PAXAFE PDF Parser

Passive Lane Risk intakes passive PDF report data (device-agnostically) and converts picture data into tabular, reportable data. This computer vision algorithm minimizes quality workflow, allowing for a passive data repository, automating product release and providing insights across lanes that utilize passive data loggers.

At this stage in your IoT journey, your network utilizes passive temperature data loggers (e.g. TempTale, Libero) for product release and quality monitoring. You may be considering real-time IoT, but don’t have any devices validated or lanes live yet.

Common problems at this stage include:

•Product release is a manual process (accept, reject, quarantine), burdening quality resources

•Regional SOPs around retaining passive PDFs and logger data

•If you’re paying for raw table data, you’re paying by region, and have to pay each logger company (expensive!)

•No central passive data repository & limited understanding of passive lane performance/risks at scale

Parser centralizes single file or bulk upload (up to 500 per upload) PDFs, and becomes the central source of truth repository for passive data! This solution provides actionable insights post shipment by extracting the collected data from passive data loggers to store and automate acceptance of Product Shipments. The process for extracting, analyzing and making quality temperature decisions using passive data loggers is manual, laborious and expensive. From manual calculations and Quality Management System (QMS) entry, to pricey middleware sensor platforms to 'decode' your data, to not having scalable insights -- your passive lanes aren't telling you much about your supply chain where PDF Parser is able to.

PAXAFE PDF Parser offers the following benefits for passive data logger-enabled supply chain risk monitoring:

• Digitize and Automate Quality Decisions – Use programmatic cross-checking against proven temperature ranges

• Reduce Human Error – Allow machines to do menial, error-prone and time-consuming tasks such as graphical interpretation or data input

• Bolster Intelligence – Extract value from passive data that is currently being thrown away