Modern Cloud AI StackRun, scale, and collaborate on AI and Data workloads on a unified compute platform.
Teams choosing to build with TractoAI
AI frontier is shifting towards data. Is your stack ready?General purpose AI models are quickly becoming commodities. The value moves towards proprietary data and custom models. Today’s tooling isn’t built for data-centric, personalized AI.
Introducing TractoAI
Run entire ML workflow—data prep, training, and inference—in a single shared environment
Handle all types of data—images, video, audio, text, and tabular—without switching tools
Cut AI and data infrastructure costs vs. hyperscalers, with no performance compromise
Access a large pool of CPUs and GPUs. Automatically scale resources up or down
No cluster setup. Run your jobs with serverless execution and usage-based pricing
Run entire ML workflow—data prep, training, and inference—in a single shared environmentHandle all types of data—images, video, audio, text, and tabular—without switching toolsCut AI and data infrastructure costs vs. hyperscalers, with no performance compromiseAccess a large pool of CPUs and GPUs. Automatically scale resources up or downNo cluster setup. Run your jobs with serverless execution and usage-based pricingDedicated cluster for production workloadsConnect data and build custom AI workflows using built-in open source frameworks and scalable compute runtime. Interactive notebooks or SDKs, your choice.
Fine-tune models on your data
Fine tune or distill popular open source models like DeepSeek, Llama or Flux. Experiment and tweak models at scale with dynamic compute.
Train your own AI models
Build custom models with Tracto distributed training launcher. Support for all major libraries like PyTorch, Hugging Face, Nanogpt. Scale up to hundreds of GPUs in seconds, store checkpoints, and monitor results on W&B.
LLM batch inference
Run distributed batch inference jobs to increase throughput and utilize both CPUs and GPUs. Built-in support for popular inference libraries vllm, sglang.
Multi modal data processing
Process structured and unstructured data including images, video, and audio. Synthetically generate data at scale for reinforcement learning.
Work with your favorite tools and save on integration work
Products and interfaces
Notebook
Workflows
Docker registry
Web Interface
SDK
Computations and data
SQL
Ray
Files
Structured metadata
MapReduce
AI Models
Dataset tables
Resource layer
Serverless GPU and CPU compute
Cypress distributed filesystem
Underlying infrastructure
Compute cloud
Bare metal racks
Scale individual workloads and ML platforms with framework friendly tools
Data scientists and ML researchers• Distribute AI workloads across multiple nodes w/o infra expertise• Leverage ML ecosystem with extensible integrations
Data & ML Platforms builders• Compute abstractions for creating scalable data & ML platforms• APIs to integrate with data and ML tools
MLOps & DevOps teams• Automatic job orchestration and scheduling• Autoscaling - scale to 100s of GPUs/CPUs
Ready for AI workloadsTracto automates deployment and scaling for tasks like ML training, exploratory analysis, and big data processing enabling teams to iterate faster
Solution libraryHit the ground running with pre-built templates and unparalleled expert guidance.
Developer friendlySupport for most popular open source libraries and data formats.
Future proofScalable and efficient compute and storage for training workloads of any size.
TractoAI reliability and speed allowed us to pre-train 1B text LLM on 15TB of unstructured data. Integrating data preprocessing and training in one platform saved our ML team hours an kept us on schedule.Pierre-Carl Langlais, Co-founder, Pleias.fr
As a startup building Gen AI video app, speed and flexibility is critical for us. TractoAI handles fine tuning of text to image models for us and easily integrates into our app backend.Sergey Vasilinets, AI/ML Lead, Unrealme.ai
Tracto's platform has dramatically simplified our training infrastructure setup. What would typically require extensive engineering effort becomes remarkably straightforward, allowing us to move faster and focus on pushing the boundaries of AI reasoning.Nathan Lile, Founder & CEO, Synthlabs.ai
Our collaboration with the TractoAI and Nebius Life Science team gave us a clear edge. Our pilot models already perform well in predicting dynamic drug-target interactions. TractoAI data infrastructure allowed us to develop continuous data feedback loops to iterate on model performance.Slava N., CEO, SieveStackProve research and bootstrap AI roadmap with TractoAI serverless