Continuously optimize your AI in production and adapt your ML in real time to unseen data
NomadicML's SDK and Workspace auto-optimizes the hyperparameters of your entire AI system, from your LLM(s) to RAGs, and your Guardrails & prompt-tuners. The Nomadic Platform enables auto-HPO of your ML system in both development (against your local test datasets & regression tests) and in production (against your real-time data of your users), which enables robustness of AI systems with unseen data.
NomadicML Key Features
Fast experimentation: Centralized platform designed for teams
Systematic Optimization: Rapid convergence to the best settings
Custom Evaluation: Standard & LLM-as-a-judge evals out of the box
Continuous tuning: Robust & continuous insights
NomadicML Use Cases
Personalization of AI systems; implement once, optimize for different user groups & use cases
Cost-efficiency and performance maximization of compound AI components
Rapid experimentation & prototyping of ML systems: go from MVP to prod in a matter of minutes
Pros
Auto-optimizes hyperparameters of the entire AI system.
Supports optimization for various components like LLMs, RAGs, Guardrails, and prompt-tuners.
Facilitates both development and production optimization, enhancing system robustness with unseen data.
Continuous adaptation possible due to real-time data integration.
Cons
Dependence on SDK and Workspace could pose limitations for highly customized systems.
Real-time optimization may incur resource overhead or increase computational costs.
May require a learning curve for users unfamiliar with hyperparameter optimization processes.
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