Chat with us!We developed a custom, domain-tuned large language model for a client with strict data-privacy needs — delivering expert-level performance on their special...
We get a model that speaks our language, never sends data outside, and we control every version.
VP of Engineering
We developed a custom, domain-tuned large language model for a client with strict data-privacy needs — delivering expert-level performance on their specialized tasks while keeping all data inside their own infrastructure.
| Project Detail | Information |
|---|---|
| Project Type | Web |
| Industry | Technology |
| Technologies | Open-weight base LLM, LoRA / PEFT, vLLM, PyTorch, Kubernetes, Weights & Biases |
| Delivery Partner | mTouch Labs |
| Primary Outcome | The custom model outperformed general APIs on the client's tasks while keeping data fully private and costs predictable. |
General-purpose APIs could not match the client's domain terminology and could not be used at all for their most sensitive data, which had to stay on-premise for compliance.
We curated a domain dataset, fine-tuned an open-weight base model, and deployed it privately with an inference stack the client fully controls, plus an evaluation harness to prove quality.
The result is a private, domain-expert LLM running in the client's environment, served through an internal API with monitoring and a clear retraining path.
Foundation for fine-tuning
Efficient domain fine-tuning
High-throughput private inference
Training and evaluation
Scalable private deployment
Experiment tracking and evals
Assembled and cleaned a high-quality domain dataset.
Tuned the base model efficiently with PEFT methods.
Built task-specific evals to validate quality and safety.
Deployed the inference stack inside client infrastructure.
Set up monitoring and a documented retraining path.
The custom model outperformed general APIs on the client's tasks while keeping data fully private and costs predictable.
A custom, privately deployed LLM gave the client domain-expert AI on their own terms — accurate, compliant, controllable, and cost-effective at scale.
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View case studyWhat businesses ask us most often about this project and how we built it.
It is building or fine-tuning a large language model on your domain data and deploying it under your control, so it understands your terminology and meets your privacy needs.
Yes. We deploy privately — on-premise or in your VPC — so sensitive data never leaves your environment.
A domain-tuned, private model can outperform general APIs on specialized tasks, keep data in-house for compliance, and offer more predictable costs at scale.
We build a task-specific evaluation harness to measure quality and safety against your real requirements before launch.
Yes. We provide a documented retraining and versioning path so the model evolves with your needs.
mTouch Labs combines AI-powered development with deep industry expertise to deliver solutions faster.
