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Enterprise LLM Infrastructure

Run AI inside your
own network —
no data leaves your perimeter

Simplico deploys and manages enterprise-grade local LLM infrastructure for organisations in Southeast Asia and Japan. Model selection, RAG pipelines, guardrails, ERP integration, and audit logs — fully within your firewall.

4–8
Weeks to production
5
Deliverables included
0
Data leaving your network
100%
On-premise deployment

Your teams are already using AI. The question is whether you control it.

Public AI tools are fast and capable — and your employees are using them with company data right now, on personal accounts, without oversight.

For enterprises operating under PDPA, APPI, PIPL, or 等保2.0, that is not a policy gap. It is active regulatory exposure. The solution is not to ban AI. It is to bring AI inside your perimeter, where your compliance and security teams can stand behind it.

What we deliver

A complete local LLM deployment

From bare infrastructure to a production-ready service your teams use every day.

01

Model Selection and Configuration

We identify the right open-weight model for your language environment and use cases — Llama 4, Qwen 3, Mistral, DeepSeek, or Japanese-tuned variants. We handle quantization, runtime configuration, and inference optimisation for your hardware.

02

LLM Harness and API Layer

We deploy an OpenAI-compatible API endpoint so your existing applications connect without code changes. Prompt management, tool routing, and workflow orchestration are configured to your requirements.

03

RAG Pipeline and Knowledge Base Integration

We build the retrieval layer that grounds model responses in your internal documents — contracts, technical manuals, compliance policies, production records. No hallucinated references. No data leaving your network.

04

Guardrails, Logging, and Observability

Every query and response is logged inside your network in a format your compliance team can audit. Guardrails prevent prompt injection, sensitive data leakage through outputs, and off-policy responses.

05

ERP, MES, and Document System Integration

We connect the LLM to the systems your teams actually use — SAP, 勘定奉行, 用友, 金蝶, your MES, or your document management platform. Use cases go live as integrated workflows, not standalone tools.

SAP 勘定奉行 用友 金蝶 MES Document systems
Architecture

How it all fits together — inside your perimeter

Every component runs within your network boundary. No query, document, or response crosses a third-party server.

flowchart LR classDef apps fill:#0b1220,stroke:#334155,color:#cbd5e1 classDef api fill:#082f49,stroke:#38bdf8,color:#e0f2fe classDef model fill:#083344,stroke:#22d3ee,color:#cffafe classDef rag fill:#3a1f0a,stroke:#f97316,color:#fed7aa classDef log fill:#052e16,stroke:#22c55e,color:#dcfce7 subgraph SYS["Your Internal Systems"] direction TB ERP["ERP / MES"]:::apps APP["Custom Apps"]:::apps DOCSYS["Document Systems"]:::apps end subgraph NET["🔒 Your Network — no data leaves this boundary"] direction LR API["LLM Harness API
OpenAI-compatible · Prompt mgmt
Tool routing · Orchestration"]:::api MODEL["LLM Model
Llama 4 · Qwen 3
DeepSeek · ELYZa"]:::model RAG["RAG Pipeline
Retrieval · Reranking
Context assembly"]:::rag VDB[("Vector Store
Embeddings")]:::rag DOCS["Knowledge Base
Contracts · Manuals
Policies · Records"]:::rag LOG["Guardrails · Audit Log
Prompt injection prevention
Compliance logging"]:::log end SYS -->|"API calls"| API API -->|"inference"| MODEL MODEL <-->|"retrieve context"| RAG RAG --> VDB VDB -->|"source docs"| DOCS API --> LOG
Who this is for

This service is built for you if

  • Your data is regulated under PDPA, APPI, PIPL, 等保2.0, or a sector-specific framework that restricts data egress
  • You need AI over internal documents, customer records, manufacturing data, or IP that cannot leave your network
  • Your query volume is consistent enough that predictable infrastructure costs beat variable cloud API fees
  • Your applications require latency that external APIs cannot guarantee — real-time quality inspection, sub-second translation, live decision support
  • Your organisation needs audit trails for AI-generated outputs for regulatory or internal governance purposes

If two or more of these apply, the conversation is worth having.

Document Intelligence

Contracts, manuals, policies — searchable and queryable without cloud exposure

Manufacturing AI

Real-time quality inspection, defect analysis, sub-second decisions

Multilingual Support

Thai, Japanese, Chinese, and English — tuned for your language environment

Compliance Reporting

Audit trails for every AI interaction — structured for regulatory review

How it works

From assessment to production in 4 to 8 weeks

01

Assessment

We review your use cases, data classification, compliance requirements, and existing infrastructure. We identify which workloads belong on local inference and which, if any, can stay on cloud APIs.

02

Model Selection

We recommend the right model family for your language environment, quantise it for your hardware, and configure the inference runtime for your expected load.

03

Harness Build

We deploy the full stack: API layer, RAG pipeline, prompt management, guardrails, logging, and observability. We configure integrations with your ERP, MES, or document systems.

04

Handover and Support

Your team receives a working service with full documentation. We provide ongoing support for model updates, scaling, and new use case additions.

Need to validate the approach before committing? We can run a scoped proof of concept in 2 to 3 weeks.

Regulatory coverage

Built for the regulatory environments of Southeast Asia and Japan

🇹🇭

Thailand

PDPA Cybersecurity Act

Designed around PDPA data processing requirements and the Cybersecurity Act. No personal data crosses a third-party server. Audit logs are structured for regulatory review.

🇯🇵

Japan

APPI J-SOX NISC

Configured for APPI third-party provision and cross-border transfer obligations, J-SOX audit trail requirements, and NISC guideline alignment. Supports Japanese-language models including ELYZa-tuned variants.

🇨🇳

China / Greater China

PIPL 等保2.0 数据安全法

Meets 等保2.0 classification requirements for systems handling important data. Designed around PIPL cross-border transfer restrictions and 数据安全法 obligations. Model options include Qwen 3 and DeepSeek R1.

Multi-market

ASEAN + Japan

For organisations operating across ASEAN and Japan simultaneously, we design the architecture to satisfy the strictest applicable framework across your footprint.

Free resource

Not sure where you stand?

Take the Enterprise Local LLM Readiness Assessment — a free 25-question self-evaluation covering compliance, infrastructure, use case clarity, integration complexity, and organisational readiness.

You will get a score across five dimensions and a clear picture of what to tackle before you deploy, what a partner should handle, and whether you are ready to move now.

Download the assessment No form — direct link
Five dimensions assessed
1
Compliance and data sovereignty
2
Infrastructure readiness
3
Use case clarity
4
Integration complexity
5
Organisational readiness

Or if you already know you need this: hello@simplico.net

Get in touch

Start the conversation

Send us a brief description of your environment and the workloads you are considering. We will come back with a practical assessment of what is achievable on your timeline and budget — no deck, no sales call, just a direct answer.

LINE
ID: iiitum1984
Call / WhatsApp
(+66) 83001 0222

Based in Bangkok. Serving enterprise clients across Thailand, Japan, Singapore, and the wider ASEAN region.

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