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How it works

Five steps from CSV to a callable, evaluated fine-tune.

We move quickly but never skip the parts that decide whether the model actually ships.

Process
01

Pick a plan that matches your dataset

Smaller plans are perfect for proof-of-concept. Studio and Enterprise plans cover production datasets with multi-epoch training and richer evaluation.

  • Five plans, one-time pricing
  • No subscription
  • 30-day money-back guarantee
02

Tell us what the model should do

After payment you fill out a short brief: use case, base model preference, and dataset upload. The brief drops into your order page where we can keep talking.

  • CSV / JSONL upload
  • Choice of GPT, Claude, Llama, Mistral
  • Built-in chat with our team
03

We profile, clean, and shape the data

We run dedup, PII scrubbing, schema validation, and split into train / validation / held-out sets. You get a transparent data report before training.

  • Schema profiling
  • Near-duplicate clustering
  • Train / val / held-out splits
04

Fine-tune and evaluate against the baseline

Training runs with a published config and loss curves. Then we evaluate on the held-out set with task-appropriate metrics (BLEU, ROUGE, F1, faithfulness).

  • Reproducible training config
  • LoRA / QLoRA on supported models
  • Side-by-side baseline comparison
05

Deploy and deliver

A REST endpoint goes live with auth and rate limits. You receive the PDF report, prompt templates, and a renewal / migration plan.

  • Authenticated REST endpoint
  • PDF report + prompt templates
  • Renewal or weight export at term-end

Start a project in five minutes.

Pick a plan, pay once, and fill out the project brief on your order page.