Close the performance gap of your ML systems.

Enterprise-grade platform for teams to continuously optimize AI products, from pre to post-production.

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Domain-specific Applications

Power your highest-value use cases

Retrieval Augmented Generation (RAG)

Ensure that your RAGs generate high-quality, relevant outputs.

Leverage custom RAG evaluation metrics and optimize your RAG pipeline parameters, from embedding models to chunk-size.

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LLM Safety

Optimize security products to better protect against vulnerabilities, including adversarial attacks and hallucination detection tests.

Continuously evaluate effectiveness of your security measures to help your customers stay resilient in real-world deployments.

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Transcription & Summarization

Optimize transcription and summarization tasks to maintain high accuracy, even when dealing with noisy or unstructured data.

Identify the most effective settings for real-time applications through Nomadic’s real-time auto hyperparameter optimization.

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1. Define

Set metrics that matter to your users

Define evaluation metrics to assess expected AI system performance, tailored to the standards of your users.

2. Optimize

Optimize systematically against them

Identify the best model parameter settings or prompt configurations in minutes using NomadicML's state-of-the-art parameter search techniques.

3. MAINTAIN

Deploy and repeat

Continuously tune your AI system and achieve optimality in the face of new production data.

Teams Using NomadicML

Trusted by AI Pioneers

PLATFORM FEATURES

Deploy self-optimizing systems  in minutes, not days

Fast experimentation

Centralized platform designed for teams

Run easy, repeatable experiments to boost your AI performance in the face of new production data.

Simplify experiment workflows across your team with centralized project setup, API key handling, and experiment configuration tools.

Systematic Optimization

Rapid convergence to the best settings

We take you beyond evaluation. Discover and auto-set the best parameters for your ML systems using NomadicML's state-of-the-art auto-hyperparameter optimization library.

Tune a wide range of your system parameters under your budgets, from your prompts to your RAG component's embedding model & chunking sizes.

Custom Evaluation

Standard & LLM-as-a-judge evals out-of-the-box

Set evaluation metrics tailored to assess performance by the standards of your users.

Custom Metrics: Capture nuanced requirements and leverage trustworthy LLM-as-a-judge integrations.

Continuous tuning

Robust & continuous insights

Shadow test and configure the best of candidate parameter configurations on your system performance & cost-efficiency

Justify post-production choices with highly customizable statistical summaries, visualizations, and score distributions.

Faq

Frequently Asked Questions

Can I try the NomadicML Platform before purchasing?

Yes! The Nomadic SDK is open-source & free to use for local experimentation. We also offer a free trial for Nomadic Workspace! With these, you can easily start exploring our features, integrate your models, and leverage the NomadicML to continuously enhance your ML systems.

Would I need to pay for LLM/compute costs to run Nomadic experiments?

NomadicML integrates with both your open & closed-source LLMs. Whether for your local experimentation with the SDK, or for continuous optimization integrations on the Workspace, NomadicML can leverage your most favorable pricing for closed-source LLM tokens & open-source compute costs.

Who can benefit from using Nomadic SDK & Workspaces?

NomadicML's offerings are ideal for all ML engineers, from solo developers to enterprise teams. You can choose between our open-source SDK and our managed-service Workspace to fit exactly your needs. Machine learning practitioners (typically MLEs, MLRs, and Applied Data Scientists) deploying compound AI systems across industry applications can leverage NomadicML's stack to ensure post-production reliability and continuous optimality,

About Us

Community-built by AI innovators

NomadicML is a team of machine learning engineers and researchers who built some of the world's most mission-critical ML systems at Lyft, Snowflake, Google, Microsoft, and Harvard. We've come together as NomadicML to shape the future of continuous learning.