Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
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Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#2[dead]
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#3This is super interesting. If it is fast enough, I would like to try on my product site.
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#4This is super interesting. If it is fast enough, I would like to try on my product site.
Yes, founding agent is powered by Moss’s sub-10 ms retrieval under the hood. Typical retrieval systems can take anywhere between 200-500 ms per turn which kills the experience of live conversation. With the help of Moss, we are able to make Founding Agent converse like human.
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#5Absolute need ! Does it work well with a very dense website ?
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#6Absolute need ! Does it work well with a very dense website ?
Yes it does! It all boils down to the retrieval speed and quality. And Moss is primarily built for this purpose which is now powering the Founding Agent.
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#7Amazing
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#8Looks promising. Curious how it scales as the amount of content grows.
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#9Looks promising. Curious how it scales as the amount of content grows.
You asked the right question that's blocking many people from productionizing this kind of solution on their website. If we break down the anatomy of the Voice Agent, it looks like this
STT -> Ambient Retrieval(Moss) -> LLM [+ Tool calls -> On-Demand Retrieval(Moss)] -> TTS
Now STT, TTS and LLM output generation are fixed cost and independent of data scales. In reality, a typical landing page and public-facing website content will range from 100's of docs (for startups) to 100K's of docs (for enterprises).
Moss's retrieval stack runs sub-10 ms with the following internal benchmarks -
- P99 of ~5.4 ms for 100K docs in a shared container
- P99 of ~4 ms for 1M docs in a dedicated VM
our R&D team is cranking it to 200M+ docs with sub-10ms promise but sky is the limit for our scale.
Re: Show HN: We put voice agent on our website, learned retrieval isn't bottleneck
#10Amazing
Thank you!