WonderSearch lets developers and AI agents search company files by meaning and pull back a cited passage, without an embedding pipeline, a vector database, or search servers to run. You upload documents, ask in ordinary language, and the service returns the relevant text with a source reference. The Y Combinator Fall 2026 launch is for teams wiring agents into existing knowledge, where finding a recent contract or policy still depends on a retrieval stack someone has to build and keep current. Search runs on WonderSearch's own model and is billed per query, with storage charged separately. A question can match a passage even when the wording differs from the document, and files become searchable after upload rather than after a separate embedding job. Teams use it on internal documents and research, or connect the same retrieval to a product, help center, or assistant through MCP, a REST API, a CLI, or a Python SDK. The service returns passages, document identifiers, and relevance scores. It does not write the final answer, so the application or model can respond and keep the citation. The company behind the product is Evokoa, Inc., in San Francisco. Co-founders are Dale Ng, CEO, and Dalton Prescott, CTO. English text is supported today, and each query can be run at a small, medium, or large effort setting.