Zapata AI’s Industrial
Generative AI Solutions
Make more informed decisions by enriching your business analytics with new, intelligently-generated data, including for variables that are otherwise unmeasurable.
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Prevent bias by balancing training datasets with new, realistic data that has been intelligently-generated to follow the statistical patterns of real data.
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Enhance your analytics by inferring data for unmeasurable variables based on their correlations with variables that can be measured directly.
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Reduce waste and downtime by generating more accurate demand forecasts to optimize your supply chain scheduling.
Cut compute costs and time-to-value by compressing large language models (LLMs), while tailoring them to your business by securely training on your own proprietary data and IP.
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Boost customer retention with more flexible and personalizable chatbots, powered by custom LLMs trained on your corpus of documentation and customer data.
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Speed up the regulatory approval process by using LLMs trained on IP and proprietary data to complete first drafts of regulatory documents.
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Learn from new research faster by using LLMs to search journals for relevant research and summarize their findings.
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Avoid data leaks by training your models in your own environment. Our solution is flexible enough to work with secure data.
Do more with LLMs by adding subroutines for accurate calculations, plot creation, database retrieval and more.
Our proprietary model compression techniques can reduce the number of GPUs and time required to train and run your generative AI applications.
We can help you compress your generative AI models so they can run on the edge — without connectivity to the cloud.
Mathematical generative models can infer the values of variables that were previously unmeasurable to enrich analytics and simulations.
Find the best configuration for your problem by comparing different techniques across libraries and hardware — with scalable GPU access.
Generative AI isn’t just for text and images. We’re doing advanced numerical analytics that are helping us make decisions; we had to build something new that works within our constraints, securely. The results with Zapata’s Generative AI have been incredible. What we’ve found is there is hardly any difference between the Zapata predicted data and actual performance data.
Bryan Herta
Race Strategist, Andretti Autosport
As you might imagine, optimizing our production schedule is an incredibly complex and unique challenge. There are a wide range of possible configurations and a high number of constraints. Working with Zapata and CQE, we were able to prove [Zapata’s technology] outperforms other techniques in production planning.
Marcin Ziolkowski
Emerging Technologies Manager, BMW Group
