Very cool. I liked the high level overview where you can view it like do a funnel analysis for failures. Good for fast decision making.
I wonder if you have thought of using this for the voice AI space for creating traces from many test calls to speed up testing of voice bots? It's true there are a lot of challenges _before_ one gets to the stage of running actual calls like creating good test data etc, but I wonder if you see a definite role for this framework in that space?
>for creating traces from many test calls to speed up testing of voice bots
I assume you mean tracing voice agents in general. If so, it depends on the where do you want to trace things. Right now, Laminar, unfortunately, doesn't trace voice SDKs like OpenAI's realtime, but we're very actively looking into it.
However, if somewhere in your pipeline you have transcripts of your voice agents, then it shouldn't be that different from tracing any other agent. In this case, Laminar and Signals work perfectly.
We also trained and benchmarked flow-1 on a lot of multi-turn voice agent like conversations.
Congrats on the product! I love the design of the website and the app. Curious whether it was made in-house, by an external design agency, with AI models, or something else
Very cool. I liked the high level overview where you can view it like do a funnel analysis for failures. Good for fast decision making.
I wonder if you have thought of using this for the voice AI space for creating traces from many test calls to speed up testing of voice bots? It's true there are a lot of challenges _before_ one gets to the stage of running actual calls like creating good test data etc, but I wonder if you see a definite role for this framework in that space?
>for creating traces from many test calls to speed up testing of voice bots
I assume you mean tracing voice agents in general. If so, it depends on the where do you want to trace things. Right now, Laminar, unfortunately, doesn't trace voice SDKs like OpenAI's realtime, but we're very actively looking into it.
However, if somewhere in your pipeline you have transcripts of your voice agents, then it shouldn't be that different from tracing any other agent. In this case, Laminar and Signals work perfectly.
We also trained and benchmarked flow-1 on a lot of multi-turn voice agent like conversations.
Congrats on the product! I love the design of the website and the app. Curious whether it was made in-house, by an external design agency, with AI models, or something else
Thanks! Our design is all done completely in-house.
Workflows are constantly changing but our design process happens across Figma, old-fashioned paper, and code.