Partner & custom deployments

GLBNXT Platform is designed to be deployed and delivered at scale through partners. System integrators, technology consultancies, AI agencies, and managed service providers working with GLBNXT can deploy the platform for their clients as a fully configured, client-specific environment tailored to the use cases, compliance requirements, and technical constraints of each engagement. This model allows partners to deliver sophisticated AI capability to their clients without building or operating AI infrastructure themselves.

This section explains how partner deployments work, what customisation is available at the environment level, and how partners and their clients should approach the deployment model to get the most from the platform.

The Partner Deployment Model

In a partner deployment, GLBNXT works directly with the partner organisation to provision and configure a platform environment on behalf of a client. The partner takes responsibility for the solution layer, designing and building the AI applications and workflows that meet the client's requirements. GLBNXT takes responsibility for the platform layer, managing the infrastructure, security, compliance, and operational foundation that the partner's solutions run on.

This model allows partners to offer clients a complete AI solution that includes both the applications their team builds and the enterprise-grade managed infrastructure those applications run on, without requiring the partner to develop or maintain infrastructure capability themselves.

Partners typically interact with GLBNXT at two levels. At the account level, the partner manages the commercial relationship, onboarding process, and ongoing engagement for each client deployment. At the technical level, the partner's development team works within the client's platform environment to build and deploy solutions, using the same platform capabilities and documentation available to any GLBNXT Platform development team.

Environment Configuration for Partner Deployments

Every client environment deployed through a partner is a dedicated, isolated platform environment. Client environments are not shared with other clients or with the partner organisation itself. Each environment has its own compute allocation, storage, network boundary, access controls, and audit trail.

During onboarding, the environment is configured in collaboration with the partner based on the requirements of the specific client engagement. Configuration decisions made during onboarding include the following.

Stack selection: the specific set of platform tools and services deployed in the client environment. GLBNXT configures each partner deployment with the precise stack the client's use cases require, without deploying unused components that add operational complexity and cost. A client requiring RAG-based assistants and workflow automation receives a stack configured for those capabilities. A client requiring high-performance model inference for a user-facing application receives a stack optimised for that workload.

Compute allocation: the GPU and CPU resources allocated to the environment based on the anticipated workload. Compute allocation is agreed during onboarding and can be adjusted as the client's usage grows or their workload requirements change.

Model selection: the models deployed in the client's Model Hub, selected based on the use cases the partner will be building and the quality, latency, and capability requirements of the client's applications.

Compliance configuration: the security controls, audit logging configuration, data retention policies, and compliance documentation applicable to the client's regulatory environment. For clients in regulated sectors, compliance configuration is a first-priority activity during onboarding.

Access and identity configuration: the identity provider integration, user roles, and access policies configured for the client's team and for the partner's development team where the partner requires access to build and maintain solutions.

White-Label and Branded Deployments

For partners who deliver AI solutions under their own brand or under a client-specific brand, GLBNXT Platform supports white-label deployment configurations. In a white-label deployment, the platform environment and any managed frontend components are presented to end users under the partner's or client's brand rather than under the GLBNXT brand.

White-label configuration options include custom domain names for the platform console and hosted application interfaces, custom visual branding applied to managed chat interfaces and webchat components, and custom naming for the environment that aligns with the partner's or client's product identity.

White-label deployments do not affect the underlying platform capabilities, security controls, or compliance posture of the environment. The infrastructure and operational layer remains fully managed by GLBNXT regardless of the branding applied at the interface level.

Multi-Client Management for Partners

Partners managing multiple client environments through GLBNXT have access to a partner management layer that provides visibility and control across their client portfolio without requiring separate login sessions for each environment.

Through the partner management layer, partners can view the operational status of each client environment, manage onboarding and offboarding processes for new and departing clients, review usage and consumption data across their portfolio, and coordinate with GLBNXT on support and escalation activities for specific client environments.

Each client environment remains isolated from every other client environment. The partner management layer provides visibility and administration capability without creating any connectivity or data sharing between individual client environments.

Custom Infrastructure and Deployment Topologies

Beyond the standard managed cloud deployment, GLBNXT Platform supports custom deployment topologies for clients and partners with requirements that go beyond what the standard model provides.

On-Premise Deployment

For clients with the most stringent data sovereignty requirements, GLBNXT Platform can be deployed on-premise within the client's own infrastructure. On-premise deployments place every component of the platform stack within the client's data centre or private cloud, under their direct operational control. GLBNXT supports the deployment, configuration, and ongoing maintenance of on-premise environments in collaboration with the client's infrastructure team.

On-premise deployments are suited for public sector and government clients, financial services clients under specific data localisation obligations, and any client that has made binding commitments about infrastructure ownership and control that cannot be satisfied by a managed cloud deployment.

Hybrid Deployment

Hybrid deployments combine on-premise components with managed cloud components, placing the most sensitive workloads and data within the client's own infrastructure while using managed cloud infrastructure for workloads with less stringent residency requirements. Hybrid deployments allow clients to benefit from the operational simplicity of managed cloud infrastructure for the majority of their workloads while satisfying specific sovereignty requirements for sensitive components.

Dedicated Cloud Infrastructure

For clients who require the isolation of on-premise deployment but prefer not to manage their own physical infrastructure, GLBNXT can deploy the platform on dedicated cloud infrastructure within a specified EU region. Dedicated infrastructure provides complete isolation from other platform tenants at the compute and networking layer, with the operational management remaining with GLBNXT.

Solution Templates and Accelerators

GLBNXT maintains a library of pre-built solution templates and configuration accelerators that partners can use to reduce the time required to deliver common AI use cases for their clients. Templates cover the most frequently implemented solution patterns on the platform, providing a validated starting point that partners can customise for each client engagement rather than building from scratch.

Available templates cover use cases including RAG-based internal knowledge assistants, document review and analysis workflows, customer support automation, automated reporting pipelines, and compliance Q&A systems. Each template includes a pre-configured application architecture, sample prompts and system configurations, ingestion pipeline setup, and deployment guidance.

Partners who develop effective solution configurations for a specific industry or use case can work with GLBNXT to contribute those configurations to the template library, making them available across the partner network and reducing delivery time for similar engagements in the future.

Partner Technical Enablement

GLBNXT provides technical enablement resources for partner development teams working with the platform. Enablement covers platform architecture and capabilities, solution design patterns, compliance and governance requirements for common sectors, and the delivery practices that lead to successful client deployments.

Technical enablement is available through the following channels.

Onboarding support: dedicated technical support for the first client environment a new partner delivers, including access to a GLBNXT technical contact throughout the onboarding and initial build phase.

Partner documentation: access to this documentation and any partner-specific technical guidance relevant to the delivery model, solution templates, and compliance requirements applicable to the partner's target sectors.

Solution design reviews: GLBNXT technical team availability to review the architecture of complex or high-stakes solution designs before development begins, providing feedback on approach, component selection, and potential risks.

Escalation support: access to GLBNXT's technical and operational teams for escalating issues that arise during client engagements and require platform-level investigation or remediation.

Responsibilities in a Partner Deployment

Partner deployments involve three parties with distinct responsibilities: GLBNXT, the partner, and the client. Understanding these responsibilities clearly is essential for ensuring that governance, support, and compliance obligations are fulfilled without gaps or ambiguity.

GLBNXT is responsible for: platform infrastructure and operations, managed component availability and performance, security and compliance controls at the platform layer, incident response for platform-level events, and the contractual and documentation obligations that support the client's compliance posture.

The partner is responsible for: solution architecture and application design, the quality and behaviour of the AI applications and workflows deployed in the client environment, client-facing communication and relationship management, compliance of application-layer design with applicable regulatory requirements, and first-line technical support for the client on solution-related matters.

The client is responsible for: defining and communicating their use case requirements, compliance, and governance obligations to the partner, managing user access and organisational policies for use of the deployed applications, responding to any data subject rights requests related to personal data processed through the applications, and fulfilling regulatory obligations that go beyond what the platform and partner can address on their behalf.

Where responsibilities overlap or are ambiguous for a specific client engagement, these should be discussed and documented during onboarding. Clear responsibility allocation from the start of a deployment prevents gaps in governance and support that become problems in production.

For guidance on the technical capabilities available in partner-deployed environments, the rest of this documentation applies equally to partner deployments as to direct client deployments. For guidance on compliance and data sovereignty in partner deployments involving regulated sector clients, see the Compliance Frameworks and Data Sovereignty sections.