The smarter way to automate content management with ML APIs.
Zorroa simplifies machine learning (ML) API integration through a GUI-based workflow, so that you can save your coding chops for building real-world applications.
The challenge with applied ML.
Machine learning is hard, even when using pre-trained models. 87% of data science projects fail because AI/ML projects are unpredictable by nature and they don't support experimentation and testing in the way of software engineering.
The Zorroa solution.
Run ML APIs from GCP, AWS, and Azure on your data to start automating media asset tagging, auditing, and classification tasks in minutes. Then experiment, iterate, and evaluate—without code or data science expertise.
A no-code path to ML-driven content management.
You can manage everything from data ingest to ML analysis, job queue management and metadata review in our fully designed GUI.Then integrate the resulting metadata into your app using industry standard APIs.
The power of Zorroa’s multi-provider ML integration.
Our platform is as extensive as the ML API ecosystem. Access ML models built and trained by the best-in-class data scientists. Experiment with and layer in features from an unlimited number of models with just a few clicks.
Types of ML Models We Support
Optical Character Recognition
Providers We Use
Get richer metadata faster, with less development.
Choose your data source, run the APIs, then view the ML-generated image labels in our UI without code.
You also get goodies like model confidence, pretty human-readable results, and even an open-sourced search app you can use to power your results search.
Abstract away account setup, API documentation, billing, and integration requirements.
Data Prep &
Ingestion at Scale
Transcode raw images, videos, and PDF docs to vendor-ready formats and batch upload.
Multi-Vendor API Access
Layer in features from the latest computer vision APIs from multiple providers, compare results.
& Faceted Search
View the results, run conditional searches, or filter based on model confidence.
Custom Label Support
Custom train a model to detect labels that are not supported by the pre-trained APIs.
Integrate ML-powered metadata into any app with Python and REST APIs.
Kick off machine learning experimentation in under an hour—without code.
Point and click workflow to run ML
No data prep required
Accelerate time to proof-of-concept
Access top ML APIs from multiple vendors without lock-in.
ML features from a broad suite of APIs
Ability to compare vendor ML
No vendor setup, API documentations, or account management required
Scale ML projects without the development hours.
ML at a fraction of the cost of DIY integration
Agility to keep up with the latest ML
Easy integration into software development