Infrastructure for Scaling AI Startups
For AI-first companies, infrastructure cost is cost of goods sold. We help you move off expensive APIs at the right moment, build serving that scales with demand, and keep margins intact through each growth stage.
What's getting in the way
What worked at 1,000 users breaks at 100,000, and the bill usually breaks first. Startups need infrastructure that scales without a dedicated platform team, and without locking into choices they'll regret at Series C.
Early on, hosted APIs are the right call: fast to integrate and nothing to operate. As volume grows, the economics shift. We help you find that crossover point, move steady-state traffic onto infrastructure you control, and keep burst capacity on APIs, so margins improve without slowing your product team.
- Margin model: cost per user and per request forecast against growth
- Hybrid serving: APIs for burst, self-hosted models for steady volume
- Autoscaling: GPU capacity that follows traffic, including scale-to-zero
- Fractional platform team: senior engineers on retainer instead of three new hires
The path we follow
Unit economics
Model cost per user, request and feature against your growth plan.
Hybrid serving
Self-host the high-volume paths while keeping APIs for the long tail.
Autoscaling
GPU capacity that follows demand, including scale-to-zero for quiet hours.
Handover
Runbooks and training so your engineers own it, or keep us on retainer.
How we deliver it
GPU Infrastructure Optimization
Cut inference and training spend with better scheduling, quantization and right-sized clusters.
Explore service →SVC-04MLOps Pipeline Setup
Automate training, evaluation, deployment and monitoring so models ship like software.
Explore service →SVC-07Ongoing Managed AI Support
A monthly retainer for monitoring, upgrades and on-call support of your AI stack.
Explore service →Common questions
We only have two engineers. Can we run this?
Yes. We design for small teams, using managed Kubernetes and automation so day-to-day operation takes little time.
Will we be locked into a cloud?
No. The stack is portable across major clouds and GPU providers.
Find out what private AI would cost you.
A 45-minute call with an engineer, not a sales script. You'll leave with a rough architecture, a cost range and the next three steps.