Case Studies
Examples of production AI systems we build for enterprise operations.
Automated Invoice Extraction System integrated with existing ERP.
Custom document-processing pipeline combining vision models, validation logic, and ERP integration.
System delivered in 6 weeks.
The Problem
Manual processing of 10,000+ monthly vendor invoices causing payment delays and high error rates.
Our Approach
Implemented an intelligent document processing pipeline using vision models to extract line items.
Stack: Vision models • Python processing pipeline • ERP integration
The Outcome
Reduced manual processing time by 85% and eliminated data entry errors.
Internal Support Copilot with citation-backed answers.
Internal support copilot built on a RAG architecture with citation-backed answers from technical documentation.
Production deployment in 5 weeks.
The Problem
Customer support team overwhelmed by repetitive technical queries, leading to slow response times.
Our Approach
Developed a RAG-based internal assistant trained on historical tickets and product documentation.
Stack: RAG architecture • vector database • internal documentation ingestion
The Outcome
Deflected 40% of tier-1 support tickets and improved complex issue resolution speed by 3×.
Supply Chain Decision Support Tool.
Predictive analytics system using operational data to forecast supply disruptions and inventory risks.
System delivered in 8 weeks.
The Problem
Operations managers lacked real-time visibility into supply chain bottlenecks.
Our Approach
Built a predictive analytics dashboard powered by custom machine learning models.
Stack: ML forecasting models • analytics dashboard • operational data pipeline
The Outcome
Reduced inventory holding costs by 15% while providing proactive disruption alerts.