VOYGR

VOYGR helps AI apps and agents understand and act in the real world with comprehensive place data. Unlike static mapping APIs, VOYGR combines accurate place intelligence with fresh web context – news, articles, and events. Real-world interactions rely on maps: 10M+ apps/websites, up to 40% of search queries, and 20% of LLM prompts need local context. Yet a restaurant recommendation can fail because the place is closed, menus aren’t searchable, or delivery goes to the wrong entrance. AI pushes expectations further – answering semantic prompts like “specialty coffee shops in SF with Wi-Fi and YC founders", and taking actions like making reservations or placing orders. We’re experienced builders in maps, search, and ML to solve this. Vlad knows this space inside and out – he worked on the Google Maps APIs GTM, plus firsthand customer experience from building in ridesharing and travel. Yarik has spent over a decade leading ML/search teams at Apple, Google, and Meta. Several customers already run VOYGR to continuously validate places data accuracy at scale, and we outperform on accuracy and coverage. Maps were built for humans browsing pins; agents need continuously updated place ground truth they can act on – from copilots and in-car assistants to delivery robots and AR. As agents become the interface to commerce and services, VOYGR aims to be the default ground-truth layer.