Platform Deep Dive · 2026

NEXUS AI

The Infrastructure Control Plane Built for the Conversational Era

Category Cloud Infrastructure
Providers GCP · AWS · Azure · Docker
Interface Conversational + API
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Deploy to GCP · Deploy to AWS · Deploy to Azure · Manage via Chat · Real-time Logs · Health Monitoring · Secret Management · Custom Domains · Multi-Cloud Control · AI-Native Infrastructure · Deploy to GCP · Deploy to AWS · Deploy to Azure · Manage via Chat · Real-time Logs · Health Monitoring · Secret Management · Custom Domains · Multi-Cloud Control · AI-Native Infrastructure ·

Cloud Infrastructure
Reimagined

NEXUS AI is not another dashboard. It's a paradigm shift — a cloud infrastructure control plane where you deploy, manage, and scale applications through natural conversation rather than clicking through labyrinthine menus.

The cloud industry has long suffered from a fundamental tension: as infrastructure complexity grows, the cognitive overhead of managing it grows proportionally. Kubernetes YAML files, AWS IAM policies, GCP service accounts, Azure resource groups — the modern cloud engineer is buried under layers of configuration, nomenclature, and provider-specific abstractions.

NEXUS AI was built to cut through this complexity. By placing a conversational AI layer on top of multi-cloud infrastructure, the platform transforms deployment management from a specialized technical discipline into something far more intuitive — a dialogue.

4
Cloud Providers
GCP, AWS, Azure, and Docker — deploy anywhere from a single interface
PRO
Current Plan Tier
Up to 500 AI requests and 5 concurrent containers per month
MCP
Protocol Standard
Model Context Protocol enables direct integration with AI assistants
01

What Is
NEXUS AI?

NEXUS AI is an AI-native cloud infrastructure control plane — a platform that unifies deployment management across GCP Cloud Run, AWS ECS Fargate (App Runner), Azure Container Apps, and local Docker environments through a single, intelligent interface.

At its core, NEXUS AI exposes a comprehensive MCP (Model Context Protocol) server that allows AI assistants — including Claude — to directly manage your cloud infrastructure. This means you can deploy a new application, check its logs, scale resources, monitor health, and manage secrets simply by talking to your AI assistant.

The platform handles the heavy lifting: building container images from your Git repositories, pushing them to cloud-native registries (ECR for AWS, GCR for GCP), provisioning infrastructure, configuring networking, and running health checks — all triggered from a single conversational command.

Claude / AI Assistant
NEXUS AI MCP Server
NEXUS AI Control Plane
GCP Cloud Run
AWS App Runner
Azure Container Apps
Docker
Your Applications
02

Multi-Cloud
Without the Complexity

NEXUS AI supports all four major container deployment targets under a unified abstraction layer. Whether your workload belongs on GCP's serverless Cloud Run, AWS's managed App Runner, Azure's Container Apps, or a straightforward Docker environment, NEXUS AI presents the same simple interface.

Provider Best For Auto-Scale Region
GCP Cloud Run
Serverless containers, global scale Yes Multi-region
AWS App Runner
Managed workloads, US-East default Yes us-east-1
Azure Container Apps
Enterprise workloads, .NET stacks Yes Multi-region
Docker (Local)
Development, testing, rapid iteration Manual Local
03

Git to Cloud
In One Command

NEXUS AI's source deployment capability bridges your Git repository directly to cloud infrastructure. Point it at a GitHub repo, specify your build commands and framework, choose a provider — and the platform handles everything else.

Step 01

Repository Ingestion

NEXUS AI clones your repository and analyzes the codebase. It respects custom install commands (npm ci, pip install), build commands (npm run build), and start commands (npm start, node server.js).

Step 02

Container Build

The platform containerizes your application — either using a detected or specified Dockerfile, or auto-generating one based on the identified framework. Supported frameworks include Node, Python, Go, and more.

Step 03

Registry Push

Built images are pushed to the appropriate cloud-native registry. AWS deployments use ECR (Elastic Container Registry), with images tagged by deployment UUID for precise version tracking and rollback capability.

Step 04

Provisioning & Health Check

Cloud infrastructure is provisioned and the service URL is configured. NEXUS AI runs HTTP health checks against the deployment endpoint, confirming live traffic readiness before marking the deployment as running.

// Deploy from GitHub via MCP — natural language trigger nexusai_deploy_source({ name: "my-app", repoUrl: "https://github.com/org/repo.git", provider: "aws_ecs_fargate", installCommand: "npm ci", buildCommand: "npm run build", startCommand: "npm start", environment: "PRODUCTION" }) // → Queued → Deploying → Running // → https://6s2i84ipfa.us-east-1.awsapprunner.com
04

The Full
Feature Set

🚀

Conversational Deployments

Deploy, scale, stop, restart, and delete applications using natural language through any MCP-compatible AI assistant. No CLI memorization, no console navigation.

📊

Real-time Logs & Health

Stream build and runtime logs directly into your conversation. Monitor health check status, restart counts, and exit codes without leaving your workflow.

🔐

Secret Management

Store and reference environment secrets securely. Pass secret names to deployments at runtime — API keys, tokens, and credentials never exposed in plain text.

🌐

Custom Domain Routing

Attach, verify, and manage custom domains on any running deployment. DNS verification is handled within the platform, no external tooling required.

↩️

One-Click Rollback

Roll back to any previous deployment revision instantly. NEXUS AI maintains full deployment history, making recovery from bad releases trivial.

🗄️

External DB Integration

Connect external databases, inspect schemas, and get AI-proposed DDL fixes when deployment errors suggest database issues — all from within the platform.

📈

Usage Analytics

Track AI request usage, container hours, active deployments by status, and plan quota consumption. Stay within limits without surprise overage charges.

🎫

Integrated Support

Create, view, and reply to support tickets directly from your AI conversation. Escalate deployment issues to the NEXUS AI team without switching contexts.

05

AI-Native
by Design

The Model Context Protocol (MCP) is the architectural foundation that makes NEXUS AI genuinely conversational — not just a dashboard with a chatbot bolted on. MCP allows AI models to discover and invoke platform capabilities as structured tools, creating a seamless bridge between human intent and cloud action.

"The difference between NEXUS AI and traditional cloud consoles is the difference between speaking and clicking. One maps to how humans naturally think. The other maps to how software was traditionally organized."

When connected to Claude via MCP, the entire NEXUS AI capability surface — deployments, logs, secrets, domains, database connections, support tickets, usage analytics — becomes instantly accessible through natural language. The AI understands deployment IDs, maps provider names to technical identifiers, and chains multiple operations (deploy → monitor → check logs → raise ticket) in a single coherent workflow.

The MCP server is available at https://api.zollo.live/mcp and exposes 25+ tools covering the full platform surface. Organizations on the PRO plan can make up to 500 AI-mediated requests per month, with token usage tracked transparently in the usage dashboard.

06

Who It's
Built For

NEXUS AI serves a wide spectrum of builders — from solo founders who need to ship quickly to engineering teams managing complex multi-cloud environments.

Founders & Indie Builders

Deploy full-stack applications without deep DevOps expertise. Focus on product, not infrastructure configuration. Go from GitHub commit to live URL in minutes.

Startups Scaling Fast

Move across cloud providers as needs evolve — start on Docker locally, graduate to GCP Cloud Run for production, expand to multi-region AWS without re-architecting.

Engineering Teams

Reduce the cognitive overhead of multi-cloud management. Standardize deployment workflows across teams using a common conversational interface.

Healthcare & Regulated Tech

Secret management, environment isolation (DEVELOPMENT / STAGING / PRODUCTION), and audit-friendly deployment history support compliance-sensitive workloads.

07

The PRO
Plan

NEXUS AI's PRO tier is designed for builders who need real production capability without enterprise pricing. The plan includes access to all four cloud providers, with the following quotas:

500
AI Requests / Month
Covers all MCP tool invocations across deployments, logs, secrets, and support
5
Concurrent Containers
Run up to 5 active deployments simultaneously across all providers
24h
Max Container Hours
Auto-destroy timer available for ephemeral workloads and testing environments

Storage is capped at 10GB, with container hours tracked and visible in the usage dashboard. The auto-destroy feature is particularly useful for preview deployments, demo environments, and temporary test workloads — keeping costs predictable.

08

The Future of
Cloud Management

The trajectory of software tooling has always moved toward higher abstraction. Assembly gave way to high-level languages. GUIs replaced command-line interfaces for millions of users. Infrastructure-as-code replaced manual server provisioning. Each abstraction level made the underlying capability accessible to a broader audience.

NEXUS AI represents the next abstraction: infrastructure as conversation. By exposing multi-cloud deployment management through the Model Context Protocol, the platform doesn't just make DevOps faster — it fundamentally changes who can do DevOps.

The implications reach beyond convenience. When deploying to AWS is as simple as saying "deploy my app from this GitHub repo using AWS," the activation energy for shipping software drops to near zero. Ideas move to production faster. Iteration cycles compress. The gap between builder and infrastructure narrows to nothing.

NEXUS AI isn't trying to be the most powerful cloud platform. It's trying to be the most accessible one — and in a world where AI mediates human-computer interaction, accessibility and power are converging.

Whether you're a solo founder deploying your first production app or an engineering team managing a portfolio of microservices across GCP, AWS, and Azure, NEXUS AI offers the same proposition: your infrastructure, your way, through conversation.

09

Frequently
Asked Questions

What is NEXUS AI?+
NEXUS AI is an AI-native cloud infrastructure control plane that allows developers and teams to deploy, manage, and scale applications across GCP Cloud Run, AWS ECS Fargate, Azure Container Apps, and Docker through natural language conversation via the Model Context Protocol (MCP).
What cloud providers does NEXUS AI support?+
NEXUS AI supports four cloud targets: GCP Cloud Run, AWS ECS Fargate (App Runner), Azure Container Apps, and local Docker — all through the same conversational interface.
How does NEXUS AI use the Model Context Protocol (MCP)?+
NEXUS AI exposes a comprehensive MCP server at api.zollo.live/mcp that allows AI assistants like Claude to invoke platform capabilities as structured tools — deploying apps, streaming logs, managing secrets, monitoring health, and handling support tickets through natural language.
Can NEXUS AI deploy from a GitHub repository?+
Yes. Provide the repo URL, install/build/start commands, and target provider — NEXUS AI handles containerization, registry push, infrastructure provisioning, and health checking automatically. Private repos are supported via secret-based GitHub tokens.
What is included in the NEXUS AI PRO plan?+
The PRO plan includes all four cloud providers, 500 AI requests/month, 5 concurrent containers, 10GB storage, 24-hour auto-destroy, secret management, custom domains, rollback, database integration, and integrated support ticketing.
How is NEXUS AI different from AWS Console or GCP Console?+
Traditional cloud consoles require navigating complex UIs and managing provider-specific configurations separately. NEXUS AI abstracts all of this into a single conversational interface — deploy to any provider using plain language, with all implementation details handled automatically.
Can NEXUS AI roll back a failed deployment?+
Yes. NEXUS AI maintains full deployment history and supports one-click rollback to any previous revision — either the immediately preceding deployment or a specific version by deployment ID.

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