Przypadki użycia

Need a hands-free process to create SAP S/4HANA Sales Orders from received Purchase Orders (PDF attachments and email bodies).

Automate PO intake → extraction → validation → structured export to enable straight-through Sales Order creation with minimal manual handling.

Implemented an end-to-end email-driven scenario: POs are received, recognized, and extracted in Graip.AI. From long text product descriptions, Graip.AI additionally extracts product characteristics and their values. Data is validated against external Master Data (e.g., existing customer validation; whether the product configuration has been sold before). Export is automated via XML to drive Sales Order creation.

Purchase orders arrive in multiple formats (Excel, PDF, scans, TXT) and non-standard layouts/codes from customers across Europe and the Americas. Teams spend hours validating item codes and manually entering data into ERP, creating delays and errors.

Achieve straight-through PO processing with robust format support, master-data validation, and customer identity resolution – routing only true exceptions to humans.

Implemented an end-to-end PO workflow in Graip.AI. The solution ingests and classifies all PO formats (PDF, DOCX, XLS/XLSX, TXT, PNG/JPG scans), extracts key fields (product codes, quantities, dates, pricing, customer details), and validates them against ERP master data. Customer identity resolution is added by cross-checking Customer ID against normalized postal address data to ensure the correct ERP customer number is used. Discrepancies (e.g., item code not found, multiple IDs mapped to one address) are routed to an exception queue. Approved records are posted directly into ERP via API with full auditability.

Manual extraction from Purchase Orders, Sales Orders, and Invoices sent by email, combined with time-consuming reconciliation between invoices and corresponding POs. Vendor identification is often inconsistent, sometimes provided only as customer codes. Additionally, a single invoice may relate to multiple POs, which increases review effort.

Automate document intake and extraction, reliably resolve vendor identity, and enable scalable matching across one-to-many invoice/PO scenarios with clear exception handling.

Implemented an end-to-end email-driven workflow in Graip.AI integrated with Microsoft Dynamics 365 ERP. The system automatically collects attachments, classifies PO, SO, and Invoice documents, and extracts line-level data. A code-mapping engine resolves vendor identity by translating customer codes into the internal Vendor Code. Two-way matching (Invoice ⇔ PO) supports one-to-many scenarios. Exact line matches are highlighted, and exceptions (description, quantity, or price variances) are surfaced for manual approval. Approved documents are created or updated in Dynamics 365 via API with full traceability.

Purchase orders arrive in multiple formats (Excel, PDF, scans, TXT) and non-standard layouts/codes from customers across Europe and the Americas. Teams spend hours validating item codes and manually entering data into ERP, creating delays and errors.

Achieve straight-through PO processing with robust format support, master-data validation, and customer identity resolution – routing only true exceptions to humans.

Implemented an end-to-end PO workflow in Graip.AI. The solution ingests and classifies all PO formats (PDF, DOCX, XLS/XLSX, TXT, PNG/JPG scans), extracts key fields (product codes, quantities, dates, pricing, customer details), and validates them against ERP master data. Customer identity resolution is added by cross-checking Customer ID against normalized postal address data to ensure the correct ERP customer number is used. Discrepancies (e.g., item code not found, multiple IDs mapped to one address) are routed to an exception queue. Approved records are posted directly into ERP via API with full auditability.

Manual extraction from Purchase Orders, Sales Orders, and Invoices sent by email, combined with time-consuming reconciliation between invoices and corresponding POs. Vendor identification is often inconsistent, sometimes provided only as customer codes. Additionally, a single invoice may relate to multiple POs, which increases review effort.

Automate document intake and extraction, reliably resolve vendor identity, and enable scalable matching across one-to-many invoice/PO scenarios with clear exception handling.

Implemented an end-to-end email-driven workflow in Graip.AI integrated with Microsoft Dynamics 365 ERP. The system automatically collects attachments, classifies PO, SO, and Invoice documents, and extracts line-level data. A code-mapping engine resolves vendor identity by translating customer codes into the internal Vendor Code. Two-way matching (Invoice ⇔ PO) supports one-to-many scenarios. Exact line matches are highlighted, and exceptions (description, quantity, or price variances) are surfaced for manual approval. Approved documents are created or updated in Dynamics 365 via API with full traceability.

Manual creation of invoices in SAP FI from multiple paper-based formats. Different invoice types require separate automation flows.

Automate capture, extraction, and ERP validation so invoices can be created consistently and quickly across invoice types.

Implemented an end-to-end workflow for paper invoices. Each invoice is photographed, ingested into Graip.AI, and automatically processed: data is recognized, extracted, and validated against the relevant purchase orders in SAP ERP. Automated API-based export then creates the correct invoice object in the ERP system, ensuring consistent and fast processing across all invoice types.

Manual data extraction from a huge monthly volume of incoming invoices.

Increase throughput and consistency by automating extraction and applying customer-specific accounting/business logic before posting to downstream systems.

Built an end-to-end automated workflow with AI-powered data extraction and recognition, plus post-processing that enriches raw data using customer-provided business logic. Automated API-based export was implemented to create objects and records in the third-party system.

Rapidly increasing volume of invoices and receipts from clients; documents varied in structure and contained multiple languages, making manual processing slow and error-prone.

Fully automate classification, extraction, and transfer to the client's payment/accounting systems to scale volume without scaling headcount.

Implemented an end-to-end Graip.AI workflow. It uses AI to classify documents such as Invoices and Receipts, automatically extract required fields, and format them for the client's payment system. Data is then transferred into the client's payment system in the specified format. The workflow eliminates manual intervention and supports significant growth in processed volume.

Manual management of Utility Bills across physical betting shops led to missed payment deadlines, service disruptions, and financial penalties. Shop managers and regional operators tracked invoices via disconnected spreadsheets and email threads, lacking centralized visibility, real-time status updates, and automated reminders. This resulted in inconsistent processes and delayed payments.

Automate Utility Bill ingestion and tracking, provide real-time visibility into payment status across all shop locations, eliminate missed payments through proactive notifications, and enable data-driven oversight with minimal manual intervention while maintaining financial compliance.

Graip.AI integrates via email and API to automatically ingest Utility Bills from multiple providers, classify and extract key billing data, and deliver a centralized platform with real-time dashboards, drill-down analytics, trend monitoring, and customizable alerts. The system sends automated email notifications for upcoming payments and missing Bills, supports role-based access control (edit/view), and enables flexible sharing and export of reports.

Operators manually reviewed supporting documents, entered details into internal systems, and verified them against registration data, causing delays and frequent errors.

Automate the KYC process, auto-approve exact matches, and reduce the number of operators needed while maintaining compliance.

After registration and before the first deposit, users upload identity documents (Passport, ID Card, or Driver's License) and proof-of-address documents (Utility Bill, Bank Statement, etc.). Graip.AI receives the documents via API in real time, classifies and extracts the data, and returns the results to the client system. Exact matches (e.g., registration address equals the address on the document) are auto-approved, while ambiguous cases are routed to operators for manual verification, ensuring full coverage and error-free processing.

Invoices arrive from multiple markets in various formats and languages and are centralized in SharePoint. Details must be manually entered into the SharePoint List, creating delays, inconsistent data, and rework.

Automate Invoice intake from SharePoint, extraction in multiple languages, master-data lookups (customer, vendor), and posting of clean records back to the SharePoint List, so the AP team only reviews exceptions.

Implemented a near-real-time Graip.AI-to-SharePoint workflow. Invoices uploaded to a designated SharePoint library are automatically ingested by Graip.AI, which classifies, extracts, and validates all required fields, including exact and fuzzy master-data matches. Only invalid or incomplete documents are routed for review, while valid invoices are posted back to the SharePoint List automatically. Status and analytics are accessible in a single SharePoint dashboard, providing full visibility across the process.

Manual data extraction from thousands of business documents each month, each with different sets of header and item fields. Data had to be manually entered into a 3rd-party system. Document types include Driving License, Insurance Document, Lease Document, Mortgage Document, Vehicle Registration, Voter Card, Deed of Trust, and Bank Statement.

Replace template-by-template manual keying with a scalable automated flow that can classify document type, extract the right fields, and push data into downstream systems with quality controls.

Implemented an end-to-end automated workflow with AI-driven document classification, extraction, and recognition. Data input and export are automated via API, including object creation in the 3rd-party solution. Added automated alerts for missing mandatory data to ensure accuracy and completeness.

Invoices arrive as PDFs from multiple customers, each using different templates and platform requirements, such as Coupa, Ariba, PayeeCentral, or Tungsten. Operations teams must distinguish purchase order (PO) invoices from non-PO invoices, apply customer-specific mapping rules, extract fields, and upload the data to the appropriate platform accounts. This manual process creates delays, requires significant effort, and increases the risk of errors.

Standardize PDF invoice intake, automatically map invoices by customer and platform, extract the necessary fields, and export a JSON payload that meets the mandatory requirements of all target platforms. Only exceptions should require human review and approval.

Implemented an end-to-end Graip.AI workflow that automatically ingests PDFs, whether uploaded directly or sent via email. The system classifies and maps invoices by customer and platform, recognizes and extracts the required fields, and exports a JSON template after human approval. The workflow supports multiple platforms, including Coupa, Ariba, and PayeeCentral, ensuring consistent, accurate, and efficient processing.

Large, multi-line purchase orders arrive in mixed formats (Excel, PDF). Key columns often combine multiple attributes in a single cell, requiring manual parsing, normalization, and validation before loading into a custom ERP. Previously, ~8 people handled this process, causing delays in confirmations and production planning.

Accurately extract data across diverse partner layouts, even when headers vary or are missing. Convert multi-value cells into structured, ERP-ready fields to enable near-real-time processing.

Implemented a Graip.AI-powered PO automation that automatically identifies the correct columns for each partner layout and splits multi-value cells into the appropriate fields. This delivers high-accuracy extraction across formats, moves processing from batches to near real time, and eliminates most of the manual workload, freeing staff to focus on supplier coordination and promotions.

High volumes of packing slips and invoices arrive from many suppliers in inconsistent formats and quality, including poor-resolution scans with handwritten notes. Teams spend significant time interpreting layouts, entering line items, reconciling conflicts, and deriving missing information, which slows confirmations and causes pricing or receiving errors.

Automate data extraction reliably, even from low-quality scans, resolve conflicts between printed and handwritten text, validate against master data, and provide real-time visibility into processing.

Implemented a Graip.AI-powered automation that ingests documents from email or file drops, applies robust OCR with handwriting recognition, and prioritizes handwritten annotations over printed text when conflicts arise. The system automatically interprets vendor layouts, identifies columns, validates against retailer master data, and routes exceptions for approval. Extracted results are exported to Google Sheets for real-time monitoring.

As transaction volumes grew, manual handling of trade paperwork became a bottleneck. Each shipment involved multiple parties and authorities. At the same time, product onboarding at scale was constrained: supplier catalogs arrived in different PDF formats, languages, and layouts, slowing standardization and listing creation.

Automate both trade document workflows (to ensure consistency and compliance) and product data extraction from catalogs, accelerating supplier onboarding and offer creation.

Introduced Graip.AI to automate the sequential creation of trade documents (Proforma Invoice → Purchase Order → Commercial Invoice), reducing manual steps and ensuring consistency across buyer and seller records. Implemented automated cross-checks of key shipment documents (Customs Declarations, Invoices, Certificates of Origin, Transport Forms) to flag discrepancies early and reduce compliance risk. In parallel, extracted product details from supplier catalogs, transforming unstructured PDFs into structured marketplace listings much faster.