Private beta access
Fine-tune AI models cheaper and much faster.
RailCompute helps teams fine-tune models faster and cheaper by automating the ML pipeline from data prep to evals, with no human in the loop.
About RailCompute
We are building the fine-tuning layer between team intent and working AI models.
RailCompute is for teams that know what they want a model to do, but do not want to spend time manually managing datasets, training scripts, infrastructure, metrics, packaging, and deployment.
Private beta
Opening access with design partners.
We are refining RailCompute with a focused group of teams before launch. If you want faster, cheaper fine-tuning without managing the ML pipeline, book a design partner call.
Be a design partner
Demo
See how we trained a PCB defect detector on RailCompute.
Open the full automated training run, inspect the model outputs, and watch the training video.
View PCB demoHow it works
Team intent in.
Fine-tuned model out.
Describe
Describe what the model should learn and answer a few focused questions.
Approve
Review the training plan before compute starts.
Train
The agent prepares data, picks the model, runs training, and monitors progress.
Receive
Get the trained model, eval summary, and a usage guide written for teams.
Data preparation
Cleans, formats, labels, validates, and uploads the dataset before training begins.
Training decisions
Selects model family, hyperparameters, eval split, target metric, and compute.
Live reporting
Tracks loss, ETA, failures, checkpoints, and final quality in language humans understand.
Contact us
Want early access or a product walkthrough?
Join the waitlist for private beta updates, or reach the team directly for partnerships, pilot users, and fine-tuning workflows.