ThinkingDBx

A foundry that trains domain-specific language models inside the customer's perimeter and delivers owned model weights, solving the problem of building capable AI when data cannot leave due to regulatory or security constraints and when only a few hundred examples exist. It sells to data, developer, and IT teams in regulated enterprises and government organizations that need private models. It is delivered air-gapped on customer hardware or on vendor hardware, starting from a corpus audit and including synthetic data expansion, gated training checks, and validated weight delivery.

Key features

• Trains models inside customer perimeter
• Delivers owned model weights
• Air-gapped deployment option
• Synthetic expansion from seed examples
• Decontamination against eval suite
• Corpus audit and tokenizer fit measurement
• Gated corpus and configuration checks
• Validation of weights before shipping