Rapidly build, train, test, & deploy
Fused Multimodal Foundational Models
No Black Boxes
We all hate “black boxes!” and open source models aren’t tailored for e-commerce. That’s why Vody builds tools for data scientists to upload data, select model configuration, and receive back a trained and optimized model to incorporate into their existing ML pipeline– using only three easy API calls. Build with tools made for you.
Integrates with your current stack
VodyMM injects the power of multimodal representations into existing models for e-commerce applications like recommendation/search/product matching. We use a set of curated and transparent routines, specific to e-commerce, that allows you to easily adapt the latest research and existing models for your business.
Introducing Vody Multi-modal (VodyMM): fuse all your data- Images, Text, Video, Audio, Clickstream
Optimized Models, Minimal Effort
Using cutting-edge research, Vody makes the latest optimization techniques available as a simple API call from your existing model development pipelines. We offer platform-agnostic, fixed-cost, server-less solutions to accelerate model development and supercharge performance. Our cutting-edge domain adaptation and multimodal representation routines enable clients to better understand and utilize their unstructured data and improve their ML pipeline’s performance and adaptability.
Decrease Time to Value
Vody’s AI automates optimization, eliminating month of engineering effort, producing results in hours.
Insights from Your Data
Vody offers products to enable rapid adoption of new models to use your data in new ways.
Integrates into Existing ML
A simple API call optimizes your models based on your data and your tasks.
Optimized recommendation models have demonstrated a 40% uplift in sales conversion for online retailers.
Remain in Control
Vody’s optimization APIs offer advanced ML engineers parameters to tailor the optimization process.
Businesses optimizing their ML see a 200% increase in ML-attributed revenue growth vs. pure adoption.
For Teams that Build ML
MultiModal Learning enables your ML models to understand and work effectively with images, text, and structured data.
Domain Adaptation adapts general language models to the context and domain-specific needs of your business.