Congrats on the launch. One complaint: RPA this, non-RPA that, but you never explain what it means. I would write down the acronym fully once at the first mention on the landing page.
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throw03172019
Biggest question is how much of this can be stored / processed on our own infra and with our own lifecycle rules? For example, this can touch a lot of PHI. Screenshots, videos, JSON inputs/outputs etc.
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throw03172019
Does this only revert back to LLM Vision when it catches an error? I.e once the RPA / workflow is built once, it’s efficient for running multiple times (until it catches an error state)?
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dragonsenseiguy
Small website nitpick: I feel like the "In production with" section's companies logos should be a bit darker, I could barely tell there was something there.
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ilundin
Is the cloud LLM the judge based on screenshots with patient/customer data included ? That seems like a no-go for many countries given privacy concerns ?
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a-dub
i'm curious: how does the steady state error rate of a stochastic automated system like this compare with the downtime and errors that come from a (brittle) deterministic bridge that can fail with upgrades? what does the observability look like? (i'm guessing one feature is that the execution log including images/screenshots for each transaction gets saved, which is probably a huge improvement.)
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throw03172019
How does this compare with CyberDesk (also YC)?
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theaniketmaurya
Congrats on the launch! Legacy system users are also one of the slowest to adopt AI. How do you navigate that?
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throw03172019
So AI companies would install this on their customer (practices) computers?
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mingabunga
Could you use this to test new releases of software for bugs? A bit like TDD but for GUI interactions
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snozolli
Computer use agents that run on Windows VMs or in the browser. On-premise, cloud
Congrats on the launch. One complaint: RPA this, non-RPA that, but you never explain what it means. I would write down the acronym fully once at the first mention on the landing page.
Biggest question is how much of this can be stored / processed on our own infra and with our own lifecycle rules? For example, this can touch a lot of PHI. Screenshots, videos, JSON inputs/outputs etc.
Does this only revert back to LLM Vision when it catches an error? I.e once the RPA / workflow is built once, it’s efficient for running multiple times (until it catches an error state)?
Small website nitpick: I feel like the "In production with" section's companies logos should be a bit darker, I could barely tell there was something there.
Is the cloud LLM the judge based on screenshots with patient/customer data included ? That seems like a no-go for many countries given privacy concerns ?
i'm curious: how does the steady state error rate of a stochastic automated system like this compare with the downtime and errors that come from a (brittle) deterministic bridge that can fail with upgrades? what does the observability look like? (i'm guessing one feature is that the execution log including images/screenshots for each transaction gets saved, which is probably a huge improvement.)
How does this compare with CyberDesk (also YC)?
Congrats on the launch! Legacy system users are also one of the slowest to adopt AI. How do you navigate that?
So AI companies would install this on their customer (practices) computers?
Could you use this to test new releases of software for bugs? A bit like TDD but for GUI interactions
Computer use agents that run on Windows VMs or in the browser. On-premise, cloud
I think you meant premises.
https://brians.wsu.edu/2016/05/30/premise-premises/
Please make your trust center public if you are focusing on healthcare AI companies…the footer link is dead.
What the deuce is an "RPA"?