Services

Fine-Tuning

When prompting isn't enough.

Overview

Your Model, Your Data

General-purpose models are impressive, but they weren't trained on your domain. Fine-tuning closes the gap — teaching models your terminology, your formats, and your edge cases so they perform like specialists, not generalists.

01

Data Preparation & Curation

We clean, format, and structure your training data into high-quality examples the model can learn from.

02

Model Selection & Training

We pick the right base model for your task and run fine-tuning with proper hyperparameter optimization.

03

Evaluation & Benchmarking

Side-by-side comparisons against the base model on your real-world test cases to prove the improvement.

04

Deployment & Serving

Optimized inference setup — hosted or self-hosted — with latency and cost targets that make sense for production.

Process

How It Works

Fine-tuning is only worth it when the data and the task are right. We make sure both are before you spend a dollar on training.

01

Feasibility & Data Review

We assess whether fine-tuning is the right approach and audit your data for quality, volume, and coverage gaps.

02

Training & Evaluation

Iterative training runs with systematic evals. We compare against baseline until the fine-tuned model clearly wins.

03

Ship & Monitor

Deploy the model with monitoring for drift and degradation. We set up retraining pipelines for when your data evolves.

AI Assistant

Ask Us Anything

Have questions about this service? Our AI assistant can help.

The Shift
AlphaCorp AI
0:000:00