AI agents are as good as the information they consume. We can implement a beautiful, fast, optimized machine learning model, but if your documents are scattered across emails, shared folders, and 7 different systems, the agent makes decisions based on incomplete information, which can contradict what's in SAP.
For example, we can implement a fraud detection agent for invoices with a very advanced model and still approve a fraudulent invoice if the agent sees the invoice (in SAP), validates it, but doesn't access the email from 2 months ago where Operations warned that the supplier was under legal investigation.
This is where Enterprise Content Management (ECM) systems stop being "document archiving" tools and become the cognitive engine for all agentic automation.
OpenText Extended ECM, when properly integrated with SAP, is exactly that.
3 classes of Business Data agents need
OpenText defines 3 categories of information that any enterprise agent needs to reason correctly.
Class 1: Human-Generated Content (Intent Layer)
Policies, procedures, documented decisions. The rules that govern your business.
Examples:
• Policy document: "Expense approvals > €50,000 require CFO sign-off"
• Procedure: "Invoices in foreign currency must be matched within 2% of the PO date exchange rate"
• Decision history: "Customer XYZ is high-risk because they had 3 payment defaults in Q1"
Without access to this, agents don't know your actual rules. They only know what's in SAP (fields, data types). But policies live in documents, memos, emails.
Class 2: Machine-Generated Data (Operational Nervous System)
Logs, telemetry, performance metrics. The history of how your system operates.
Examples:
• Invoice processing logs: "Supplier XYZ takes an average of 15 days to correct discrepancies, vs. 3 days industry average"
• Performance dashboards: "This month we paid 2 days slower, likely due to understaffing in banking"
• Audit trails: "Invoice #12345 was rejected 3 times in 2 weeks before being approved"
Without access to this, agents don't learn. They don't know that certain suppliers are problematic. They don't see patterns. Every invoice is new.
Class 3: Transactional & Business Network Data (Source of Truth)
Orders, invoices, financial records. The structured data in SAP that governs transactions.
Examples in SAP:
• PO #12345: quantity, Price, GL Code, Delivery Date
• Invoice: amount, GL Code, Tax, Date
• Vendor Master: payment terms, risk level, communication details
Without this, the agent lacks numbers, dates, and counterparties. But this data alone is not enough.
The problem when AI lacks the data to do its job
To better understand, here's an example of automation without integrated ECM. What the AI agent sees in this case is:
• SAP data: Invoice of €5,000, PO for €5,050, vendor is "acme-supply"
• Decision: "1% discrepancy, within 5% tolerance, approve"
• Action: Execute payment
But it doesn't see:
• Policy (Human-Generated): "Discrepancies > 2% require manual approval" (Policy is in a Word doc saved on OneDrive!)
• Operational data (Machine-Generated): "Acme Supply had 3 disputes last month, add to watchlist" (The log is on a dashboard the agent doesn't have permission for!)
• Context (Business Network): "Email from the 5th of this month: Customer reported that acme-supply sent incorrect quantity" (Email is in someone's inbox!)
Result: the agent approves, and those responsible blame the AI.
OpenText Extended ECM as an integration platform
The metadata flow between OpenText and SAP
The metadata flow between OpenText and SAP creates what OpenText calls 'integrated content governance.' It not only stores documents but also integrates them directly into the business context through automatic Business Workspaces.
That is to say, each SAP object (vendor, contract, order, invoice) automatically generates a Business Workspace in OpenText with a standard structure, and SAP metadata is automatically replicated in OpenText (policy, payment terms, supplier risk level).
But it also works in reverse: when a manager approves an invoice in OpenText, that approval is automatically recorded in SAP as 'Approved,' and payment is triggered. One action, two synchronized systems.
Integrated Workflows
Approvals occur within OpenText, but are integrated with SAP:
Example: Invoice approval workflow
1. Invoice arrives in OpenText
2. Automatic workflow: Extracts GL code (SAP), searches for policy (OpenText document), determines approver based on Amount + GL code
3. Notification to approver: "Invoice for €7,500 requires your approval. Here is the contract, here is the PO, here is the payment history for this vendor"
4. Approver digitally signs in OpenText
5. Signature automatically updates SAP as "approved" → Invoice ready for payment
Direct access from SAP
Users do not leave SAP. The Invoice-to-Pay Orchestrator clicks on an invoice in SAP, and sees Business Workspace from OpenText embedded within the SAP transaction. Furthermore, documents maintain a complete history without duplication, but are accessible via shortcuts/links.
Invoice-to-Pay is a perfect use case. In fact, Invictia, our e-invoicing solution integrated with SAP, is built exactly on this model with centralized documents, synchronized policies, auditable approvals, and compliance reporting (e-invoicing, eTaxes, etc.).
We audit your Document Management system for effective scaling
At Brait, after years of integrating ECM solutions, we know that when implemented correctly, AI projects scale and perform. OpenText Extended ECM + SAP creates the corporate memory, integrating documents + transactions + policies + auditing into a system where agents can reason correctly.
Contact us for a diagnosis, and we'll analyze:
• Where your critical documents reside (policies, procedures, decisions).
• What information SAP holds that your agents need but cannot access.
• Compliance risk due to fragmentation.
We design the roadmap most suitable for the company's needs.
