Auto ML Platform
Project Details
Enterprise infrastructure that allows organizations to securely train, deploy, and scale custom machine learning models on their proprietary company data.
The Challenge
Enterprises want to train ML models on local documentation without sending confidential data to public APIs. Our client needed a self-contained training platform that secures corporate intellectual property.
Architectural Solution
Deployed custom open-source Mistral models inside a secure Kubernetes cluster. Created a pipeline that indexes files into vector DBs (RAG) inside the firewall, preventing outbound internet calls and establishing data sandboxing.
Business Outcome
Zero corporate IP data leaks. Trained 12 custom LLM models for 4 distinct business units, automating customer service pipelines.
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