Before you begin, make sure you:
Have Group Reporting Templates created and configured
Have your subsidiary companies connected via Xero or QuickBooks
Verify you have sufficient AI mapping credits available
Review your chart of accounts to understand account naming conventions
Consider your mapping requirements and consolidation objectives
Understanding AutoMap with AI: Secure intelligent automation
GATHER.nexus's AutoMap with AI functionality uses Microsoft Azure AI models to provide secure, intelligent account mapping suggestions. This powerful feature analyses account names, types, and patterns to suggest optimal mappings between your company's chart of accounts and your Group Reporting Template structure.
Why AutoMap with AI transforms your mapping process:
Dramatic Time Savings: Reduce mapping time through intelligent automation
Secure Technology: Leverages Microsoft Azure AI with enterprise-grade security and data protection
Intelligent Analysis: AI evaluates account names, types, and business logic for optimal suggestions
Confidence Scoring: Provides percentage-based confidence levels for each mapping suggestion
Transparent Reasoning: Detailed explanations for each AI mapping decision
Consistency: Maintains consistent mapping approaches across multiple entities
Azure AI Security Benefits:
Enterprise Security: Microsoft Azure provides bank-level security for all AI processing
Data Privacy: Your financial data remains secure and is not used to train AI models
Reliability: Enterprise-grade AI infrastructure ensures consistent performance
Step 1: Access Group Reporting Templates
Navigate to Group Financial Reporting and click on the Group Reporting Template tab to view your available templates.
(The Group Reporting Templates dashboard showing "Demo Group" with mapping status indicators and "Setup Group Accounts" functionality.)
Step 2: Review mapping status
Review your template's current mapping status to understand which accounts need attention:
Mapping Status Indicators:
Demo 1: Shows "2 Mapped | 29 Unmapped" indicating progress needed
Demo 3: Displays "1 Mapped | 30 Unmapped" showing initial mapping state
(The template dashboard highlighting the mapping status with red borders around companies showing unmapped accounts requiring attention.)
Step 3: Open the mapping interface
Click on Setup Group Accounts or any of the mapped/unmapped status indicators to access the Group Reporting Template Mapping interface.
This opens the comprehensive mapping environment where you'll access AI-powered automation.
Step 4: Access AutoMap with AI functionality
In the Group Reporting Template Mapping interface, locate and click the AutoMap with AI button.
(The mapping interface showing "Demo Group: Demo Group" with Profit and Loss accounts ready for AI mapping, displaying the AutoMap with AI button with remaining credits "28/30 left".)
Key Interface Elements:
Credits Display: "Credits: 29/30 left" shows your remaining AI mapping allocation
Account Categories: Revenue section displayed for systematic mapping
Company Selection: "Demo 1" chosen for mapping focus
Available Accounts: Right panel shows company accounts ready for AI analysis
Step 5: Initiate AI mapping process
Click AutoMap with AI to begin the intelligent mapping analysis. The AI will process your company's chart of accounts and suggest mappings to your Group Reporting Template.
AI Processing Includes:
Account Name Analysis: Evaluates account names for semantic meaning
Account Type Recognition: Identifies account types and categories
Business Logic Application: Applies accounting principles for logical mappings
Step 6: Review AI mapping suggestions
After processing, the AI displays intelligent mapping suggestions with confidence indicators:
Confidence Level Indicators:
0-20%: Low confidence - requires review and validation
20-40%: Moderate confidence - consider manual verification
40-60%: Good confidence - likely accurate but worth reviewing
60-80%: High confidence - strong mapping likelihood
80-100%: Very high confidence - excellent mapping probability
(The mapping interface showing AI-generated mappings with confidence percentage indicators: 0-20%, 20-40%, 40-60%, 60-80%, and 80-100% displayed as visual indicators across the mapped accounts.)
Step 7: Access detailed AI reasoning
Hover over the information icon (i) next to any mapping to understand the AI's reasoning:
(A tooltip displaying: "'Operating Revenue' is best matched with 'Sales (REVENUE)' as it is the primary regular revenue account. High alignment in both account type and purpose.")
AI Reasoning Benefits:
Transparent Logic: Understand why AI made specific mapping decisions
Learning Opportunity: Gain insights into optimal mapping strategies
Validation Support: Verify AI logic aligns with your business requirements
Confidence Building: Build trust in AI suggestions through clear explanations
Optimising AI mapping results
Reviewing and validating AI suggestions
High Confidence Mappings (80-100%):
Generally accurate and can be accepted with minimal review
Verify they align with your specific business requirements
Consider any unique aspects of your chart of accounts
Medium Confidence Mappings (40-80%):
Review AI reasoning to understand mapping logic
Validate against your consolidation requirements
Consider manual adjustments if needed
Low Confidence Mappings (0-40%):
Require careful manual review and validation
May indicate unique account structures or naming conventions
Consider manual mapping for these accounts
Manual adjustments and refinements
When to make manual adjustments:
AI confidence level doesn't meet your requirements
Specific business logic requires different mapping approach
Unique account structures not recognised by AI
Regulatory or compliance requirements mandate specific mappings
How to refine AI mappings:
Use drag-and-drop functionality to reassign mappings
Review unmapped accounts for additional mapping opportunities
Apply consistent mapping logic across similar accounts
Document mapping decisions for future reference
Best practices for AI mapping success
Maximising AI effectiveness:
Account Naming Consistency: Maintain consistent, descriptive account names across entities for better AI recognition
Chart of Accounts Structure: Use standard accounting structures that AI can easily recognise and categorise
Regular Review: Periodically review AI suggestions to ensure continued accuracy and relevance
Credit management and allocation:
Monthly Credit Allocation: Monitor your monthly AI mapping credit usage (e.g., "29/30 left")
Strategic Usage: Reserve credits for complex entities or challenging mapping scenarios
Credit Optimisation: Use AI for initial mapping, then manual refinement for efficiency
Common questions
Q: How secure is the AI mapping process?
A: GATHER.nexus uses Microsoft Azure AI with enterprise-grade security. Your financial data is processed securely and is not used to train AI models.
Q: What if AI confidence levels are consistently low?
A: Low confidence may indicate unique account naming or structures. Consider standardising account names or using manual mapping for these accounts.
Q: Can I override AI mapping suggestions?
A: Yes, all AI suggestions can be manually reviewed, modified, or replaced using the drag-and-drop interface.
Q: How many AI credits do I receive monthly?
A: 30 Credits/Month this will renew in the next month.
Q: Will AI learn from my manual corrections?
A: While AI doesn't learn from individual corrections, GATHER continuously improves prompts to get better ouptut.
What's next?
With AutoMap with AI successfully implemented, you can:
Accelerate mapping for additional entities using proven AI patterns
Refine mappings based on AI reasoning and business requirements
Scale consolidation efficiently as you add new subsidiary companies
Maintain consistency across your multi-entity structure with AI-assisted mapping
Focus on strategy rather than manual configuration tasks
Your AI-powered mapping system now provides the foundation for efficient, accurate, and scalable multi-entity consolidation.
Have questions or need assistance❓
Contact our support team at support@gather.nexus