Case Studies: Supply Chain Risk
Automating With LLMs
Problem
Poor risk analytics & low analyst efficiency
Solution
Domain-specific LLM for supply chain risk
Results
- 90% reduction in manual review time
- 75% increase in accuracy
Innovate or Stagnate
Real Results
Our supply chain analytics client provides global supply chain risk analytics for enterprise and government clients. They needed to improve analyst efficiency by automating the review of tens of thousands of weekly news articles to identify potential threats. Initial machine learning efforts produced inaccurate and inconsistent results.
APPROACH
We developed a custom news filtration system, reducing manual review by 90%. Using open-source software, large language models, and transfer learning, we created a domain-specific solution tailored to their needs.
RESULT
The solution saves 20 hours of analyst time per week and has become part of 202 Group’s core product offering, enhancing operational efficiency and customer value.
Proven Expertise
The Rotational Difference
Tailored AI Solutions
We create customized AI/ML systems that directly address your business needs, ensuring impactful, scalable results.
Proven Expertise
We know how to train, deploy, and maintain AI solutions that maximize efficiency and ROI.
Sensible Tech
We use sensible, proven tech that delivers business value while ensuring your systems are future-proof for evolving needs.
End-to-End Support
From R&D to deployment and monitoring, we provide comprehensive services that ensure long-term success.
Security & Control
Your data stays within your environment—no third parties involved—ensuring full control and compliance.
Operational Impact
We focus on measurable outcomes that save costs, generate growth, or improve productivity for lasting business value.