Now supporting Llama 3.3 and Mistral

Fine-Tune AI Models Without the PhD

Upload your data, pick a task, and let TrainBurt handle the ML wizardry. Production-ready custom models in hours, not weeksโ€”no infrastructure or expertise required.

Start Training Free โ†’ See How It Works
trainburt-cli
$ trainburt train --model llama3 --task classification
๐Ÿ“ค Uploading dataset... 12,847 examples
๐Ÿงช Applying recipe: text-classification-v3
โšก Training started on 4x A100 GPUs

Epoch 1/3 โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ 100%
Epoch 2/3 โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ 100%
Epoch 3/3 โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ 100%

โœ“ Training complete in 47 minutes
โœ“ Accuracy: 94.2% (โ†‘12% vs base model)
โœ“ Deployed to: api.trainburt.com/v1/model-8f3k
$

Trusted by developers at

โ—† Ramp
โ—† Notion
โ—† Linear
โ—† Vercel
โ—† Stripe

Fine-tuning is hard.
It doesn't have to be.

Generic AI models get you 80% of the way there. But that last 20%โ€”the part that makes your product actually workโ€”requires custom training on your data.

  • โฑ๏ธ

    Weeks of setup before you write a line of training code

    Infrastructure provisioning, data pipelines, GPU configuration...

  • ๐ŸŽ“

    ML expertise most teams don't have (or can't afford)

    Senior ML engineers cost $400K+. Good luck competing for that talent.

  • ๐ŸŽฐ

    Hyperparameter guesswork that burns through budget

    Learning rate? Batch size? Epochs? Hope you like expensive experiments.

๐Ÿ“Š
Traditional Fine-Tuning
The painful reality
Week 1-2
Set up cloud infrastructure & GPU clusters
Week 3-4
Build data pipelines & preprocessing
Week 5-6
Hyperparameter tuning experiments
Week 7-8
Training, debugging, more training
Week 9+
Deploy & hope nothing breaks

From data to deployed model in an afternoon

TrainBurt handles the infrastructure, hyperparameters, and deployment. You just bring your data and pick a task.

1
๐Ÿ“ค

Upload Your Data

Drop in a CSV or JSON, or connect directly to your database. TrainBurt auto-validates, cleans, and formats everything for training.

โšก ~5 minutes
2
๐Ÿงช

Pick a Recipe

Choose from battle-tested training recipes for classification, extraction, summarization, Q&A, and more. Each encodes optimal settings from thousands of runs.

โšก ~2 minutes
3
๐Ÿš€

Train & Deploy

Watch training in real-time, test in the playground, and deploy to a scalable API endpoint with a single click. That's it.

โšก ~1-2 hours

Everything you need, nothing you don't

Built by engineers who were tired of wrestling with ML infrastructure when they just wanted to ship features.

๐Ÿ“ค

One-Click Data Ingestion

Upload CSVs, JSONs, or connect to your database. Smart sampling suggests optimal dataset sizes. No data engineering required.

๐Ÿงช

Task-Specific Recipes

Pre-built training configurations with optimized hyperparameters. Better results without the guessworkโ€”our recipes encode what actually works.

๐Ÿ“Š

Live Training Dashboard

Real-time loss curves, evaluation metrics, and completion estimates. Full visibility into what's happeningโ€”no black box anxiety.

๐ŸŽฎ

Interactive Playground

Test your model instantly in a chat interface. Compare outputs against base models side-by-side. Share links with teammates.

๐Ÿš€

One-Click Deployment

Deploy to a scalable API endpoint instantly. Auto-scaling handles traffic spikes. Usage-based pricing means you only pay for what you use.

๐Ÿ”„

Version Control

Every training run is versioned. Compare models, A/B test in production, roll back instantly if needed. Experiment confidently.

Developers are shipping 10x faster

Join thousands of developers who've ditched the ML infrastructure pain and started building.

"We evaluated building an ML pipeline in-house. 3 engineers, 4 months, $200K+ fully loaded. TrainBurt got us there in a weekend for a few hundred bucks. The math was obvious."

JC

James Chen

CTO, Finch (YC W22)

"I'm not an ML engineer, but I trained a model that classifies support tickets with 94% accuracy. Felt like I had superpowers. Our support team is thrilled."

SM

Sarah Miller

Solo Developer

"Our ML team had a 6-week backlog. I used TrainBurt to fine-tune a model for our new feature and had it in production before our next sprint planning. Game changer."

MK

Mike Kumar

Product Manager, Lattice

10x
Faster than building in-house
94%
Avg. accuracy on custom tasks
$50
Average cost per trained model
2,400+
Developers building with TrainBurt

Simple, usage-based pricing

Start free, scale as you grow. No hidden fees, no GPU cost surprises.

Free
Perfect for experimentation
$0 / month
  • 10 training hours/month
  • 1 hosted model
  • Community support
  • All base models included
  • Playground access
Get Started
Pro
For serious builders
$99 / month + usage
  • Unlimited training hours
  • 5 hosted models
  • Priority support
  • Advanced recipes
  • API access
  • Version history
Start Free Trial
Team
For growing teams
$399 / month + usage
  • Everything in Pro
  • Unlimited hosted models
  • Team collaboration
  • SSO & audit logs
  • Dedicated support
  • SLA guarantee
Contact Sales

Frequently asked questions

Everything you need to know about TrainBurt.

We currently support Llama 3.3 (8B and 70B), Mistral 7B, and Mistral Mixtral 8x7B. We're constantly adding new modelsโ€”Gemma and Phi are coming soon. All models are available on all plans.
Those tools are built for ML engineers. TrainBurt is built for developers. No infrastructure setup, no hyperparameter tuning, no DevOps. Upload data, pick a recipe, get a deployed model. What takes weeks on SageMaker takes hours on TrainBurt.
Yes. Your data never leaves your isolated training environment. We're SOC 2 Type II certified. All data is encrypted at rest and in transit. Models are deployed to single-tenant endpoints. For enterprise customers, we offer VPC deployment and can run entirely in your cloud account.
We have optimized recipes for text classification, entity extraction, summarization, question answering, and custom instruction-following. If you have a different task in mind, reach outโ€”we're happy to help configure a custom recipe.
They're focused on their own models and enterprise customers. We're model-agnostic and developer-obsessed. We support open-source models that give you flexibility, portability, and cost savings that proprietary providers won't offer. Plus, our training recipes get better with every run across all models.
The average training run costs $30-80 depending on dataset size and model. Our optimization layer reduces compute costs by 60% vs. raw cloud pricing. Hosting starts at $0.10 per 1K requests. Most customers spend $50-200/month total.

Your data. Your model. Production-ready today.

Join 2,400+ developers who've stopped waiting on ML teams and started shipping custom AI features.

Start Training Free โ†’ Schedule a Demo