As AI adoption accelerates, companies often develop thousands of siloed models, each for a narrow use case, creating unnecessary redundancy and driving up costs. For example. AI-GO is a novel AI governance platform designed to address the growing challenge of “AI model sprawl.” It provides companies with complete visibility into their deployed AI landscape, monitors usage and performance, and applies advanced analytics to identify opportunities for model consolidation.
The key features of AI-Go are:
1.A catalogue of AI models with runtime metrics and metadata.
2.Benchmarking algorithms to assess performance, value, and efficiency.
3.AI consolidation recommendations based on multi-domain and multi-modal capabilities.
The goal is to reduce the number of redundant models in production while maintaining or improving output quality and business value. The platform will deliver open-source software, published results, and tangible cost-saving metrics.
Expected Impact
1.Cost & Efficiency Gains: Enables organisations to reduce AI operational expenditure by consolidating underused or redundant models
2.Sustainability at Scale: Reduces the carbon footprint of large AI deployments.
3.Commercialisation: Creates a licensable platform and a high-tech startup
