Global AI Compute Solutions & Full-Stack AI Engineering
Starfire aggregates 100+ global data centers and compute supply factories into a unified, enterprise-ready infrastructure platform. Powered by NVIDIA HGX B300 (Blackwell Ultra) and backed by world-class AI engineers.
100+
Data Center Nodes
2,500+
Flagship GPU Cluster
99.98%
SLA Target Uptime
2.1 TB
HBM3e GPU VRAM
Nordics Tier-3
Iceland Geothermal
APAC Hubs
Singapore / HK
Americas
US East/West
About Starfire Technology
Connecting Fragmented Supply into Scalable Enterprise Capability
Rather than simple resource aggregation, Starfire acts as a single, unified service window that transforms raw global GPU supply into guaranteed, production-ready compute clusters with full-stack technical management.
Multi-Source Orchestration
Cross-partner screening across 100+ strategic data center partners eliminates single-supplier dependency while standardizing delivery protocols, SLA guarantees, and network topologies.
Regional & Compliance Match
Deploy exact cluster configurations in regions matching your enterprise requirements, regulatory compliance, data residency laws, and network latency targets.
Progressive Elastic Scaling
Seamlessly expand from initial POC validation and steady-state inference production to multi-node dedicated training clusters without environment re-architecture.
World-Class R&D and Infrastructure Engineering Team
Our engineering team combines academic research depth with enterprise-scale production experience. Team members and academic advisors stem from top global research institutions including **University of Cambridge**, **UC Berkeley**, **Hong Kong University of Science and Technology (HKUST)**, **Fudan University**, and **Zhejiang University**.
Cambridge
Distributed Systems
UC Berkeley
AI Frameworks & Systems
HKUST
Parallel Computing
Fudan Univ.
LLM & Quantization
Zhejiang Univ.
Agentic Orchestration
NVIDIA HGX B300 (Blackwell Ultra)
Purpose-built for massive scale LLM inference, post-training, ultra-long context window processing, and high-performance multi-modal workloads.
Total System HBM3e Memory
HGX B300 8-GPU system memory capacity, supporting ultra-large model parameter loading and extreme context window length without out-of-memory bottlenecks.
5th Gen NVLink Bandwidth
Ultra-high throughput GPU-to-GPU intra-node interconnect for zero-latency tensor parallelism and pipeline parallel execution.
Inter-Node Fabric Bandwidth
High-speed system networking architecture laying the foundation for seamless horizontal cluster scaling across multi-node topology.
Attention Acceleration
Enhanced attention engine performance compared to baseline Blackwell, drastically reducing TTFT (Time-To-First-Token) in long-context inference.
Optimal Enterprise Workload Alignment
LLM Inference & Post-Training
SFT, DPO, RLHF, and high-concurrency LLM production serving at reduced cost per million tokens.
Long-Context Window Models
128k+ to 1M token context window processing for complex document analysis, code repos, and legal AI.
Multimodal & High-Density HPC
Vision-Language models, video synthesis, scientific simulations, and large-scale parallel analytics.
Not Just Renting GPUs — Delivering Usable AI Infrastructure
Raw compute without engineering is friction. Starfire delivers production-ready clusters equipped with complete software stacks, networking, storage pipelines, and active SLA monitoring.
Architecture Design
Tailor-made compute, interconnect, and storage topology based on model parameters, target precision, QPS targets, and latency budgets.
Standardized Deployment
Turnkey delivery of host OS, NVIDIA drivers, CUDA toolkits, Container engines (Docker/K8s), PyTorch, vLLM, TensorRT-LLM, and LMDeploy.
Cluster & Storage Interconnect
High-speed intra-node NVLink & inter-node InfiniBand setup paired with distributed NVMe storage pipelines for continuous dataset staging.
Real-Time Monitoring
Continuous monitoring of GPU utilization rate, VRAM fragmentation, throughput, job status, and TTFT metrics to maximize hardware efficiency.
Fault Response & SLA
Proactive node replacement protocols, ticketing escalation paths, thermal management, and rapid hardware fault swap to minimize downtime.
Seamless Workload Migration
Hands-on assistance migrating container images, model weights, checkpoints, and production traffic with minimal implementation friction.
Maximizing Token Throughput Per Dollar Spent
Compute cost is governed not only by chip rental price but by execution efficiency. Our specialized optimization team fine-tunes training and inference workloads to extract peak performance from hardware.
Training & Fine-Tuning Acceleration
Implementation of 3D parallelism (Tensor, Pipeline, ZeRO Data Parallelism), FlashAttention-3, and custom SFT/RLHF tuning.
Precision Quantization (FP8 / INT8 / INT4)
Low-bit quantization strategies preserving model accuracy thresholds while halving VRAM footprint and boosting inference QPS.
Inference Engine Tuning (vLLM / TensorRT-LLM)
PagedAttention, KV-Cache compression, dynamic batching, and chunked prefill tuning to minimize latency.
PERFORMANCE BENCHMARK GAINS TYPICAL UNTUNED VS STARFIRE OPTIMIZED
* Measurements derived from internal vLLM / TensorRT-LLM benchmarks on Llama-3 70B & DeepSeek models.
Agentic AI & Multi-Agent Workflow Orchestration
Transitioning static LLMs into enterprise-grade autonomous agent systems capable of multi-step planning, tool utilization, and enterprise knowledge integration.
RAG & Knowledge Retrieval
Hybrid vector search, reranking, and dynamic context window staging to connect enterprise knowledge bases to LLM engines securely.
Tool Calling & API Integration
Robust function calling execution, structured output schemas, external database connections, and fail-safe exception handles.
Multi-Agent Collaboration
Role-based agent delegation, state management, inter-agent communication protocols, and complex task decomposition pipelines.
Governance & Guardrails
Input/output content filtering, safety alignment, step-by-step reasoning audit logs, and enterprise compliance monitoring.
Resource Scaling Built for Every Growth Stage
Match compute commitments with business milestones. We eliminate mandatory long-term lock-ins during early verification phases.
Short-Term Rental
Model loading, benchmark testing, framework compatibility verification, and business feasibility tests.
Steady-State Production
Weekly or monthly reserved capacity balancing strict uptime availability, performance, and operational budget.
Dedicated Isolated Nodes
Single-tenant exclusive nodes providing environment lock-in, zero multi-tenant noisy neighbors, and strict data security.
Multi-Node Clusters
High-speed InfiniBand network topology, shared distributed NVMe storage, and Slurm/K8s job orchestration for scale-out AI.
Four-Step Delivery Loop into Production
Model size, batch concurrency, precision, latency budget, data privacy, and region selection.
Bidding across 100+ partner nodes to match hardware specs, cost, delivery timeframe, and SLAs.
Environment configuration, CUDA drivers, network fabric testing, and baseline benchmark acceptance.
Ongoing monitoring of utilization rates, memory efficiency, and capacity adjustment.
Systemic TCO Optimization Framework
Lowering total cost of ownership is not just asking for lower hourly rates — it is optimizing procurement sourcing, contract commitments, hardware matching, and runtime utilization.
Interactive TCO & Savings Calculator
Estimate your cost reduction compared to standard hyperscaler public cloud pricing.
Case Study: 2,500x NVIDIA B300 Iceland Green Energy Cluster
Deploying a massive high-density compute cluster for a Tier-1 European AI enterprise requiring long-term capacity, extreme reliability, and sustainable energy sourcing.
Cluster Size
2,500
NVIDIA B300 GPUs
Contract Term
60 Months
Long-term Strategic
Availability SLA
99.982%
Uptime Guaranteed
Energy Sourcing
100%
Geothermal & Hydro
Cluster A: 1,024 GPUs
AIR-COOLEDStandard rack deployment engineered for rapid commissioning, flexible operational scaling, and production inference environments.
Cluster B: 1,476 GPUs
LIQUID-COOLEDUltra-high density liquid cooling deployment designed to handle maximum sustained TDP thermal dissipation for continuous heavy LLM pre-training.
Technical & Procurement FAQ
Powering Your Next-Gen AI Workload
Tell us your model scale, operational goals, and region preference. Our AI Infrastructure team will complete a tailored resource match, technical architecture, and TCO proposal.
Enterprise Business Inquiry
info@starfiretech.com.sg
Global HQ
Starfire Technology Pte. Ltd., Singapore
AI Compute & TCO Assessment Form
Step of 2Assessment Request Received
Our AI Infrastructure team will review your requirements and respond within 24 business hours with a resource evaluation and TCO estimate.