AI ส่วนตัวและการติดตั้ง LLM ภายในองค์กร

Data Sovereignty & Privacy

Prompts, embeddings, and completions never leave your network perimeter. You retain full ownership and auditability of every byte processed, eliminating third-party data-sharing agreements and residual-use clauses.

Regulatory Compliance

Meet HIPAA, GDPR, SOC 2, ITAR, and sector-specific mandates without relying on a vendor's compliance posture. On-premise deployment gives auditors a clear, controllable surface area.

Low Latency & Deterministic Performance

Eliminate variable round-trip times to cloud endpoints. On-premise inference delivers consistent sub-100ms token latency, enabling real-time applications such as code completion, live chat, and process automation.

Predictable & Declining Cost

Cloud API costs scale linearly with token volume. On-premise hardware is a capital expense that depreciates while throughput increases through model optimisation. At sustained volume, self-hosted inference costs 60-80% less per token.

Llama 3.1 (8B / 70B / 405B)

ผู้ให้บริการ: Meta

Best general-purpose open model family. Strong reasoning, instruction following, and multilingual support. The 8B variant runs on a single consumer GPU; the 405B variant rivals frontier closed models.

เหมาะที่สุดสำหรับ: General enterprise assistant, document analysis, code generation

Mistral 7B / Mistral Large

ผู้ให้บริการ: Mistral AI

Exceptionally efficient inference at the 7B scale. Sliding-window attention enables long-context processing with modest memory. Mistral Large competes with GPT-4 class models.

เหมาะที่สุดสำหรับ: High-throughput classification, summarisation, customer support

Mixtral 8x7B / 8x22B

ผู้ให้บริการ: Mistral AI

Mixture-of-experts architecture activates only 2 of 8 expert networks per token, delivering 70B-level quality at 12B-level inference cost. Excellent reasoning and code capabilities.

เหมาะที่สุดสำหรับ: Complex reasoning, multi-step analysis, code review

Fine-Tuned & Domain Models

ผู้ให้บริการ: Your Organisation

LoRA and QLoRA adapters let you specialise any base model on your proprietary data in hours, not weeks. Domain-tuned models outperform general models on narrow tasks by 20-40%.

เหมาะที่สุดสำหรับ: Medical coding, legal contract review, internal knowledge Q&A

Single NVIDIA RTX 4090 (24 GB VRAM) or Apple M-series Mac with 64 GB unified memory. Runs quantised 7-8B models at interactive speeds for small teams of 5-15 users.

โมเดลที่รองรับ: Llama 3.1 8B, Mistral 7B, Phi-3

Dual NVIDIA A100 (80 GB each) or equivalent. Handles 70B-class models with 4-bit quantisation and supports 50-100 concurrent users with batched inference.

โมเดลที่รองรับ: Llama 3.1 70B, Mixtral 8x7B, CodeLlama 70B

Multi-node clusters with 8x NVIDIA H100 GPUs per node. Required for full-precision 405B models and high-throughput production workloads serving thousands of users.

โมเดลที่รองรับ: Llama 3.1 405B, Mixtral 8x22B, any model at scale