Save the ‘busy’ work
for the machines
Conversational
AI Agent
An intelligent, multi-tenant AI assistant operating from within your Microsoft Teams or use Multi-Channel Integration: Teams, Web, Chat, Outlook.
Access data instantly
Effortlessly reach the information you need 24/7,
with your ERPure.AI agent available via Microsoft Teams.
Eliminate human error
Your ERPure.AI agent securely operates in multi-tenant environments with strict role-based access control.
Expense Management
AI Agent
A cloud-based AI agent that streamlines expense reporting via natural conversation.
Full expense management
Your ERPure.AI Agent helps your team submit expenses, approve submissions, and process expense reports directly through Microsoft Teams.
End-to-end traceability
Maintain audit trails and ensure compliance via receipt attachment handling without opening your SAP Business One environment.
Sales Process
AI Agent
The digital assistant automatically processing customer purchase orders via Microsoft Office.
Real-time stock management
Checks SAP Business One stock levels and availability, ensuring accurate inventory figures before sales order creation.
Smart record creation
Automatically suggests and creates missing customers, business records and item codes when needed, reducing processing time from hours to minutes.
Accounts Payable
AI Agent
The smart, autonomous system that acts as your digital assistant for vendor invoices.
Complex invoice handling
Efficiently handles complex vendor invoicing scenarios such as missing vendors or item codes, creating missing entities where necessary in SAP Business One.
Proactive notifications
With integrated Human-in-the-Loop collaboration, be instantly notified of successfully processed invoices, or if exceptions arise requiring human oversight.
What is ERPure.AI for SAP Business One?
Integrating your SAP Business One environment with Microsoft O365 through the power of Agentic AI
How it works
Adopting ERPure.AI for SAP Business One is simpler than it seems.
Securely connect your SAP Business One, Microsoft Outlook and Teams with ERPure.AI for effortless automated admin. Simply send your first task.
Your ERPure.AI agent replies instantly with the insights you need – ready to add, update, or retrieve your SAP Business One data on-demand.
With ERPure.AI managing every update and decision in real-time, your SAP Business One tasks are sent, tracked and completed without even opening the platform.
FAQs
How do Agentic AI agents learn?
Agentic AI learns from labelled examples, finds patterns independently, and improves decisions through rewards and feedback.
Over time, it continually adapts its understanding based on new experiences and data, becoming more accurate and effective.
Where do Agentic AI agents store their learning?
Agentic AI agents store learned information in their model parameters, external databases, or directly on devices. They may also use cloud storage for easy access, structured knowledge graphs for complex reasoning, or hybrid approaches combining multiple methods.
How is data privacy protected when using Agentic AI?
Protecting data privacy when using Agentic AI involves several strategies and technologies designed to safeguard sensitive information while still enabling the AI to learn and function effectively. Here are key measures commonly implemented:
1.
Data Anonymisation and Pseudonymisation
Before data is processed by AI systems, it can be anonymised or pseudonymised. This involves stripping or masking identifiers that connect data to an individual, making it difficult to trace back to the person without additional information that is kept separate.
2.
Encryption
Data used by Agentic AI can be encrypted both in transit and at rest. Encryption ensures that data is transformed into a secure format that only authorised systems and users can decode, protecting against unauthorised access.
3.
Access Controls
Implementing strict access controls ensures that only authorised personnel and systems have access to sensitive data. This can include role-based access controls (RBAC), where permissions are granted based on the user’s role within an organisation.
4.
Secure Data Storage
Whether data is stored on local servers, on devices, or in the cloud, implementing secure storage practices is crucial. This involves using secure servers, employing strong authentication methods, and regularly updating security protocols to protect against vulnerabilities.
5.
Differential Privacy
When aggregating data from many users to train AI models, differential privacy techniques can be employed. These techniques add noise to the data in such a way that the privacy of individual data points is maintained while still allowing for accurate aggregate analysis.
6.
Federated Learning
This is a technique where the AI model is trained across multiple decentralised devices or servers holding local data samples, without exchanging them. Thus, learning happens locally, and only the model improvements are shared and aggregated, not the data itself.
7.
Regular Audits and
Compliance Checks
Regular audits help ensure that data handling practices comply with privacy laws and regulations such as GDPR, HIPAA, or CCPA. Compliance checks can help identify and rectify potential privacy issues before they become problematic.
8.
Data Minimisation
This principle involves limiting the data collection to what is directly relevant and necessary to accomplish a specified purpose. By collecting only the data needed, Agentic AI reduces the risk of privacy breaches.
9.
Transparent Data Policies
Providing clear and understandable data policies helps users know how their data is being used, what measures are in place to protect it, and how they can control their personal information. This transparency builds trust and ensures compliance with regulatory requirements.
10.
Ethical AI Frameworks
Developing and following ethical AI frameworks that prioritise privacy is crucial. These frameworks guide the design, development, and deployment of AI systems with an inherent respect for user privacy.