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Custom AI ModelDevelopment and Training
Off-the-shelf AI models deliver generic results. Petronella Technology Group builds, fine-tunes, and deploys custom AI models trained on your proprietary data for domain-specific performance that general models cannot match. Private infrastructure options ensure your training data never leaves your control.
Custom Model Development Services
From model selection through production deployment, we handle the full AI model lifecycle with security embedded at every stage.
Model Selection and Sizing
We evaluate your use case against available models (Llama, Mistral, Phi, Qwen) and recommend the best fit for your performance, hardware, and compliance needs.
Fine-Tuning on Your Data
LoRA, QLoRA, and full fine-tuning approaches on your domain data. Training happens entirely within your environment for complete data sovereignty.
RAG Pipeline Development
Retrieval-augmented generation that grounds model outputs in your actual documents and knowledge bases for accurate, citation-backed responses.
Production Deployment
Optimized inference with quantization, batching, and tensor parallelism. Deployed on private infrastructure or managed cloud.
Security Hardening
Prompt injection defenses, input validation, output filtering, and audit logging following NIST and OWASP LLM Top 10 standards.
Monitoring and Optimization
24/7 monitoring of model health, inference latency, GPU utilization, and error rates with proactive alerting.
Generic vs. Custom Models
Generic Model Responses
General-purpose models miss industry terminology, document formats, and domain-specific patterns.
Per-Token API Costs
Commercial API pricing scales linearly with usage, making high-volume workloads expensive.
Data Sent to Third Parties
Every prompt and response traverses provider infrastructure outside your security boundary.
Domain-Specific Accuracy
Models fine-tuned on your data understand your terminology, workflows, and regulatory context.
Fixed Infrastructure Cost
Unlimited inference at predictable cost. Organizations processing 1M+ tokens daily see 60-80% savings.
Complete Data Sovereignty
All training and inference runs within your controlled environment with zero external data exposure.
Frequently Asked Questions
What hardware do we need for custom model training?
A 7B parameter model runs on a single NVIDIA A100 or H100 GPU. 70B models require 2-4 GPUs. We handle all hardware sizing and can deploy on your existing GPU infrastructure if compatible.
Which models work best for fine-tuning?
Llama 3.1, Mistral, and Qwen 2.5 are current leaders for general-purpose deployment. For specialized tasks, smaller fine-tuned models often outperform larger general models at lower cost.
Can you deploy in air-gapped environments?
Yes. We regularly deploy in CMMC and classified environments with no internet connectivity. All model weights and dependencies are packaged for offline installation.
How does cost compare to API pricing?
At moderate usage (500K+ tokens/day), private deployment typically breaks even within 6-12 months. At high usage (5M+/day), costs are 60-80% less annually.
How do we get started?
Call 919-348-4912 or schedule a consultation. We assess your use case, recommend models, and size the infrastructure.
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Ready to Build Custom AI Models?
Schedule a free consultation to discuss your custom model requirements, data environment, and deployment needs.