Experience
the next level ofML & LLMs
deployment.
EzDeploy is the orchestration layer for AI deployment. Connect a repo and ship a production inference endpoint on your own cloud—AWS, GCP, Azure, RunPod, or Railway. One control plane for every live model. No Kubernetes to wrangle.
Explore the platform →MLOps is still broken. Shipping a model means weeks of DevOps, brittle pipelines, and GPUs sitting idle while the infrastructure catches up. Putting a model in production shouldn't require a platform team. EzDeploy is an orchestration layer that turns deployment into a single connection—repo to live endpoint, on your own cloud—so teams can ship, move, and monitor models without rebuilding infrastructure every time.
From repository to a live endpoint on your own cloud.
Connect your repository
Point EzDeploy at a GitHub repo. It parses the code, resolves dependencies, and builds an optimized production container — no Dockerfiles or Kubernetes to wrangle.
Deploy to your own cloud
EzDeploy stands up an inference endpoint on the infrastructure you choose — AWS, Google Cloud, Azure, RunPod, or Railway. Your models and data never leave your security perimeter.
Manage from one control plane
Shift live models across providers with zero downtime, and monitor health, token and API usage, data drift, and accuracy — all from a single dashboard.
EzDeploy is an orchestration layer, not a black box — you keep full control of your infrastructure. Now onboarding early-access teams.
Get early access →Deploying intelligence at the speed of thought.
From Repo to Endpoint
Connect a GitHub repository and EzDeploy handles the rest: it parses the code, resolves dependencies, builds an optimized production container, and stands up a live inference endpoint. For standard models, deployment becomes a single connection instead of a two-week DevOps project.
Bring Your Own Cloud
EzDeploy is an orchestration layer that runs on your infrastructure — AWS, Google Cloud, Azure, RunPod, or Railway. Your models and data never leave your own security perimeter, and you can shift live models across providers with zero downtime to follow GPU availability and cost.
One Control Plane
Once a model is live, EzDeploy becomes a single control plane to manage it. Track system health, monthly token and API usage, and get instant observability into data drift and drops in model accuracy — across every deployment, in one place.
Backed by the Microsoft for Startups Founders Hub.
Founders Hub
Selected for Microsoft for Startups to build out EzDeploy — from automated container builds to multi-cloud model deployment on enterprise-grade infrastructure.
$100K+ in Cloud Credits
Supported by six-figure in-kind cloud infrastructure credits, enabling enterprise-scale Azure GPU testing, high-performance computing, and sandbox telemetry validations.
Direct Access
Direct technical guidance channels with Microsoft engineers, helping us harden EzDeploy’s path from repository to production endpoint.
Core Architect
The minds engineering the next layer of zero-overhead machine learning deployment operations.
Akhyar Ahmad
Founder, CEO & Technical LeadTechnical founder driving Oryvo’s core engineering. Machine learning engineer and AWS Certified Solutions Architect. Software engineering student at the University of Engineering & Technology, Lahore.
Muhammad Anas
Head of People & Operations2 years of experience in software engineering. Cyber security student. Student at University of Engineering & Technology, Lahore.