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A thorough analysis of a credit management company’s operations allowed us to map the AI opportunities capable of improving staff productivity and the customer experience, ultimately driving growth.
Our client, an international credit management company, helps its customers manage contract compliance, efficient invoicing, and timely repayments. Striving for improved efficiency and growth, the company engaged us to identify high-impact AI integration opportunities within its business and outline the process and terms of their implementation.
Credit management company
Trading & financial services
LLM solution
AI opportunity mapping
Python, Tableau, PowerBI
We conducted the mapping in three key phases: analyzing ongoing processes, identifying AI opportunities, and planning for integration opportunities.
We started by analyzing the company’s tasks and processes, categorizing them into routine, data-driven, decision-making, and customer support tasks. We then interviewed the company’s employees to identify the issues and inconveniences they encounter in completing these tasks.
Our assessment identified specific operations that could benefit from AI-powered data analysis, predictive analytics, and intelligent decision support. We also examined the tools employees use to complete their tasks, which allowed us to identify automation opportunities.
Our team then specified the AI technologies and solutions required for each integration option. To assess their feasibility and determine the optimal order of execution, our specialists evaluated the resources needed and estimated the return on investment for each AI integration.
After a thorough analysis, we created a comprehensive strategic roadmap outlining the steps and optimal order of AI implementation, including timelines, milestones, and required resources. This roadmap gave our client a clear picture of the next steps.
Based on our analysis of the company’s operations, the EffectiveSoft specialists outlined several AI integration opportunities, along with the terms and optimal order of their implementation. As a result, our team integrated a RAG-based LLM solution to automate responses to customer queries, improving customer support and workload distribution while lowering costs. Our collaboration with the client is ongoing, with plans to implement several other outlined solutions.
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