ML & AI
Enterprise LLM
Deploy, fine-tune, and operate large language models within your own infrastructure — full data sovereignty, compliance, and enterprise-grade performance.
The Case for Enterprise LLM
For many enterprises, sending sensitive data to third-party model APIs is not an option. Regulatory constraints, data residency requirements, IP protection concerns, and the need for predictable costs all point toward self-hosted or private-cloud LLM deployments.
Software Brothers helps you stand up enterprise LLM infrastructure that gives you the power of frontier AI without sacrificing control, privacy, or compliance.
What We Offer
- Private Model Deployment — Deploy open-source models (Llama, Mistral, Qwen, Phi) on your own GPU infrastructure, VPC, or on-premise servers.
- Fine-Tuning & Alignment — Domain-specific fine-tuning using LoRA, QLoRA, or full fine-tuning on your proprietary datasets.
- Inference Optimization — Quantization, batching, and serving optimizations (vLLM, TGI) for maximum throughput at minimal cost.
- Model Evaluation & Benchmarking — Rigorous evaluation against your domain-specific tasks before rollout.
- Access Control & Audit Logging — Role-based access, user-level quotas, and complete audit trails for compliance.
- MLOps Integration — Model versioning, A/B testing, canary deployments, and automated retraining pipelines.
Deployment Options
On-Premise
Full control on your own hardware. Best for maximum data security and air-gapped environments.
Private Cloud VPC
Isolated deployment on AWS, GCP, or Azure within your own VPC. Combines control with cloud elasticity.
Hybrid
Sensitive workloads on-prem, scalable overflow in a private cloud. Flexible and cost-efficient.