01

One gateway in front of every model

A hybrid reference design for regulated workloads: sensitive work stays in your account, other work uses the cloud's model service.

Hybrid LLM Gateway
checkssensitivegeneral workdata residencyCallersAWS CloudCustomer accountVPC · privateGPU node pool · open-weight modelsShared servicesManaged models · same regionOption · in-region GPU cloudAgentsCoding assistantsRAG servicesBatch jobsGuardrailsmasking · output checksLLM gatewayroute · budget · auditIAM Identity CentervLLM / TGIopen-weight modelsAmazon EKSGPU node poolAmazon EC2 GPUinstancesAmazon BedrockIn-region modelendpointFPT Smart Cloud · VN, JPAWS Secrets ManagerAmazon CloudWatchusage · cost · latencyAudit logevery call

Point at a component to light its links; select it for what it does here and the practice that makes it right on AWS.

Point at a component to see what it does; select it for the best practice.Open the architecture
02

Three places a model can run

Chosen per workload, not per company. Many customers use more than one, behind one gateway.

OptionFits whenWhat NGT engineers
Hyperscaler AI: Amazon Bedrock, Azure OpenAI, Vertex AIThe fastest start; the region meets your data rulesPrivate endpoints, identity, guardrails, cost tags, pipeline
Open-weight models on GPU KubernetesSensitive data must stay in your account or data centreGPU node groups, serving (vLLM, TGI, Triton), scaling, operations
In-region GPU cloud: FPT AI Factory, Token Factory (FPT Smart Cloud)Data must stay in Vietnam or JapanArchitecture, integration, gateway routing, quotas, operations
03

No customer data offshore

For customers whose data may not leave their environment. The offshore team never sees it.

  1. 01Build on mock data
    • Agent core built on mock or synthetic data
    • Public models in the build zone
    a release packagesecurity boundary
  2. 02Cross the boundary
    • Source and package review
    • Licence, SBOM and vulnerability checks
    customer approval
  3. 03Connect in your zone
    • You approve and import the package
    • Adapters and data connectors added on your side
  4. 04Run with real data
    • Self-hosted open-weight model in the secure zone
    • Your data stays there
04

One agent, two environments

The same agent code in two zones. Only the models and the data differ.

Build zoneCustomer zone
PurposeDevelop and testProduction
ModelsPublic modelsSelf-hosted open-weight LLM
DataMock and syntheticReal customer data
LocationFPT delivery environmentThe customer's secure environment
05

Platforms we build on

Hyperscaler AI, open-source model tooling and FPT group platforms. NGT designs, integrates and runs on them.

Hyperscaler AI services

Amazon BedrockAzure OpenAIGoogle Vertex AI

Open models and serving

huggingfacevLLMTGINVIDIA Triton

Agent frameworks and protocols

langchainlanggraphDifyMCPA2A

FPT group platforms

FPT AI FactoryToken FactoryFPT AI AgentsCodeVista
Ecosystem, not NGT products

FPT AI Factory, Token Factory and FPT AI Agents are run by FPT Smart Cloud; CodeVista by FPT Software's AI Center.

SourcesNGT Service Offering v3.2 (Jul 2026)AI-First DevOps Transformation: Services & Solutions, NGT (Oct 2026)Full SDLC with GenAI & Multi-Agent AI, NGT (Jun 2025)Platform Engineering v1.2, NGT (Sep 2026)FHN AI Service Introduction v0.9.3 (Mar 2026)Executive briefing: Look Forward 2027, FHN (Oct 2026)FPT Smart Cloud: AI Agents, Token Factory and AI Factory introductions (2025–2026)