Train, Fine-Tune, and Deploy AI Models at Scale

Supervised fine-tuning, reinforcement learning, benchmarking, multi-tower pipelines, and GPU deployment — all in one platform.

Treni AI platform screenshot

Pipeline builder

Build multi-tower model pipelines visually

Combine multiple models in the same pipeline — time series analysis, transformer classifiers, ensemble architectures — all connected in a visual editor.

Multi-tower architecture
Chain specialized models together: feed time series data through an analyzer, then route outputs to a transformer for classification or generation.
Visual pipeline editor
Drag and drop models, configure data flows, and set up branching logic without writing orchestration code.
Unified data routing
Automatically handle data format conversion between models. Connect any output to any input across your pipeline.
Build multi-tower model pipelines visually

From data to deployment — one platform.

Why Treni AI

Most ML teams juggle a dozen disconnected tools: one for data prep, another for training, a third for evaluation, and yet another for deployment. Treni AI replaces that fragmented stack with a unified platform where every step — from dataset curation to production serving — lives in one place.

We support both commercial models (OpenAI, Anthropic, Google) and open-source models (Llama, Mistral, Phi, Qwen) on the same platform. Run benchmarks across all of them, fine-tune the open-source ones, and deploy whichever performs best — without switching tools.

Built-in GPU management means you never have to SSH into machines, write SLURM scripts, or negotiate with cloud providers. Select your hardware tier, click deploy, and Treni AI handles provisioning, scaling, health checks, and cost optimization automatically.

The visual pipeline builder lets you design multi-tower architectures by connecting model blocks in a drag-and-drop canvas. Chain a time series forecaster into a transformer classifier, add an ensemble layer, and deploy the entire graph as a single endpoint.

Why Treni AI

Capabilities

Everything you need to train and deploy

Supervised Fine-Tuning

Fine-tune LLMs and open-source models with your own data. Support for LoRA, QLoRA, and full parameter training across dozens of architectures.

Supervised Fine-Tuning

Reinforcement Learning

RLHF and DPO alignment for production-ready models. Build reward models, run preference optimization, and ship aligned outputs.

Reinforcement Learning

Multi-Model Benchmarking

Compare commercial and open-source models side by side. Evaluate accuracy, latency, cost, and quality across standardized benchmarks.

Multi-Model Benchmarking

Multi-Tower Pipelines

Chain models together: time series + transformers, ensemble architectures. Build complex inference graphs with a visual pipeline editor.

Multi-Tower Pipelines

GPU Deployment

Deploy and scale models on GPUs with one click. From A100s to H100s, autoscale based on traffic and optimize for cost or latency.

GPU Deployment

No-Code Training

Launch fine-tuning jobs without writing training scripts. Configure everything through an intuitive UI.

Scale to Any GPU

From A100s to H100s, deploy on the hardware you need. Automatic provisioning and cluster management.

Fully Configurable

Customize hyperparameters, data splits, and model architectures. Full control over every aspect of your training pipeline.

Developer-first

Integrate with a few lines of code

JavaScript

// Fine-tune a model with Treni AI
const job = await treni.fineTune({
  model: 'llama-3-70b',
  dataset: 'my-dataset',
  method: 'sft'
});

Python

# Launch a training pipeline
from treni import Pipeline

pipeline = Pipeline()
pipeline.add_model('time-series-analyzer')
pipeline.add_model('transformer-classifier')
pipeline.run(dataset='my-data', gpus=4)

Trusted by ML teams

What our users say

Treni AI cut our fine-tuning iteration time from days to hours. The multi-tower pipeline feature is a game-changer for our ensemble models.

Dr. Sarah Chen

Dr. Sarah Chen

ML Research Lead

We benchmark across 15 models monthly. Treni AI's unified platform replaced our entire custom evaluation infrastructure.

Marcus Rodriguez

Marcus Rodriguez

Head of AI

Stop configuring. Start training.

While other platforms make you manage infrastructure, Treni AI lets you focus on what matters: your models and data. Launch your first training job in minutes.