Add source Login
Google is phasing out its Privacy Sandbox technologies; the initiative was launched in 2019 to develop privacy-protecting tech to replace third-party cookies (Kendra Barnett/Adweek)

Google is phasing out its Privacy Sandbox technologies; the initiative was launched in 2019 to develop privacy-protecting tech to replace third-party cookies (Kendra Barnett/Adweek)

Kendra Barnett / Adweek : Google is phasing out its Privacy Sandbox technologies; the initiative was launched in 2019 to develop privacy-protecting tech to replace third-party cookies —  The elimination of many remaining Privacy Sandbox APIs come six months after third-party cookies got a reprieve in Chrome.

Developers can now add live Google Maps data to Gemini-powered AI app outputs

Developers can now add live Google Maps data to Gemini-powered AI app outputs

Google is adding a new feature for third-party developers building atop its Gemini AI models that rivals like OpenAI's ChatGPT, Anthropic's Claude, and the growing array of Chinese open source options are unlikely to get anytime soon: grounding with Google Maps. This addition allows developers to connect Google's Gemini AI models' reasoning capabilities with live geospatial data from Google Maps, enabling applications to deliver detailed, location-relevant responses to user queries—such as business hours, reviews, or the atmosphere of a specific venue. By tapping into data from over 250 million places, developers can now build more intelligent and responsive location-aware experiences. This is particularly useful for applications where proximity, real-time availability, or location-specific personalization matter—such as local search, delivery services, real estate, and travel planning. When the user’s location is known, developers can pass latitude and longitude into the request to enhance the response quality. By tightly integrating real-time and historical Maps data into the Gemini API, Google enables applications to generate grounded, location-specific responses with factual accuracy and contextual depth that are uniquely possible through its mapping infrastructure. Merging AI and Geospatial Intelligence The new feature is accessible in Google AI Studio, where developers can try a live demo powered by the Gemini Live API. Models that support the grounding with Google Maps include: Gemini 2.5 Pro Gemini 2.5 Flash Gemini 2.5 Flash-Lite Gemini 2.0 Flash In one demonstration , a user asked for Italian restaurant recommendations in Chicago. The assistant, leveraging Maps data, retrieved top-rated options and clarified a misspelled restaurant name before locating the correct venue with accurate business details. Developers can also retrieve a context token to embed a Google Maps widget in their app’s user interface. This interactive component displays photos, reviews, and other familiar content typically found in Google Maps. Integration is handled via the generateContent method in the Gemini API, where developers include googleMaps as a tool. They can also enable a Maps widget by setting a parameter in the request. The widget, rendered using a returned context token, can provide a visual layer alongside the AI-generated text. Use Cases Across Industries The Maps grounding tool is designed to support a wide range of practical use cases: Itinerary generation: Travel apps can create detailed daily plans with routing, timing, and venue information. Personalized local recommendations: Real estate platforms can highlight listings near kid-friendly amenities like schools and parks. Detailed location queries: Applications can provide specific information, such as whether a cafe offers outdoor seating, using community reviews and Maps metadata. Developers are encouraged to only enable the tool when geographic context is relevant, to optimize both performance and cost. According to the developer documentation, pricing starts at $25 per 1,000 grounded prompts — a steep sum for those trafficking in numerous queries. Combining Search and Maps for Enhanced Context Developers can use Grounding with Google Maps alongside Grounding with Google Search in the same request. While the Maps tool contributes factual data—like addresses, hours, and ratings—the Search tool adds broader context from web content, such as news or event listings. For example, when asked about live music on Beale Street, the combined tools provide venue details from Maps and event times from Search. According to Google, internal testing shows that using both tools together leads to significantly improved response quality. Customization and Developer Flexibility The experience is built for customization. Developers can tweak system prompts, choose from different Gemini models, and configure voice settings to tailor interactions. The demo app in Google AI Studio is also remixable, enabling developers to test ideas, add features, and iterate on designs within a flexible development environment. The API returns structured metadata—including source links, place IDs, and citation spans—that developers can use to build inline citations or verify the AI-generated outputs. This supports transparency and enhances trust in user-facing applications. Google also requires that Maps-based sources be attributed clearly and linked back to the source using their URI. Implementation Considerations for AI Builders For technical teams integrating this capability, Google recommends: Passing user location context when known, for better results. Displaying Google Maps source links directly beneath the relevant content. Only enabling the tool when the query clearly involves geographic context. Monitoring latency and disabling grounding when performance is critical. Grounding with Google Maps is currently available globally, though prohibited in several territories (including China, Iran, North Korea, and Cuba), and not permitted for emergency response use cases. Availability and Access Grounding with Google Maps is now generally available through the Gemini API. With this release, Google continues to expand the capabilities of the Gemini API, empowering developers to build AI-driven applications that understand and respond to the world around them.