InfoCert replaces custom ML models with Amazon Bedrock GenAI, projecting 80% lower onboarding costs

Overview

InfoCert, a European provider of trusted digital communication solutions, evolved its Intelligent Multichannel Classification and Routing (IMCR) email/document processing system into IMCR AI, replacing months-long custom ML model training with Amazon Bedrock foundation models and prompt engineering. The proof of concept achieved classification results close to the prior custom system while InfoCert projects an 80% reduction in startup, development and configuration costs and a 20% reduction in ongoing running costs when onboarding new customers.

The challenge

InfoCert previously built custom ML models to classify and process emails and attachments for each Legalmail customer; training and deploying these models was a lengthy, costly process requiring months for data preparation, model training and rules definition, which limited access to larger companies.

The solution

InfoCert conducted a proof of concept combining Amazon Bedrock's generative foundation models with prompt engineering to evolve its Intelligent Multichannel Classification and Routing (IMCR) system into IMCR AI, offering a unified workflow suitable for customers with small-to-moderate information extraction needs, moving from a custom per-customer ML approach to a general solution requiring minimal adjustments and no model training.

Reported business value

InfoCert anticipates a decrease in the time required for model definition, training and refining, measured in weeks instead of months, projects an 80% reduction in startup, development and configuration costs when onboarding new customers, and expects a 20% reduction in ongoing running costs, with preliminary classification results close to the prior custom-trained system.