
May 19, 2025
Case Study - Analysis of contractor credibility for a factoring company
Explore the project of a modular, agent-based AI system that automates the collection, monitoring, and reporting of online company information.
This case study describes how we developed a modular, agent-based AI system that automates the collection, monitoring, and reporting of online company information. By orchestrating specialized agents to search different sources, compare findings to prior reports, and generate actionable alerts and summaries, our users can now support factoring decisions at scale with unprecedented speed and accuracy.
Challenge
Faktoring company’s underwriting team struggled to keep pace with manual internet research on client companies, facing several obstacles:
High volume of companies to monitor, making individual searches impractical
Fragmented data across multiple online platforms without clear timestamps
Risk of missing emerging issues such as negative client reviews or employee complaints
Manual consolidation into reports consumed hours per client and delayed credit decisions
Solution Development

We co-created a suite of autonomous AI agents, each responsible for a distinct research task, and a master agent to coordinate workflows:
Search Agents
Deploy unlimited agents that run in parallel
Each agent focuses on a specific type of company data
All agents feed their findings into the Master Agent
Examples:
Corporate Profile Agent: pulls business basics, leadership changes, major announcements
Sentiment Agent: tracks customer reviews, employee comments, public opinion
Compliance Agent: flags legal filings, regulatory notices, sanctions
Custom Agents: spot niche or industry-specific risk signals
Add or remove agents on the fly to match evolving monitoring needs
Master Agent
Aggregates raw outputs from all Search Agents
Compares current findings to the most recent report to detect new or changed items
Reporting Agent
Generates a concise summary report highlighting new issues, trends, and risk indicators
Configurability
The system adapts to company’s evolving risk criteria:
Unlimited Search Agents can be added for new data sources
Alignment with jurisdictional compliance rules and internal credit policies
Security and Integration
Enterprise-grade safeguards and seamless connectivity ensure trust and scalability:
Deployment options: public API for non-sensitive queries, or private cloud instances for confidential monitoring
Integration with company’s CRM and credit-decision systems
Zero retention of source documents beyond what is needed for report generation
Anticipated Business Impact
Joint testing on a sample portfolio demonstrated transformative benefits:
Research time reduced from hours to under two minutes per company
Early detection of potential risks through incremental monitoring
Consistent, unbiased summaries free from human error or fatigue
Scalable monitoring capable of handling thousands of companies daily
Underwriters reallocated to high-value analysis rather than data collection
Summary
By adopting an agentic AI approach, the company's underwriting operations shift from reactive, manual research to proactive, automated monitoring and reporting. This solution not only accelerates credit decisions but also enhances risk visibility, enabling the firm to grow its portfolio with confidence.
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