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Computer Vision AI
Deriving actionable insights from digital images and videos can make computer vision (CV) a pivotal strategy for your organization. But until you can make purposeful recommendations based on the information you gain from CV, and take action at scale, cost-effectively, and reliably, you can’t make it valuable.
Forecasting (Batch)
There are many examples of forecasting, ranging from estimating future product production needs in consumer goods, to the potential effectiveness of an advertising campaign. What’s true in many of these cases is that the number of forecasting “jobs” that need to run on a regular basis could be 100s to 10’s of thousands because of the need to customize the models based on location, product, advertiser, etc. Wallaroo enables deploying a large number of custom models, generating the forecast quickly and efficiently, and monitoring the reliability of each model.
CyberSecurity (Microbatch)
A large enterprise can typically generate 100M to billions of network events or other internal system events every day, and many of the most effective models that look for security anomalies can be computationally expensive deep learning models. In addition, such models need frequent retraining and redeployment to keep working the most effectively. Wallaroo makes it easy to update and redeploy models in seconds, to run the analysis on the data using up to 80% less infrastructure than alternatives, and to generate alerts when either the input data or the predictions of the model have drifted away from expected behavior.
Fraud (Real-time)
A common example of fraud is in credit card transactions. The prediction of fraud needs to be low-latency (real-time) and models need frequent retraining and redeployment. In addition, the final determination of whether a particular transaction is fraudulent can involve an ensemble of many models working together, where each model is trained to look for a different type of fraud signal. Wallaroo makes it easy to deploy ensembles of models, can run these models highly efficiently within it’s Rust-based server without much infrastructure or data copying overhead, and can alert you if the models lose their efficacy over time.
Generative AI (Real-time)
Generative AI, such as Large Language Models (LLMs) can help enterprises create better products as well as to operate more efficiently. However, they also are complex models to deploy, are significantly more expensive to support in production than other forms of machine learning or a standard search query, and can generate unexpected outputs. In addition to the Wallaroo platform that helps in all these areas, engagement with us provides you with a trusted partner that ensures best practices for efficient deployment and serving, as well as troubleshooting potentially risky model behaviors.

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Computer Vision (AI) Run even complex models in constrained environments, with hundreds or thousands of endpoints