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Modern enterprises receive thousands of customer orders daily through multiple channels, including email, attachments, and structured documents. Processing these orders manually often results in slow turnaround, data inconsistencies, and compliance risks.
To solve this, organizations are turning to Agentic AI-powered automation, enabling end-to-end orchestration from email ingestion to ERP posting, acknowledgment, and analytics.
At XenonStack, we’ve designed and deployed such AI-driven order automation workflows across multiple enterprise ecosystems, including SAP ECC, SAP HANA, Oracle Cloud Fusion, Salesforce, and Infor. One of the best examples of this transformation is our work with Hans Logistics, a leading logistics company in the Middle East.
The Challenge: Fragmented and Manual Processes
A Middle-East logistics provider needed to turn high-volume, email-driven orders into clean, auditable ERP postings—fast. Documents arrived in various formats, including PDFs, Excel spreadsheets, HTML bodies, and nested attachments; staff had to retype details into trade/finance systems and SAP ECC, which created delays and reconciliation errors.
We implemented an Agentic AI workflow that ingests emails, extracts structured data, validates against master data, stages safely in SAP, posts via standard APIs/BAPIs, and sends automatic acknowledgments—backed by full observability and replay. The reference implementation and results are based on our logistics work in the region.
Key challenges included:
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Multi-format intake at scale
Orders and invoices arrive via Outlook as PDF, Excel, HTML, and email bodies, often with nested or inconsistent attachments; manual extraction is prone to errors and slow.
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Dual/multi-system posting
Operational and statutory flows (e.g., trade declarations + ERP) must be kept in lockstep; manual reentry creates mismatches across financial, inventory, and customs records.
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Validation against master data
Material codes, plants, storage locations, vendors, tax codes—all must validate before posting to avoid reversals and downstream churn.
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Safety and auditability
Direct writes into core tables are risky. You need safe staging with per-record lineage, error logs, and replay capabilities to meet SLAs and audit requirements. -
Throughput and fairness
ERP gateways have concurrency limits. Flooding them with parallel requests can degrade service; you need queues, batching, and throttling that adapt to real-time conditions.
The Solution: AI Agentic Workflow for End-to-End Automation
We build a multi-agent automation framework powered by the Akira Agentic AI Platform and NexaStack AI, integrating seamlessly with ERP Systems.
1) Email intake & document parsing
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Monitor designated inboxes, parse subject/body, and extract fields from PDFs/Excel/HTML files.
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Detect order numbers, delivery dates, SKUs, quantities, customer/vendor IDs.
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Normalize values (units, currency) and capture attachment metadata for audit.
2) Validation + safe staging in SAP
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Instead of posting directly, stage into custom Z-tables:
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ZHS_INV_HDR (header with status flags NEW/VALIDATED/POSTED/ERROR),
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ZHS_INV_ITM (line items),
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ZHS_ATTACH (attachment metadata),
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ZHS_ERR_LOG (structured error details),
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ZHS_DECL (cross-reference to external declaration numbers).
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This decouples external payloads from SAP core and enables replayable, auditable flows.
3) API layer via SAP Gateway (OData)
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Custom OData service ZHS_INV_SRV exposes entities and actions:
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POST /Headers (create header),
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POST /Headers('UUID')/Items (add items),
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POST/Headers('UUID')/Attachments (upload file or metadata via CREATE_STREAM),
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POST /Postings(DocUUID=…) to validate + post to ECC,
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GET /Errors?$filter=DocUUID eq '…' (retrieve error details).
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Implemented in ABAP with DPC_EXT classes for mapping, validation, and posting.
4) Standards-based posting (FI/MM/SD)
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Goods movements: BAPI_GOODSMVT_CREATE with checks on plant, storage location, and material master.
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Financial postings: BAPI_ACC_DOCUMENT_POST or BAPI_INCOMINGINVOICE_CREATE with vendor/tax validation.
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Failures are captured in ZHS_ERR_LOG, and ZHS_INV_HDR status flips to ERROR; agents can remediate and replay safely.
5) Acknowledgments + notifications
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Upon success, generate automated email acknowledgments with ERP document IDs. Upon validation failure, send actionable error notices linked to the error log (DocUUID) for quick fixes and replay (per the Data Errors endpoint).
6) Security, transport, and governance
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Same-network deployment for agents; HTTPS/TLS to Gateway; technical role ZROLE_HS_ODATA; access limited to the OData node and Z-tables (no core-table writes).
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Dev→QA→Prod via SAP transports for versioning and auditability.
7) Observability, testing, and replay
- Unit tests for mapping/validation; integration tests for OData endpoints; end-to-end from email → staging → posting → acknowledgment.
- Dashboards + exception replay for transparent operations and compliance.
8) Throughput control at enterprise scale
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OData $batch, backlog queues, dynamic throttling based on response times; deferred transactions remain in agent queues until safely posted; operations can trigger reprocessing via OData or a custom SAP monitor (e.g., ZHS_ERR_MON).
Traditional RPA tools are limited to rule-based execution. Our Agentic AI approach extends automation with:
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Perception + understanding: Agents interpret diverse formats (PDF, Excel, HTML, nested emails) and generalize to new vendor/customer layouts without brittle templates—dramatically reducing maintenance on document changes.
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Reasoning and validation: Beyond extraction, agents reason over context (e.g., plant/material validity, tax code presence, duplicate detection using email message IDs) before posting. When confidence is low, they ask for human input and learn from outcomes (closed-loop improvement).
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Action + autonomy: Agents don’t just “fill forms”—they call OData actions, invoke BAPIs, and manage end-to-end flows including retries, replay, and acknowledgments. This shortens the cycle time from hours to minutes.
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Memory and observability: With Z-table staging, structured error logs, and dashboards, agents build operational memory. They utilize prior failures to auto-correct mappings and reduce reprocessing to less than 2%.
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Control and governance: Agentic workflows respect the segregation of duties (no core-table writes), utilize transported ABAP artifacts, and operate within strict TLS/role-based access—ready for audits and SLA reviews.
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Scale + resilience: Queue management, batching, and adaptive throttling keep ERP gateways healthy while maintaining high throughput—vital when volumes spike (seasonality, promotions, backlog bursts).
Cross-ERP Experience: How Agentic AI Extends Across Enterprise Systems
Modern enterprises rarely operate on a single ERP. A global logistics, banking, or manufacturing organization may utilize SAP ECC for finance and inventory, Oracle Fusion for procurement, Salesforce for customer operations, and Infor CloudSuite for supply chain execution.
Our Agentic AI framework is designed to integrate seamlessly across these ecosystems, utilizing the same core principles: API-first connectivity, staging for auditability, autonomous validation, and observability.
Below is how our experience spans each ERP family:
SAP ECC and S/4 HANA
Our strongest lineage is in SAP environments, where we design Agentic Gateways that enable autonomous agents to interact with ECC and S/4HANA using standard BAPIs and OData services.
Integration pattern
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Custom Z-tables (Header, Item, Attachment, Error Log, Declaration) provide a safe staging layer.
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SAP Gateway OData services (e.g., ZHS_INV_SRV) expose create, update, and posting actions.
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Agents use BAPI_GOODSMVT_CREATE, BAPI_ACC_DOCUMENT_POST, and BAPI_INCOMINGINVOICE_CREATE for transactional posting.
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Observability dashboards and replay transactions (ZHS_ERR_MON) offer complete auditability.
Typical agentic use cases
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Email-to-Invoice ingestion and validation.
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PO-based Goods Receipt / Goods Issue automation.
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Vendor Helpdesk response based on live invoice status.
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SLA Analytics and Exception Replay dashboards.
Outcome
Real-time posting, < 2 % reprocessing, and end-to-end transparency, all within SAP governance and transport control.
Oracle Cloud Fusion
In Oracle Fusion ecosystems, our agents leverage REST APIs and BIP interfaces to automate financial and procurement workflows.
Integration pattern
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Agentic pipelines extract and normalize data (from PDFs, Excel, or supplier emails).
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Validated data is sent to Fusion through its REST endpoints for invoices, POs, and payments.
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AI-driven mapping ensures compliance with Oracle’s data model and chart of accounts.
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Agents poll acknowledgment or rejection responses and reconcile statuses back into the staging layer.
Use cases
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Autonomous Invoice Entry and PO matching.
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Exception handling for tax, supplier, or tolerance mismatches.
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AI-based supplier communication (acknowledgments, clarifications).
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Automated reporting for audit and SLA compliance.
Outcome
- Reduction in manual entry and faster invoice-to-payment cycles while maintaining Fusion’s native approval hierarchy.
Salesforce (Enterprise Cloud CRM)
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Salesforce is often the system of engagement for orders, cases, or customer requests.
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Our Agentic AI connectors transform it into a front-end orchestrator for ERP automation.
Integration pattern
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Agents listen to Salesforce events (such as new Order, Opportunity Closed, or Case Raised).
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Data is fetched via the Salesforce API or Platform Events.
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Validations are performed against back-end ERP master data.
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Agents post resulting documents (such as Sales Orders, Deliveries, or Invoices) into SAP ECC or Oracle Fusion through API calls.
Use cases
- Order-to-Cash automation: Salesforce → SAP posting → acknowledgment → status sync back.
- Complaint or return handling: Salesforce Case → ERP Credit Memo → confirmation.
- AI assistants that answer customer queries using ERP-fetched data.
Outcome
Seamless collaboration between CRM and ERP—no manual rekeying, and instant visibility of order and payment status.
Infor CloudSuite / LN / ION
Infor systems power supply chain and manufacturing processes. Our integration focuses on workflow synchronization and API-based posting through Infor ION middleware.
Integration pattern
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Agentic workflows extract orders, shipments, or invoices from external sources.
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Data is transformed to ION’s JSON/XML structure.
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REST API calls create or update documents in Infor’s modules.
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Agents monitor the ION Inbox for acknowledgments or exceptions.
Use cases
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Purchase Order and Receipt Automation.
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Inventory reconciliation and goods movement synchronization.
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AI-driven notification workflows for supply chain stakeholders.
Outcome
Improved process velocity and compliance in high-volume logistics and manufacturing environments.
Business Impact
Implementing Agentic AI for order processing and invoice automation delivers tangible operational improvements:
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90%+ automation accuracy in data extraction and posting
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Processing cycle reduced from hours to minutes
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Error rate under 2% through adaptive validation and reprocessing
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Audit-ready transparency with detailed logs and dashboards
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Future-proof design compatible with S/4HANA migration
Conclusion
The automation of customer order processing is no longer a back-office optimization — it’s a strategic enabler for growth. By integrating Agentic AI workflows with ERP systems like SAP ECC, SAP HANA, Oracle Fusion, Salesforce, and Infor, enterprises can achieve higher speed, accuracy, and compliance while reducing manual overhead.
Agentic AI transforms email-driven transactions into autonomous digital workflows — delivering a future-ready enterprise where orders process themselves, acknowledgments are instant, and business runs seamlessly across systems.
Frequently Asked Questions (FAQs)
Agentic AI automation transforms how businesses manage customer orders by streamlining the entire process—from order validation to payment, inventory management, and customer communication.
What is Agentic AI Automation in Customer Order Processing?
Agentic AI utilizes advanced automation to streamline and optimize the entire customer order process—automatically validating orders, processing payments, managing inventory, and communicating with customers without manual intervention.
How does Agentic AI improve customer order processing?
By automating repetitive tasks, Agentic AI accelerates order fulfillment, reduces human errors, and provides real-time updates to customers—resulting in faster deliveries andmore reliable service.
Is Agentic AI secure for handling customer data?
Yes, the system is designed with top-tier security protocols, including encryption and compliance with global standards such as GDPR and PCI-DSS, ensuring that all customer data remains protected.
Can I monitor and adjust the AI system if needed?
Yes, the AI system provides real-time dashboards to track key metrics and allows for manual overrides when needed, giving businesses complete visibility and control over their operations.
What are the cost benefits of using Agentic AI in order processing?
Implementing Agentic AI reduces operational costs by automating labor-intensive workflows, boosting efficiency, and scaling seamlessly with increasing order volumes—delivering significant long-term savings.
