Who AI recommends, and when it changes.
Data as of Apr 10, 2026 · Based on 20 AI answers · A buyer need in LLM Fine-Tuning Platforms. · See how Parse measures this
Recommendation share
Glean leads at 15% of AI recommendations; Modulai follows at 10%.
By platform
Platforms disagree: Glean leads on Google AI Overviews, Adaptive ML on ChatGPT.
Representative prompts behind this market ranking, and how AI tends to answer.
Why here: Builds custom per-customer embedding models for enterprise search and RAG. · 2 sources
Why here: Consultancy adapting embedding models to niche fields with specialized jargon. · 2 sources
Why here: Provides AI solutions and domain-specific adaptation for embedding pipelines. · 2 sources
Why here: Offers pre-trained domain-specific embedding models for legal and finance. · 2 sources
Why here: Tools for customizing open-source models, including embedding adaptation. · 1 source
Why here: Advanced embed models (v3) trainable on proprietary datasets for slang. · 1 source
Why here: Enterprise generative AI retrieval tooling for specialized vocabularies. · 1 source
Why here: Helps build custom LLM and RAG systems with fine-tuned embedding models. · 1 source
Why here: Embeddings as a service, training and fine-tuning on proprietary data. · 1 source
Why here: Fine-tuning services adapting models to domain-specific jargon in private environments. · 1 source
Why here: Provides recipes for embedding fine-tuning, used to improve retrieval accuracy. · 1 source
AI assistants most frequently direct buyers seeking domain-adapted embeddings to 
Where a different pick wins:
Voyage AIPre-trained domain-specific embedding models for legal and financial terminology. · 2 sources
“Our semantic search misses queries using industry slang. Who provides domain-adaptation services for embedding models?”
AI assistants respond with a broad list of providers that customize embedding models for industry terminology.
Specializes in fine-tuning within private environments for domain-specific jargon. · 1 source
Modulai
