Multi-agent extendable hyperautomation platform for enterprise accounting automation

The client is a leading global retail chain operating in over 50 countries with 9,000 stores worldwide. The company offers a diverse range of consumer products through an extensive brick-and-mortar and e-commerce presence, serving millions of customers across multiple markets.

Before implementing the hyperautomation system, the client faced several operational challenges:

• High volume reconciliation workload – Managing hundreds of suppliers with frequent, high-volume financial settlements across 60+ legal entities
• Resource-intensive manual processes – Each reconciliation required 30-45 minutes of manual data gathering, manipulation, and matching
• Legacy system limitations – Operating with disconnected enterprise resource planning systems and customer relationship management platforms that lacked API connectivity
• Inconsistent processes – No standardized reconciliation playbook across multiple entities, leading to process variation across departments
• Operational bottlenecks – Finance teams working late hours to complete reconciliations, producing 15,000 reports per quarter

The company needed an intelligent automation solution to improve reconciliation efficiency, reduce manual workload, and minimize error rates without disrupting their existing technology infrastructure.

Constraints: The hyperautomation platform needed to work within the client’s existing enterprise software ecosystem without requiring major system overhauls or extensive process modifications. The solution had to maintain the same level of financial accuracy while significantly reducing manual intervention.

Process mapping revealed that data extraction, formatting, and validation were performed manually with no existing automation solutions, creating bottlenecks and dependencies.

Solution: We implemented intelligent agents for data extraction and processing, creating automated workflows that handle repetitive operations while maintaining accuracy. The system processes diverse input formats and validates data automatically across all enterprise systems.

Tech stack audit showed that enterprise resource planning systems lacked API connectivity and were not fully integrated, requiring manual interventions to share data across systems.

Solution: We developed custom connectors and integration layers that enable seamless data flow between disconnected systems. Our agents interact with each system independently while maintaining unified reconciliation processes across all 60+ legal entities.

Discovery found no standardized reconciliation playbook across multiple entities, leading to significant process variation across departments and legal entities.

Solution: We created a flexible multi-agent architecture that adapts to different process variations while establishing unified automation standards. The system accommodates entity-specific requirements while maintaining consistent reconciliation principles.

Analysis revealed that processes needed categorization into full automation, partial automation, and non-automation eligible, requiring sophisticated exception handling mechanisms.

Solution: We built intelligent classification systems that automatically determine automation eligibility for each reconciliation task. The platform includes robust exception-handling tools that flag complex scenarios for human intervention while fully automating high-volume repetitive actions.

Roadmap design constraints required deployment within a quarter while working exclusively within the existing enterprise software infrastructure without modifications.

Solution: We designed a non-invasive integration approach that works with existing enterprise systems without requiring infrastructure changes. Our agents operate through existing interfaces, ensuring rapid deployment while maintaining system stability and user familiarity.

Managing hundreds of suppliers with diverse communication formats and approval processes created significant coordination and response tracking challenges during reconciliation cycles.

Solution: We developed an intelligent Router agent with Named Entity Recognition capabilities that automatically processes supplier emails, classifies responses, and manages the entire communication workflow. The system handles supplier interactions autonomously while maintaining complete audit trails and escalation protocols.

In the first phase, we built a rule-based RPA tool for automating straightforward reconciliation tasks.

• Automating basic reconciliation operations through deterministic reconciliation procedures
• Supporting standard reconciliation act formats
• Generating a discrepancy report

At this stage, we moved on to building an LLM-based multi-agent AI platform that could navigate complex tasks, learn based on its prior experience, and adapt to unexpected scenarios.

This self-learning agent enabled the following automation:

• Creating an account reconciliation schedule
• Generating reconciliation reports
• Sharing the reports with the counterparty for validation and approval
• Continuous monitoring of an accountant’s inbox for replies from counterparties
• Filing approved reconciliation statements into the ERP