Custom Models & Fine-Tuning for proprietary problems.
Domain-specific model fine-tuning (LoRA / QLoRA), embedding models, and private local LLM deployments tailored exclusively to your business datasets.
Frontier generalist models fail on specialized enterprise jargon. We fine-tune open weights to become masters of your domain.
Sending sensitive corporate IP to third-party commercial APIs creates vendor lock-in and compliance vulnerabilities. Steigern Tech fine-tunes and quantizes open-weights models specifically on your internal data, delivering private models that run entirely in your VPC.
Parameter-efficient tuning
Applying LoRA, QLoRA, and weight quantization to train state-of-the-art models on modest GPU clusters at a fraction of standard cost.
100% Local model weights
Running your fine-tuned model on private vLLM or Ollama instances with zero internet egress, ensuring complete IP confidentiality.
Regression benchmark gates
Every model checkpoint evaluated against a golden domain test set to ensure general reasoning isn't lost during specialization.
Six engineering stages, your private weights.
Custom model engineering pairs parameter-efficient fine-tuning (PEFT/QLoRA) with model distillation: compact 8B models can match 70B parameter generalist performance on your specific domain tasks at 1/10th the inference cost.
Dataset curation & synthetic data
Clean, deduplicate, and format your internal documents into optimal prompt-response pairs with synthetic augmentation.
PEFT & QLoRA adaptation
Train lightweight adapter weights on Meta Llama 3.3 or Mistral Large on NVIDIA GPU clusters with rapid convergence.
High-throughput vLLM serving
Deploy models with vLLM PagedAttention and dynamic batching, delivering high token throughput with minimal VRAM overhead.
INT4 & INT8 model compression
Quantize model weights using AWQ and GPTQ to run high-capability 70B models on cost-effective single GPU configurations.
Domain embedding fine-tuning
Train custom embedding spaces tailored to your industry taxonomy for drastically superior semantic search accuracy.
Continuous benchmark auditing
Rigorous evaluation harnesses measuring perplexity, schema accuracy, and safety guardrails across every training epoch.
From open weights to proprietary domain models, hosted 100% in your private cloud.
Own your model weights completely. No subscription rate limits, no third-party data inspection, and zero unexpected deprecation cycles.
Data curation & synthetic pairing
Curate high-quality instruction-tuning pairs with automated de-duplication, quality filtering, and formatting.
Base model benchmark tournament
Evaluate Llama 3.3, Mistral Large, Qwen, and DeepSeek against your domain task metrics to select the optimal foundation.
QLoRA fine-tuning sprint
Train domain adapters using LoRA, flash attention, and learning rate warmups on dedicated GPU clusters.
Evaluation harness & benchmark
Measure perplexity, task accuracy, and safety alignment against commercial APIs on strict held-out test datasets.
Quantization & vLLM deployment
Compile to FP8 / AWQ and deploy high-concurrency vLLM serving clusters in your private cloud or on-prem VPC.
Weight handover & runbooks
Deliver full model weights, training checkpoints, Docker containers, and operational maintenance runbooks.
Data curation & synthetic pairing:Curate high-quality instruction-tuning pairs with automated de-duplication, quality filtering, and formatting.
production vLLM cluster deployment in your private VPC with full IP handover
adapter recalibration and new foundation model checkpoint upgrades
Tuning Outcomes that own your intelligence.
Durable enterprise IP that you own completely. Here are the operational advantages of private fine-tuned model weights.
100% Proprietary IP ownership
Model weights reside entirely on your private servers; no vendor can revoke access, increase prices, or inspect your traffic.
3x Reduction in recurring inference fees
Replacing expensive frontier API tokens with a right-sized, highly tuned 8B–14B model running on fixed-cost private GPUs.
Specialized domain vocabulary accuracy
Reliably understanding niche internal terminology, part codes, and regulatory acronyms that generic models miss.
Sub-100ms local token latency
High-throughput local serving without the network latency and throttling unpredictability of public cloud APIs.
Immunity to provider deprecations
Never worry about third-party API providers deprecating a model version that your software systems rely upon.
Complete compliance isolation
Fulfilling strict defense, healthcare, and financial compliance standards with zero external internet telemetry.
Parameter-efficient fine-tuning & high-throughput serving engines.
We utilize PyTorch, Hugging Face TRL, Unsloth, DeepSpeed, vLLM, and TensorRT-LLM for state-of-the-art training and production serving.
Idea to Market–Ready Product
We turn your idea into a secure, compliant, and test-ready product in weeks, not months.
Inquiry & Scoping
We rapidly decompose requirements, pressure-test commercial viability, and align technical scope before capital is committed.
01 / 06
Ready to build custom AI
that does real work?
Share your operational bottlenecks, dataset needs, or automation goals. An AI solutions architect will provide an architectural roadmap within 24 business hours.