ModelBrew

ModelBrew lets you fine-tune open-weight models, add new domains without overwriting previous training, and govern dynamic facts outside the model weights. The platform features Live Knowledge, which keeps facts in a searchable bank and produces verifiable erasure certificates whenever a fact is removed. It is designed for developers and organizations that need reproducible training, transparent data cleaning, and verifiable fact governance without expensive infrastructure.

Unlike traditional fine-tuning where updating a model can cause catastrophic forgetting or drift, ModelBrew uses a Constrained Residual Mixing Adapter (CRMA) to chain domains sequentially while keeping the base model stable. Users can clean datasets before training, fine-tune models ranging from 1.1B to 14B parameters, and deploy live knowledge banks either in the cloud or on-premise in a governed VPC.