How AI Builder and Dynamics 365 Invoice Capture Streamline F&O and Project Operations
How AI Builder and Dynamics 365 Invoice Capture Streamline F&O and Project Operations Manual Accounts Payable (AP) processing remains one of the most resource-intensive operational bottlenecks for mid-market and enterprise organizations. From lost documents and manual data entry errors to slow invoice routing across project managers, traditional AP workflows lag behind modern digital transformation goals. Microsoft addresses this challenge head-on with Dynamics 365 Invoice Capture—a solution native to the Power Platform ecosystem that bridges AI Builder with Dynamics 365 Finance & Operations (F&O) and Dynamics 365 Project Operations. Here is a practical look at how the technology works under the hood and how to set up an automated, intelligent AP pipeline across your core enterprise platforms. 1. The Core Engine: How AI Builder Scans and Extracts Data At the heart of Invoice Capture is AI Builder Document Processing (powered by Azure Applied AI Services). Unlike legacy Optical Character Recognition (OCR) systems that depend on rigid, manual templates for every single vendor layout, AI Builder uses deep-learning models trained on millions of business documents out of the box. [Inbound Email / PDF] │ ▼ [AI Builder Engine] ──► Extracts Layout, Headers & Lines │ ▼ [Confidence Scoring] ──► High Confidence? ──► Touchless Transfer to D365 │ └─────────────► Low Confidence? ──► Side-by-Side Review Queue Key Capabilities of the Scanning Engine Layout-Agnostic Extraction: Automatically identifies essential fields—including Vendor Name, Invoice ID, Purchase Order (PO) numbers, line-item descriptions, line totals, and tax—regardless of where they sit on the page. Dynamic Confidence Scoring: Every extracted field receives a confidence score ($0\text{--}100\%$). You can set operational thresholds (e.g., auto-process anything above $85\%$, flag lower scores for human review). Continuous Learning Loops: When an AP clerk corrects a misread value in the validation interface, the system records the visual-to-field relationship in Dataverse. Over time, the model automatically learns non-standard vendor formats without custom code. Custom AI Extensions: For specialized industry requirements (such as pulling specific project task codes, vessel numbers, or custom tax attributes), standard pre-built models can easily be extended using AI Builder studio. 2. Ingestion & Visual Exception Review Before an invoice reaches your ERP ledger, it flows through an automated capture and review queue hosted on Dataverse. +-----------------------------------------------------------------------+ | SIDE-BY-SIDE REVIEW QUEUE | | | | +---------------------------------+ +----------------------------+ | | | RAW PDF DOCUMENT | | EXTRACTED DATAVERSE FIELDS | | | | | | | | | | INVOICE #: INV-90210 | |...
