WhatPre-fine-tuned, domain-specific LLMs sold as API endpoints for regulated verticals like legal, healthcare, and finance — where RAG alone falls short on specialized reasoning.
SignalCommenters debate whether fine-tuning still matters versus RAG, but multiple practitioners point out that specialized fine-tuned models consistently beat state-of-the-art general models on domain tasks, and that stuffing massive context windows with enterprise knowledge bases is neither practical nor performant for real-time applications.
Why NowOpen models now match GPT-4-class quality as base models, meaning a fine-tuned 70B open model can surpass closed API performance on narrow tasks — this was not possible even 6 months ago.
MarketLegal tech, compliance, and healthcare AI buyers paying $100K+/yr for AI tools; TAM $5B+; gap is that current vertical AI startups mostly use RAG on closed models rather than owning fine-tuned open models.
MoatCurated, licensed domain training data and validated benchmark performance on industry-specific evaluations create high switching costs once customers integrate.
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