Hi HN, we’re Yarik and Vlad from VOYGR (https://voygr.tech/), working on better real-world place intelligence for app developers and agents. Here’s a demo: https://www.youtube.com/watch?v=cNIpcWIE0n4.
Google Maps can tell you a restaurant is "4.2 stars, open till 10." Their API can't tell you the chef left last month, wait times doubled, and locals moved on. Maps APIs today just give you a fixed snapshot. We're building an infinite, queryable place profile that combines accurate place data with fresh web context like news, articles, and events.
Vlad worked on the Google Maps APIs as well as in ridesharing and travel. Yarik led ML/Search infrastructure at Apple, Google, and Meta powering products used by hundreds of millions of users daily. We realized nobody was treating place data freshness as infrastructure, so we're building it.
We started with one of the hardest parts - knowing whether a place is even real. Our Business Validation API (https://github.com/voygr-tech/dev-tools) tells you whether a business is actually operating, closed, rebranded, or invalid. We aggregate multiple data sources, detect conflicting signals, and return a structured verdict. Think of it as continuous integration, but for the physical world.
The problem: ~40% of Google searches and up to 20% of LLM prompts involve local context. 25-30% of places churn every year. The world doesn't emit structured "I closed" events - you have to actively detect it. As agents start searching, booking, and shopping in the real world, this problem gets 10x bigger - and nobody's building the infrastructure for it. We recently benchmarked how well LLMs handle local place queries (https://news.ycombinator.com/item?id=47366423) - the results were bad: even the best gets 1 in 12 local queries wrong
We're processing tens of thousands of places per day for enterprise customers, including leading mapping and tech companies. Today we're opening API access to the developer community. Please find details here: https://github.com/voygr-tech/dev-tools
We'd love honest feedback - whether it's about the problem, our approach, or where you think we're wrong. If you're dealing with stale place data in your own products, we'd especially love to hear what breaks. We're here all day, AMA.
30 comments
Bog-standard LLM mapping is terrible and I recently added Google Maps to my personal agent to remediate this.
I'd love to try Voygr for fun. Is there a skill defined that I could just swap in Voygr
Google also doesn't tell you if a place exists - it just returns the list of possible places which it thinks could be relevant. We have instructions defined for agents to onboard https://github.com/voygr-tech/dev-tools
I'm not sure I understand : how can you product help for opening times or pictures of my local boulangerie ? What kind of data sources will help you automate the reviewing of its attributes ?
We are not providing opening times yet - we just check if place is permanently closed or not. But it is in the works under our experimental enrichment API (which is not yet open to public)
This is a great idea, albeit one that will be really hard to pull off well but really valuable for developers if you're able to execute.
Definitely kind of a boil-the-ocean high-schlep startup but I would love to see this succeed.
Thanks, it is going to be fun! :)
Really cool! We're currently using map and web searches in our agent to gather this info for our tool. Does it support an approximate address? For example, if a plaza can have multiple street numbers, do I need to make a request for each possible address or would it find a certain business with an approximate address?
Thanks! Our initial API works as follows - you provide POI/business name and its address and we are telling you if it exists or not. So if you are looking to check if the plaza is existing, you just need to provide its supposed address. If it is a business within plaza, then an address of that business is required
Let me rephrase my question. How exact must the address input be? Do I need to include unit numbers? What if the street number is off by a few due to the layout of a plaza?
Using Maps or Web Search APIs, I can find approximate locations for certain businesses based on my input. Can your API work in a similar manner?
It is supposed to work if you even don't include unit number or a house number is a bit off. We analyze other signals too, so if the address is a bit off, the API is still supposed to mark a place as existing
Why not go with V'ger? Seems like a missed opportunity: https://en.wikipedia.org/wiki/List_of_Star_Trek_characters_(...
Indeed, we've been told about that. Hopefully, it won't be a defining moment for us as a company :)
I like the agent-first signup via API. Is this meant to be distributed as an agent skill?
Indeed, in the current age we need to build things for agents first. We think that the skills will primarily will be discovered through marketplaces or via web search
Implementing maps into our app so giving this a shot. How does pricing compare to google maps api?
It is on par with Google Maps API, but Google gives you more data. Our terms of service are more flexible - for instance we don't require attribution and deleting our data past 30 days. And we are actively working on adding more info to our APIs
what kinds of data quality evals do you guys use now? i'm curious to try integrating it
We are using judges with LLMs and web grounding plus manual grading. We recently did a benchmark on the LLM quality across major AI providers - we plan to open source it soon and will probably open source our API quality check benchmark too https://news.ycombinator.com/item?id=47366423
Who are your customers? Consumer or business?
Both - we're building APIs ultimately designed for AI agents and LLMs that need trustworthy place data and that includes cases from enterprise to personal people's agents
Its quite funny that you are building an "infinite place profile", you both worked on products used by 100s of millions of people, and yet your website is down from 45 minutes of HN traffic!
Joking, but its a very good idea. Synchronization between the physical world information and digital has been a very hard problem for decades and im sure an agentic approach can 10x the value.
Thanks! Was it truly down? I have checked and I don't see any disruptions
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We work in this space and have found that, very often, the realities on the ground do not match the digital information, especially when it comes to geospatial data, where businesses exist, what businesses actually exist, and their status. At Rwazi, we have millions of users helping collect on-the-ground data.
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