WELCOME TO OUMI

Oumi is a platform for building and deploying custom AI models tailored to your specific tasks. It significantly boosts the productivity of AI experts while empowering domain experts with less AI experience to train models effectively. By streamlining the entire lifecycle, from dataset creation and evaluation to training and deployment, Oumi enables you to move from idea to production in hours, not months.

Using natural language prompts with the Oumi Agent, you can create custom models in record time and run complex ML workflows while staying focused on outcomes rather than setup. Check out a few examples of how you can use the Oumi Agent to perform powerful machine learning tasks:

Model distillation

Train a compact fraud detection model using a stronger model’s responses as guidance.

Model evaluation

Evaluate a model on a customer support dataset to uncover common weaknesses and recurring failure patterns in its responses.

Train custom model

Fine-tune a model to automatically classify customer support questions by topic and urgency.

Improve custom model

Analyze specific areas where your model is underperforming and generate targeted datasets for retraining.

Dataset synthesis

Generate 500 question-answer pairs from a product documentation PDF for use in training or evaluation.

Dataset augmentation & expansion

Expand your dataset by generating new samples that match the style and format of your existing examples.

WHY CUSTOM MODELS

Frontier models (e.g., GPT, Claude, Gemini, Qwen, DeepSeek) are built to be general-purpose. However, this power comes with tradeoffs:

They are often not accurate enough on your specific task
They are slow and expensive at scale
You are building on a commodity, versus developing your competitive advantage

Closed models add a set of transparency and control challenges:

Quality can change without warning and impact your product
Terms of use may change, impacting model availability for your use case
Deployment options are constrained, limiting privacy/security control

If AI is core to your product, you should own your future. Control quality, cost, deployment, and iteration speed by building custom models optimized for your tasks.

HOW CUSTOM MODELS ARE TYPICALLY DEVELOPED

Developing a high-quality custom model is typically an iterative loop:

1. Evaluate: Start by benchmarking existing models to establish baseline performance. This requires a reliable test set and robust evaluation methodology.
2. Create training set: Analyze where the baseline model fails, then build or curate training data that targets those gaps.
3. Train: Train a new model using the improved training set and with careful selection of and training strategy.

Then repeat steps 1 to 3 until you meet your quality goals, and finally deploy. In practice, this process can take months and demands significant AI expertise for each model and task, even after assembling and integrating a patchwork of tools to support it.

HOW OUMI DOES IT

Oumi follows the same fundamental development loop but automates all the steps while still giving you full flexibility and control.

Development stage	Traditional custom model development	Oumi
Evaluation	Teams manually create datasets for testing and build out the entire evaluation process for measuring performance.	Automatically synthesizes comprehensive test sets and generates LLM-based evaluation judges from a simple natural language task description.
Training set creation	Engineers manually inspect numerous failure cases to identify where models fail, then manually curate training data to improve quality.	Automatically analyzes model failures and surfaces the failure modes. Then automatically generates targeted training data designed to address failure modes.
Training	Effective model training requires carefully selecting the right model family, size, and hyperparameters.	Automatically suggests the correct model family, size, and hyperparameters based on tradeoffs (e.g., quality vs. efficiency) and task type.
Iteration speed	Iteration cycles can take weeks or months due to manual data creation, experimentation, and infrastructure management.	Automates all steps in the model development loop, dramatically accelerating iteration cycles.
Deployment	Deployment pipelines must typically be built and managed separately from training workflows.	Provides integrated tooling to easily deploy and run trained models in production environments.

By automating evaluation, training set creation, model tuning, and deployment, Oumi significantly accelerates the process of building high-quality custom models.

Bring your own data, or start with none at all. All that’s required is a task description and a target outcome. You can apply your own AI expertise at any level, or rely on Oumi to handle the end-to-end workflow and underlying steps for you. While Oumi automates much of the workflow, you remain in full control. Every step is:

Transparent: you can see exactly what actions will be taken
Reproducible: all actions are recorded as reusable recipes
Flexible: you can review and modify recipes before they are executed

WHO OUMI IS DESIGNED FOR

AI has automated many workflows, but building high-quality machine learning models has remained a painfully manual effort. As the platform that automates AI development itself, Oumi is best for teams that want:

Higher quality on critical tasks
Lower inference cost at scale
Lower latency for latency-sensitive applications
Building models to deploy on devices
Controllable deployment for better privacy and security
Full transparency into AI model development to ensure auditability in regulated industries and beyond
Full control and ownership over AI models when they are critical for business success
Faster time to value, with a clear focus on high-impact outcomes rather than work that doesn’t drive meaningful differentiation

Owning your AI future has never been this easy. What will you build?

Getting started

Oumi workflow

WELCOME TO OUMI

Model distillation

Model evaluation

Train custom model

Improve custom model

Dataset synthesis

Dataset augmentation & expansion

WHY CUSTOM MODELS

HOW CUSTOM MODELS ARE TYPICALLY DEVELOPED

HOW OUMI DOES IT

WHO OUMI IS DESIGNED FOR

Model distillation

Model evaluation

Train custom model

Improve custom model

Dataset synthesis

Dataset augmentation & expansion

​WHY CUSTOM MODELS

​HOW CUSTOM MODELS ARE TYPICALLY DEVELOPED

​HOW OUMI DOES IT

​WHO OUMI IS DESIGNED FOR

WHY CUSTOM MODELS

HOW CUSTOM MODELS ARE TYPICALLY DEVELOPED

HOW OUMI DOES IT

WHO OUMI IS DESIGNED FOR