Pruna AI provides an AI optimization engine that enhances machine learning model performance with just two lines of code, utilizing execution kernel and graph optimization techniques. This solution reduces runtime costs and carbon emissions by making AI models faster and more efficient, enabling scalable inference without extensive re-engineering.
Funding
$7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Machine learning (ML) model inference can be computationally expensive, leading to high runtime costs, increased carbon emissions, and challenges in deploying models at scale. Optimizing these models often requires extensive re-engineering and specialized expertise.
Solution
Pruna AI offers an AI optimization engine designed to improve the performance of machine learning models with minimal code changes. By employing execution kernel and graph optimization techniques, Pruna AI reduces the computational resources required for inference. This leads to faster model execution, lower operational costs, and reduced environmental impact. The engine aims to simplify scalable inference, making AI more accessible and sustainable for ML teams.
Target Audience
Pruna AI targets machine learning teams seeking to simplify scalable inference, reduce operational costs, and improve the sustainability of their AI deployments.
Features
- Optimizes models with just two lines of code, minimizing the need for re-engineering.
- Employs execution kernel optimization to improve computational efficiency.
- Utilizes execution graph optimization to streamline model execution.
- Reduces runtime costs associated with machine learning inference.
- Decreases carbon emissions by making AI models more efficient.
- Supports various ML models, including Flux, Stable Diffusion, and Computer Vision models.
- Provides a free token for initial use and experimentation.