Reprompt (YC W24)

New product: Find Places in Reprompt We've been heads down building product (my absolute favorite way to operate), but it's time to share some exciting things over the next few weeks. Today: We've built the easiest way to Find Places and enrich them, all in one AI-powered swoop. Customers are starting to use it for: -Leadgen: Get me the phone numbers for every Plumber in America -Point of Interest enrichment: Get the opening hours for every hardware store in Austria -Site selection: Find all the Daves Hot Chickens which have drive thrus and more than 30 parking spaces

😯 I've been working on Scout, a location agent that roams, analyzes, and can enrich location data with street-level vision. Scout has an extensible environment to freely explore. Today is an integration with Google Maps and an open-vocabulary detection model and now we're integrating other street-level imagery providing. Joining Reprompt (YC W24) has been a challenging and rewarding experience to take on geospatial problems. Scout is a massive leap forward to solve many problems related to delivery, rideshare, POI, and other highly valuable tasks that take humans minutes if not hours to complete. Today, Scout can essentially, 👉 Enrich information about a location with a combination of tools like object detection and captioning. 👉 Decide combinations of tools to solve problems and assign them to more specialized workflows or agents. 👉 Completely control an integrated UI in real-time. 👉 Do tons of quick math to get more relevant views derived from a view of interest (the zoom effect). 👉 Extend with other tools and functions (Kepler, Mapbox) 👉 Return JSON about target attributes given a series of addresses. If enough interest, I'll share a more in-depth article about its inner workings and how it (somehow) was built without any LLM frameworks. We're also looking for talent to find creative ways--much like this agent--to solve difficult geospatial problems.

🚀 Innovation is all about making the right decisions at the right time. In this conversation with Reprompt (YC W24), Foursquare CTO Vikram Gundeti explains the thinking behind our latest product releases—how we’re pushing the boundaries of location tech, solving real-world challenges, and shaping the future of geospatial data. 🌍✨ Jump to the comments for the link to the full video 👇 #Foursquare #Innovation #LocationTech #AI

Humans 🤝 Agents: Vikram Gundeti explains how Foursquare's vision involves both Humans and Agents collaborating to create the most accurate place data possible. Beside’s the community there are three workforces contributing to Foursquare data: 1. Human workforces in a call center browsing the web and calling businesses and using their local knowledge to update and add places. 2. On-the-ground apps: Users provide real-time corrections and updates directly from their devices. 3. Agents like Reprompt handling tasks at massive scale continually learning from human feedback to match human-level quality. Why are agents like Reprompt so valuable? - They scale tasks that would be impossible for a single person or even a large team. - They reduce costs by automating repetitive work. - They monitor signals—like social media chatter—to see if places are opening, closing, or changing their hours in real time - impossible for a human workforce to do.