Trieve
Infrastructure for search teams building retrieval and RAG. Trieve combines search language models with tools for tuning ranking and relevance. Building excellent search is difficult and can take months to implement then even more time to maintain. Trieve offers production-ready infrastructure that works out of the box to help search teams build adjustable AI search and RAG into their products. With tools for custom models, relevancy weighting, date-recency biasing, semantic full-text hybrid sea
Y Combinator
yc-company-directory #5650Infrastructure for search teams building retrieval and RAG. Trieve combines search language models with tools for tuning ranking and relevance. Building excellent search is difficult and can take months to implement then even more time to maintain. Trieve offers production-ready infrastructure that works out of the box to help search teams build adjustable AI search and RAG into their products. With tools for custom models, relevancy weighting, date-recency biasing, semantic full-text hybrid sea
sourceTrieve is classified as AI infrastructure from source descriptions and fund-directory context. Similar companies below are ranked from offline product facets and meaningful description overlap; category and source affiliation can only strengthen an existing product match. For lookup-created rows, the profile starts as pending enrichment until deeper source collection runs.
Local clusters rerank extracted product concepts and description terms. The generated graph remains the fallback for sparse descriptions: offline reciprocal product-similarity graph: extracted concepts + description terms + bounded category/affiliation boosts. Minimum fallback score: 0; max competitors: 6.
Companies similar to Trieve
A deterministic local cluster built from offline product facets and meaningful description terms. Category and selected-institution affiliation provide bounded tie-breaks. Open any peer to continue exploring its cluster.
Unsiloed AI
match 82AI teams spend 6+ months building document workflows, yet fewer than 10% ever reach production. Generic LLM parsers and OCR collapse on multimodal documents with text, tables, images, and charts. Poor parsing and suboptimal chunking cripple RAG pipelines and downstream automation. Unsiloed AI has built state-of-the-art vision models which serves as the infrastructure layer for turning unstructured data into structured, queryable, and LLM-ready assets. Our APIs are already parsing hundreds of tho
shared extracted concept terms: model, rag; shared product terms: infrastructure, rag, model, month; shared product theme: developer infrastructure; shared affiliation: Y Combinator
OnDeck AI
match 77OnDeck is the infrastructure layer that makes Vision Language Models accessible and scalable for enterprise. We let organizations instantly find any object, behavior or event, in any footage, without needing to train a model or collect any training data. The Pain: Creating vision models usually takes months: collecting training data, training, then deployment. Worse yet: + it’s often impossible to get enough data for a specific task, and + even the best cv models struggle to generalize across di
shared extracted concept terms: language, model; shared product terms: infrastructure, language, model, take; shared product theme: developer infrastructure; same category: AI infrastructure; shared affiliation: Y Combinator
Nee AI
match 55Nee AI optimizes large language models (LLMs) with real-time evaluation and correction, reducing hallucinations, bias, and evaluation time by up to 80%.
shared extracted concept terms: language, model; shared product terms: language, model, time, bias; same category: AI infrastructure
Sapling.ai
match 50Sapling offers an API and SDK to help businesses integrate language models into their applications. Its messaging assistant sits on top of CRMs and messaging platforms to help users more efficiently compose responses.
shared extracted concept terms: language, model; shared product terms: offer, language, model; shared product theme: developer infrastructure; shared affiliation: Y Combinator
Versori
match 49Orchestrate custom integrations, workflows & agents in hours, not months. Take control of your integration strategy and breathe easy with maintenance on AI Autopilot. For Product Teams: Build better integration libraries. Build a feature-rich integration library, for your users to enjoy. Offer out-of-the-box integrations that work for you and your customers. Embedded IPaaS typically locks you into connector or endpoint limitations. Versori gives you to tools for limitless customisation. Proactiv
shared product terms: take, month, offer, out; shared affiliation: Y Combinator
Relace
match 46Relace makes it easy to deploy production-ready coding agents. Our models are co-optimized with infrastructure to achieve SoTA performance: 10k+ token/s code merging and retrieval across million-line repositories in seconds.
shared product terms: production, ready, model, infrastructure; shared product theme: developer infrastructure; shared affiliation: Y Combinator