Microsoft Entra ID SSO
Support for Microsoft Entra ID.
Enterprise Trust For
Document Execution Workflows
E-Flow is built for finance and trade workflows where documents lead to validations, approvals, and system actions. This page explains how access, deployment, auditability, and workflow control are handled across enterprise environments.
GDPR-aligned external AI models
No AI Model Training
Flexible Deployment
Auditability
Security Details Available during Review
RBAC model
Role-based access controls for different users.
Audit log sample
Trace key workflow actions across the workflow.
Data retention
Data remains within the agreed environment.
Encryption
AES-256 encryption at rest and TLS 1.2 for data in transit.
Deployment
On-prem, private Azure, AWS, or GCP cloud, or SaaS.
Your Proprietary Data Stays Yours
Data Handling Boundary
E-Flow controlled processing path
Business documents
Invoices and workflow files
AI processing
Approved model controls
Client environment
Records and audit history
No training path: proprietary business data is not retained or reused for model training or model improvement.
Customer-controlled storage
Your documents, extracted data, workflow records, and audit history are saved inside the agreed client-controlled environment.
Zero data training
Your proprietary data is never used to train, fine-tune, or improve Effectz.AI models.
Controlled external AI use
Where external AI models are enabled, GDPR-compliant services are used within the agreed data-handling controls.
Trust Built around Workflow Control
Backup & Recovery
Backup, restoration and recovery procedures aligned to the agreed deployment environment and operational requirements.
Incident Response
Defined processes to identify, assess and respond to security incidents affecting customer workflows or data.
Auditable workflow actions
Important workflow steps can be traced from intake to review, approval, and downstream execution.
Vulnerability Management
Security issues are identified, prioritised and remediated through ongoing review and controlled updates.
Penetration Testing
Application and deployment security can be validated through controlled penetration testing and remediation reviews.
External AI Model Controls
Where approved external AI services are used, required processing data is transmitted under agreed contractual and technical controls and is not used for our model training.
Deployment Options Based on Control Requirements
Typical trust boundary
On-premise
Private cloud
Managed SaaS
Customer data location
Customer environment
Customer cloud
Managed tenant
Infrastructure ownership
Customer
Customer
Effectz.AI managed
Security operations responsibility
Customer-led
Customer-led
Effectz.AI led
Model/runtime control
HighestHighest
HighHigh
ManagedManaged
Backup & recovery ownership
Customer
Customer
Effectz.AI
Best fit
Strict internal control
Enterprise cloud governance
Fast deployment with governance
Traceable from Document to System Action
10:02 AM / Intake event
Document received
Input arrives through configured intake channels.
10:02 AM / Extraction event
Fields extracted
Core workflow data is structured for validation.
10:03 AM / Validation event
Validation completed
Business checks run before workflow movement.
10:03 AM / Exception event
Exception raised
A policy or confidence threshold triggers review.
10:05 AM / Review event
Reviewer action
A human operator verifies, approves, or corrects the step.
10:06 AM / Execution event
System sync completed
The approved result moves to the downstream system.
Not Every Business Step Should Be Left to Unchecked Automation
Effectz.AI combines intelligent automation with human oversight so nothing important slips through the cracks.