How GLBNXT Platform works

GLBNXT Platform operates on a simple principle: GLBNXT manages the infrastructure, and your team builds the solutions. Every capability on the platform is designed around this division, so development teams never have to context-switch between building AI products and maintaining the stack that runs them.

The Two-Layer Model

The platform is structured around two distinct layers that work together seamlessly.

Managed Platform Layer

The Managed Platform Layer is everything GLBNXT operates on your behalf. It forms the complete enterprise-grade foundation that your AI solutions run on, handling every operational concern that would otherwise fall to your DevOps and infrastructure teams.

This layer includes:

• Compute - GPU and CPU resources provisioned and scaled on demand, optimised for AI inference and training workloads

• Kubernetes orchestration - containerised workloads managed, scheduled, and scaled automatically across your environment

• Networking and security - isolated network environments, firewall rules, ingress controls, and secure communication between services

• Secrets and credential vault - credentials, API keys, and sensitive configuration managed securely and injected into applications at runtime

• Storage and backups - persistent storage, object storage, and automated backup policies across all data services

• Observability and monitoring - infrastructure metrics, health checks, alerting, and performance visibility across the full stack

• Compliance and audit trails - complete logs of platform activity, query history, and data access events to support regulatory requirements

• Model routing - intelligent routing of inference requests to the appropriate models and compute resources based on configuration

Solution Layer

The Solution Layer is where your development team works. With the managed foundation in place, engineers, data scientists, and architects have direct access to every component needed to design, build, and deploy production-grade AI applications.

This layer includes:

• Vector databases - for semantic search, retrieval-augmented generation, and embedding storage

• RAG pipelines - end-to-end retrieval and generation workflows connected to your data sources

• Agents and memory - multi-agent systems with persistent memory, tool use, and reasoning capabilities

• Workflows and triggers - automated processes connecting AI models, APIs, data sources, and external services

• Functions and APIs - exposing AI capabilities as programmable endpoints for downstream applications

• Webchat components - configurable chat interfaces and assistant frontends for end users

• User-facing applications - complete AI-powered products deployed and hosted within the platform environment

From Prototype to Production

GLBNXT Platform is designed to compress the time between an idea and a working production deployment. Because the infrastructure is already in place, teams can move directly from designing a solution to building it, without waiting on environment setup, security reviews, or DevOps provisioning cycles.

A typical journey on the platform looks like this:

1. Access your environment - your platform environment is provisioned and ready from day one, with models, databases, and services available immediately

2. Select your approach - choose a low-code path using visual builders and pre-built templates, or a full-code path using direct APIs and custom logic, or combine both within the same project

3. Build your solution - connect models, data sources, workflows, and interfaces using the platform components available in your stack

4. Deploy and monitor - publish your application within the platform environment, with observability, audit logging, and scaling handled automatically

Low-Code and Full-Code Flexibility

GLBNXT Platform supports teams working at different levels of technical depth, and allows both approaches to coexist within the same environment.

Low-code approaches are suited for teams that want to move fast using visual builders, workflow automation, and pre-built solution templates. This path is particularly effective for agencies and consultancies delivering AI solutions to clients without requiring deep ML expertise on every project.

Full-code approaches give engineers direct access to platform APIs, model endpoints, database connections, and infrastructure primitives. This path supports custom logic, complex architectures, and integrations that require precise control.

Most production environments on GLBNXT Platform use a combination of both, applying the right tool to each part of the solution.

Open-Source at the Core

Every component in the GLBNXT Platform stack is built on open-source technology. GLBNXT takes the world's best open tools, makes them enterprise-ready, and delivers them as a cohesive managed platform. There are no proprietary formats, no hidden layers, and no lock-in to GLBNXT as a vendor. If your organisation ever needs to take a component in a different direction, the underlying technology remains fully accessible and portable.