invoice_processing · logistics · workflow
Uber advances invoice document processing using GenAI with the TextSense platform
Uber's invoice processing relied on manual data entry and RPA that could not scale to diverse invoice formats, invoices arriving in over 25 languages, and high volumes, leading to high average handling time, errors, and rising operational costs.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Invoice submission trigger
Suppliers submit invoices via a self-service platform or by email.
Tools used
TextSenseVision GatewayOCRNLPGPT-4CadenceRPALlama 2Flan T5
Outcome
The GenAI-powered TextSense system achieved a 2x reduction in manual invoicing, an overall accuracy rate of 90%, a 70% reduction in average handling time, and a 25-30% cost saving compared to the manual process.
What failed first
Existing Rule-Based Systems and RPA could not adapt to new invoice formats without manual rule-setting, failed to scale as Uber onboarded new suppliers and document formats, and required continual maintenance and manual error correction.
Results
Time saved70%
Volume2x reduction
Cost replaced25-30%
Grounding & classification
Source type: technical build writeup
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computer visiondata extractiondocument aiidpocremailinvoicepurchase orderfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedlogisticssoftwareaccuracy improvementautomation ratecost reductionemployee productivitytime savedtechnical build writeupaccounts payableinvoice processingprocurementdocument to recordextract classify routehuman review queue