Custom LLM Development Built on Your Data, Running on Your Infrastructure
Fine-tuned language models trained on your proprietary data, deployed on hardware you control. No data leaves your network. Full CMMC, HIPAA, and SOC 2 compliance from day one.
Generic AI vs. Custom LLM
Off-the-shelf models route your data through third-party servers. A custom LLM keeps everything inside your security perimeter.
Custom LLM Advantages
- 25-40% higher accuracy on domain-specific tasks vs. generic models
- Data never leaves your network. You own the model weights
- Fixed infrastructure cost. No per-token billing at scale
- Open-weight models (Llama, Mistral). Zero vendor lock-in
Cloud AI Risks
- Prompts processed on servers you cannot audit or control
- 30-day data retention by default on most platforms
- Not FedRAMP authorized for CUI. CMMC compliance gaps
- Per-token costs scale linearly. Model deprecation at vendor discretion
Custom LLMs for Regulated Industries
Domain-specific AI that understands your terminology, follows your conventions, and meets your compliance requirements.
Healthcare
Clinical documentation, discharge summaries, and prior authorization letters. PHI never leaves your network. Full BAA coverage with HIPAA compliance controls.
Defense and Government
CUI-safe AI for technical manuals, RFP responses, and compliance documentation. Air-gapped and ITAR-compliant environments supported. Aligned with CMMC requirements.
Financial Services
Regulatory filing analysis, risk assessment narratives, and client communications. SOC 2 Type II controls with full audit trails and model explainability documentation.
Legal
M&A due diligence, patent analysis, contract redlines, and research memos. Trained on your firm's precedent database and citation practices. Attorney-client privilege maintained.
What Changes With a Custom LLM
Data Exposure
Every prompt sent to cloud AI travels through servers you do not own, with retention policies you did not negotiate.
Generic Outputs
Off-the-shelf models lack your domain vocabulary, formatting conventions, and quality standards.
Escalating Costs
Per-token API fees scale linearly with usage. $60/user/month adds up fast across an organization.
Complete Data Sovereignty
Your data never leaves your network. Model weights, inference logs, and outputs stay on hardware you control.
Domain-Expert AI
Fine-tuned on your proprietary data with 25-40% higher accuracy on your specific tasks.
Fixed Infrastructure Cost
No per-token billing. ROI within 6-12 months for organizations spending $5K+/month on cloud AI APIs.
How We Build Your Custom LLM
Requirements and Data Audit
Data Preparation and Pipeline
Base Model Selection
Fine-Tuning (LoRA/QLoRA)
Benchmarking and Evaluation
Deployment and Monitoring
Built For
Frequently Asked Questions
How much data do we need to train a custom LLM?
Most fine-tuning projects achieve strong results with 5,000 to 50,000 high-quality examples. Quality matters more than volume. A curated dataset of 10,000 expert-written documents typically outperforms 100,000 unfiltered records.
What is the difference between fine-tuning and RAG?
Fine-tuning changes the model's weights, embedding domain knowledge permanently. RAG keeps the base model unchanged and retrieves relevant documents at query time. Many deployments combine both for optimal results. See our RAG vs. Fine-Tuning comparison.
How long does a custom LLM project take?
Typical projects run 6 to 12 weeks from kickoff to production. Organizations with well-organized data can reach production in 6 weeks. Projects requiring extensive data preparation take closer to 12.
Can a custom LLM be HIPAA compliant?
Yes. We deploy on infrastructure with AES-256 encryption, role-based access controls, audit logging, and network segmentation. We sign Business Associate Agreements for hosted deployments. Our HIPAA compliance practice has served healthcare organizations for over two decades.
What does a custom LLM project cost?
Projects range from $25,000 for focused fine-tuning to $150,000+ for full custom development including data engineering and on-premise deployment. Organizations spending $5,000+/month on cloud AI APIs typically achieve ROI within 6-12 months.
Explore Our AI Solutions
Ready to Build a Custom LLM?
Stop feeding proprietary data to third-party AI services. Get a private, fine-tuned model that delivers superior accuracy on your specific tasks.