AI infrastructure hosting
Ship apps and AI on the same infrastructure.
Push a repo to deploy. Spin up an endpoint to serve a model. One dashboard for both.
Private beta. No credit card, no commitment.
Built on the tools your team already uses
- Next.js
- Docker
- PyTorch
- Kubernetes
- NVIDIA
- PostgreSQL
The platform
One platform, two jobs
Most teams bolt a web host onto a GPU provider and maintain the seam between them by hand. iDynoTech removes the seam.
Deploy applications
Connect a Git repository and every push builds, previews and ships. Custom domains, automatic TLS and instant rollbacks are part of the platform, not add-ons.
Serve models
Run open-weight models or your own checkpoints behind an authenticated HTTPS endpoint. Endpoints scale to zero between requests, so idle capacity costs nothing.
One control plane
Applications, endpoints, logs, usage and spend in a single dashboard — with one team, one invoice and one set of API keys.
How it works
- 01
Connect a repo
Point iDynoTech at a Git repository — no other setup.
- 02
Build & deploy
Every push builds, previews, and ships automatically.
- 03
Live endpoint
Your app or model is live behind a URL. Done.
Capabilities
What you get on day one
Deployments
From commit to production in one step
Every branch gets a preview URL with its own isolated build. Promote it to production when it is ready, or roll back to any earlier release in a click — build caches and artifacts are retained, so a rollback is instant rather than a rebuild.
- A preview deployment for every pull request
- Build cache shared across branches
- Atomic rollback to any previous release
Inference
GPUs when you need them, nothing when you don't
Choose a GPU class, point at a model, and get an authenticated endpoint back. Warm pools keep first-token latency low while traffic is flowing; when it stops, the endpoint scales to zero and billing stops with it.
- Per-second billing on GPU time
- Scale to zero between requests
- Bring your own weights, or start from an open model
Observability
One view across requests and tokens
Application traces and model metrics land on the same timeline: latency percentiles, GPU utilisation, tokens in and out, and what each of them cost. Set a budget and hear about it before you cross it, not on the invoice.
- Latency and error rates per route
- Token and GPU usage per endpoint
- Spend alerts that arrive before the bill
Built for the way teams actually ship
- control plane for applications, endpoints, logs and spend
- 1control plane for applications, endpoints, logs and spend
- idle GPU cost — endpoints scale to zero between requests
- 0idle GPU cost — endpoints scale to zero between requests
- billing granularity on GPU time
- 1sbilling granularity on GPU time
- first-class languages: English and Arabic, right-to-left included
- 2first-class languages: English and Arabic, right-to-left included
These describe the platform we are building. We will publish independent benchmarks when the beta opens.
FAQ
Questions we get asked
Everything we can answer before the beta opens.
What is iDynoTech, exactly?
A managed hosting platform with two sides: application deployment in the style you already know from modern web platforms, and managed AI inference on GPU hardware. Both run under one account, one dashboard and one invoice.
When can I use it?
We are opening a private beta in stages. Joining the waitlist puts you in the queue, and we will email you when a slot is ready. No credit card is needed to hold a place.
Which models can I run?
Popular open-weight models will be available as one-click endpoints, and you will be able to deploy your own checkpoints from a container image or a storage bucket.
How will pricing work?
Usage-based: per-second billing for GPU time, plus bandwidth and build minutes for applications. Full pricing goes live before the beta does, and waitlist members see it first.
Is the platform available in Arabic?
Yes. The interface, documentation and support are being built in English and Arabic together, with genuine right-to-left support rather than a translated afterthought.
Where will my data live?
You will pick a region per project and workloads stay in it. Region availability at launch will be published alongside pricing.
Get early access to iDynoTech
Join the waitlist and we will send an invite as capacity opens, plus the occasional note on what we shipped.