AI Fine Tuning Service That Makes Generic Models Yours

It is an engagement that adapts a pre-trained foundation model to your business using your own examples. The work runs from use-case scoping and data preparation through training, evaluation, and deployment. AutoArmy advises and oversees while vetted specialists execute the runs. The result is a model that knows your domain, holds your tone, and benchmarks against the stock version.

Prompt engineering instructs a stock model at request time, and retrieval-augmented generation feeds it your documents as context. Fine tuning changes the model’s weights, so behavior, tone, and format stick without long prompts. The fine-tuning vs RAG choice is rarely either-or: many production systems tune for behavior and retrieve for facts. Scoping shows which mix fits your case.

Most engagements start with a few hundred to a few thousand quality examples: resolved tickets, approved documents, labeled records, or transcripts. Quality beats volume, since one wrong example teaches the model the wrong lesson. The data preparation phase cleans, labels, and augments what you have, and the scoping call tells you whether your current set clears the bar.

A scoped pilot typically runs four to eight weeks from data audit to a benchmarked model, with parameter-efficient methods like LoRA at the short end. Production deployment with integration, guardrails, and monitoring adds several weeks more. Retraining cycles after launch run shorter, since pipelines and evaluation sets already exist. Timelines firm up once your data gets a look.

Parameter-efficient tuning projects often land in the low-to-mid five figures, while full fine-tuning of larger models with deep integration runs higher. Data readiness drives most of the spread, because clean examples cut both training runs and rework. Each proposal pairs the cost with a measured target, accuracy lift or cost per call, so you buy an outcome rather than GPU hours.

Yes, when the engagement is built for it. Your data moves under NDA, with SOC 2 controls, encryption in transit and at rest, and access scoped to the training team. PII gets scrubbed during preparation, and sector rules like HIPAA fold into the plan where they apply. You keep ownership of the data, the adapters, and the resulting model.