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Lyon

Foundation models on event data

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Lyon trains a foundation model from scratch on customer event data, producing customer embeddings that feed downstream predictions. It addresses the recurring work of building separate feature pipelines for each task, supporting churn, credit risk, fraud, collections, income, and cross-sell from a single model. Existing features can be passed to downstream models alongside the embeddings.

Fine-tuning works through task adapters: select a label table, verify the split, and start a LoRA fine-tune. Training and inference run inside your VPC on AWS, GCP, or Azure, so data and models remain in your cloud. The platform is described with SOC 2, GDPR, and LGPD compliance.

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