a warm model never pays a cold-load penalty on the hot path.
02How many models are available?
The platform hosts 147 foundation models across the open-source and licensed catalogs, plus any checkpoint you fine-tune yourself. Every model sits behind the same inference API, so switching models is a config change, not a rewrite.
03Which regions does it run in?
Inference runs across 50 edge regions today, with new regions added as demand grows. Pro and Enterprise plans can pin a workload to specific regions for data residency; the open-source tier runs on the shared pool with no region selection.
04How does pricing work?
The open-source tier is free with a 10,000-request monthly cap. Pro is a flat $249 a month for unlimited requests, and Enterprise is a custom contract for dedicated, air-gapped infrastructure. There are no separate per-model licensing fees on any tier.
05What is the security posture?
Every request is encrypted in transit with TLS 1.3, and Enterprise workloads can run fully air-gapped, on-premises, with no data leaving your network. API keys scope access to the control plane, and every call is written to an audit log.
06Can I bring my own fine-tuned model?
Yes. Upload a checkpoint through the deploy API and the platform packages it, health-checks it, and puts it behind the same routing layer as the built-in catalog. A standard-size checkpoint is live in under two minutes.
DEPLOY YOUR FIRST MODEL
The open-source tier includes 10,000 requests a month with no time limit. Upgrade to Pro for unlimited requests and sub-5ms routing.
Request a Demo