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    Aizon Predict

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    Sold by: Aizon 
    Deployed on AWS
    Aizon Predict is a GxP AI operationalization platform for pharmaceutical manufacturers and CDMOs that brings machine learning models into production in weeks. Deploy models in 12 weeks with full lifecycle governance, real-time predictions, and continuous model monitoring.

    Overview

    Aizon Predict is a GxP AI operationalization platform designed for pharmaceutical manufacturers and CDMOs that need to move machine learning models from proof of concept into production. While most organizations can build models, deploying them in a GxP environment requires governance, validation, and continuous monitoring that generic platforms do not provide. Predict enables data scientists to build, validate, and deploy models directly on contextualized manufacturing data, with full lifecycle control and regulatory alignment.

    Predict provides real-time, batch-linked manufacturing insights from day one. Data scientists can explore process parameters, quality attributes, and batch context without manual data preparation. Models are deployed into live manufacturing workflows to deliver real-time predictions on yield, deviations, and process performance. Continuous monitoring ensures models remain within validated conditions, with controlled lifecycle management and full traceability.

    The platform includes GxP-compliant audit trail, version control, and automated documentation aligned with industry guidance. Predict enables use cases such as yield optimization, deviation reduction, and continued process verification, helping teams improve process performance and decision making.

    Highlights

    • Deploy machine learning models into production manufacturing workflows in 12 weeks with full GxP lifecycle governance from validation to monitoring
    • Deliver real-time predictions on yield, deviations, and process performance using models trained on contextualized batch data from Aizon Unify
    • Ensure model reliability with continuous monitoring, controlled retraining, and full audit trail aligned with regulatory requirements

    Details

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    Deployed on AWS
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    Pricing

    Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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    12-month contract (1)

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    Dimension
    Description
    Cost/12 months
    Application Subscription
    Aizon Predict Subscription Bundle
    $100.00

    AI Insights

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    Dimensions summary

    Aizon Predict uses a single pricing dimension: the Aizon Predict Subscription Bundle, billed as a contract subscription measured in units. You buy this bundle rather than choosing among separate tiers or instance sizes. Pricing scales with the number of subscription units you commit to. The bundle covers the predictive analytics application, which supports yield optimization, deviation reduction, capacity utilization, and predictive maintenance. There are no separate usage add-ons or optional modules in the pricing table. To size the subscription for your operation, work directly with the vendor.

    Top-of-mind questions for buyers

    The pricing table defines the charge as an Application Subscription measured in units, sold as the Aizon Predict Subscription Bundle. The listing does not spell out what one unit maps to in terms of sites, processes, or data volume. To confirm how units are counted for your operation, work directly with the vendor.
    The bundle covers the predictive analytics application. It supports yield optimization, deviation reduction, and capacity utilization. It also applies predictive maintenance to flag equipment risks before failures occur. The application alerts you to product quality risks ahead of time. These capabilities are bundled together rather than sold as separate priced modules.
    The seller describes the solution as supporting an unlimited number of users with virtually no limits on data amount. This suggests cost is driven by the subscription bundle you commit to rather than by user counts or data volume. To confirm how this applies to your contract, work directly with the vendor.
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    Delivery details

    Software as a Service (SaaS)

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