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
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maelito
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 ?
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acombandrew
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.
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amir_karbasi
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?
I like the agent-first signup via API.
Is this meant to be distributed as an agent skill?
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frankdenbow
Implementing maps into our app so giving this a shot. How does pricing compare to google maps api?
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thesiti92
what kinds of data quality evals do you guys use now? i'm curious to try integrating it
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macrolet
Who are your customers? Consumer or business?
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deepdarkforest
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.
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dk8996
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.
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
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 ?
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.
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?
Why not go with V'ger? Seems like a missed opportunity: https://en.wikipedia.org/wiki/List_of_Star_Trek_characters_(...
I like the agent-first signup via API. Is this meant to be distributed as an agent skill?
Implementing maps into our app so giving this a shot. How does pricing compare to google maps api?
what kinds of data quality evals do you guys use now? i'm curious to try integrating it
Who are your customers? Consumer or business?
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.
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.