If the team is here, would love to understand how it compares to something like Amplitude's agent analytics (https://amplitude.com/ai-agents).
We call Amplitude's feature an "AI Analyst". Essentially Amplitude is layering a LLM copilot on top of their own product - so you don't have to click the buttons or write reports to get insights.
We're an analytics platform built for tracking your agents. Different products with different problems they're solving.
Not sure if this helps, but essentially Amplitude could use Voker to track how well their AI Analyst agent product is actually working!
From what I can tell in this video, it still seems like Amplitude is focusing on the obs trace details (latency, tokens, etc).
They don't seem to go as deep (or at least don't highlight) as much of the semantic data processing and detection we're doing (intents, corrections, resolutions) - and creating higher level classifications and insights from those. We're completely purpose built for monitoring agent products, so we're striving to do more than just visualizations, we intend to be best-in-category at the actual automated annotations and analysis of agent<>user interaction data.