OnDeck AI
OnDeck 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
Y Combinator
yc-company-directory #3033OnDeck 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
sourceOnDeck AI 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 OnDeck AI
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.
Trieve
match 77Infrastructure 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
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
Unsiloed AI
match 74AI 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: vision, model; shared product terms: infrastructure, layer, vision, model; shared product theme: developer infrastructure; shared affiliation: Y Combinator
Zoa Research
match 67Historically, quantitative models are domain specific. Brilliant people spend their best years testing features, tuning hyperparameters, and iterating architectures within a narrow domain. But scale is the panacea: large models will find patterns people, and specialized models, could not. Forecasting generalizes. Zoa trains cross-domain event forecasting engines. *Automating Iteration* LLMs—embedded in multi-agent optimization loops and evaluated against fixed policies—can automate the build-tes
shared extracted concept terms: model; shared product terms: model, find, event, train; shared affiliation: Y Combinator
Osmosis
match 66Osmosis is a post-training platform that helps companies fine-tune language models using reinforcement learning. We work with fast-growing AI companies to train task/domain-specific models that beat foundation models on performance, cost, and latency. Our platform handles compute orchestration, reward modeling, and training run observability as a CLI-based product usable by developers and agents.
shared extracted concept terms: language, model; shared product terms: language, model, train, specific; shared product theme: developer infrastructure; shared affiliation: Y Combinator
CrowdAI
match 63CrowdAI equips enterprises of all sizes with the power of deep learning and the approachability and speed of no-code software. Our easy-to-master platform allows users of all technical abilities, from business operators to data scientists, to power real-time decisions from their visual world. Recognizing data as the new code, CrowdAI is the only vision AI platform to truly provide organizations with the infrastructure for the entire AI-lifecycle, empowering you to label data systematically, trai
shared extracted concepts: organizations; shared product terms: enterprise, vision, organization, infrastructure; shared product theme: developer infrastructure; same category: AI infrastructure; shared affiliation: Y Combinator
KugelAudio
match 48Kugel is an enterprise-ready TTS model, available on-prem, with a focus on 30+ languages and low latency.
shared extracted concept terms: enterprise, model; shared product terms: enterprise, model, language; same category: AI infrastructure; shared affiliation: Y Combinator