AI Model Fine-Tuning & Custom LLMs
Fine-tune open-source models (Llama 3.1, Mistral, Qwen) on your proprietary domain data using LoRA/QLoRA. Run privately on-premise or cloud VPCs with zero per-token API costs.
What is AI Model Fine-Tuning & Custom LLMs?
Commercial LLM APIs (OpenAI/Anthropic) can become prohibitively expensive at scale, risk exposing confidential proprietary data to third parties, and lack domain-specific terminology for specialized medical, legal, or financial use cases.
We engineer customized, fine-tuned open-source language models using Parameter-Efficient Fine-Tuning (LoRA / QLoRA) on Llama 3.1, Mistral, and DeepSeek. We clean and format your training datasets, benchmark validation loss, and deploy high-throughput inference servers (vLLM / Ollama) on your private cloud VPC.
Tailors model weights to your proprietary terminology with minimal GPU compute overhead.
Operates entirely inside your private AWS/RunPod/Vast.ai VPC with zero data leaving your network.
Replaces recurring $5,000+/month OpenAI API bills with predictable fixed GPU compute hosting.
What's Included in Every Project
Full-cycle AI engineering deliverables designed for accuracy, reliability, and business impact.
Proprietary Dataset Curation & Formatting
Data cleaning, deduplication, synthetic sample generation, and tokenization in JSONL format.
LoRA / QLoRA Training Experimentation
Supervised fine-tuning across Llama 3.1 (8B/70B), Mistral, or Qwen models with hyperparameter tuning.
Automated Evaluation & Validation Loss Benchmarks
Evaluation suite comparing base model vs fine-tuned checkpoint on domain test cases.
High-Throughput vLLM / TensorRT Inference Setup
Production model deployment with continuous batching and sub-50ms token generation.
OpenAI-Compatible REST API Wrapper
Drop-in API endpoint allowing existing applications to switch to your private model effortlessly.
30-Day Post-Launch Warranty & Model Checkpoint Handover
Complete transfer of Safetensors weights, training scripts, and deployment Dockerfiles.
Our 4-Step AI Engineering Process
Benchmark-driven sprint delivery with continuous accuracy evaluations.
Data Audit & Feasibility Benchmark
We analyze your training dataset, define target output formats, and choose the optimal base open-source model.
Dataset Cleaning & Tokenization
We prepare high-quality instruction-tuning pairs and split data into training and validation sets.
GPU Fine-Tuning & Evaluation
We execute LoRA/QLoRA training runs, optimize learning rates, and evaluate against domain benchmarks.
vLLM Cloud Deployment & API Handover
We deploy the quantized model on your private cloud VPC, test streaming latency, and hand over the weights.
Technologies & Foundation Models
Frontier LLMs (GPT, Claude & Gemini), vector databases, and workflow automation frameworks.
Milestone-Based Investment Tiers
Fixed pricing with no hidden licensing fees. 100% IP ownership upon final milestone.
Fine-tune a 7B/8B parameter model (Llama 3.1 / Mistral) on your domain dataset with private API deploy.
- Llama 3.1 / Mistral 8B Parameter Model
- Dataset Preparation (up to 10k Samples)
- LoRA / QLoRA Supervised Fine-Tuning
- OpenAI-Compatible REST API Endpoint
- vLLM Inference Deployment on Private VPS
- 30-Day Post-Launch Warranty
- 100% Model Weights Ownership
High-capability 70B parameter model fine-tuning with multi-GPU inference clustering and synthetic data.
- Llama 3.1 70B Parameter Architecture
- Synthetic Data Generation & Cleaning
- Multi-GPU vLLM Clustered Inference
- Domain-Specific Evaluation Benchmark Suite
- Quantized AWQ / GGUF Export Formats
- Priority 30-Day Support
- Full GitHub & Checkpoint Handover
Air-gapped on-premise GPU server deployment for defense, healthcare, or financial compliance.
- Air-Gapped On-Premise GPU Deployment
- Dedicated Senior LLM Fine-Tuning Architect
- Continuous Self-Learning Feedback Loop
- SOC2 / HIPAA / ISO 27001 Compliance
- 24/7 SLA Support Retainer
Custom Enterprise & Bespoke Project Scope
Have specialized requirements, existing legacy architecture, dedicated SLA agreements, or custom team workflows? We analyze your technical scope and deliver tailored milestone estimates within 24 hours.
Related AI Automation Case Studies
Measurable efficiency gains and cost reductions delivered for our clients.
Legal Contract Redline Model Fine-Tuning
Fine-tuned Llama 3.1 70B on 15,000 annotated commercial contracts, deployed privately on AWS EC2.
Medical Diagnostic Terminology Custom LLM
Trained a Mistral model on clinical trial reports, enabling doctors to summarize patient notes offline.
Frequently Asked Questions
Common questions about ai model fine-tuning & custom llms and our AI engineering methodology.
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Ready to implement your ai model fine-tuning & custom llms?
Describe your operational workflows and automation objectives. Receive a comprehensive feasibility review and fixed milestone quote within 24 hours.