congratulations!
Launch HN: Voker (YC S24) – Analytics for AI Agents
11–20 of 36 posts
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#12Earlier quoted context omitted.
Yeah, this is a confusing one on wording. TLDR: Amplitude is analytics for your web/product data, Voker is analytics for your agent data. 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 di…
I think the link is off above, but they're thinking of Amplitude's not yet GA agent analytics, not their general analytics: https://amplitude.com/blog/agent-analytics
Thanks for clarifying - yes this is a much closer analog to what we're building. That being said, we haven't heard from anyone using it or tried it ourselves yet so can't speak to quality comparison.
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 agentuser interaction data.
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#13[flagged]
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#14How is it different than Langfuse? sorry if I am off the track but Langfuse also provides some detailed tracing of agentic behavior and decisions.
We get this question a lot! We work hand-in-hand with obs tools like Langfuse. Langfuse is great for debugging technical issues on individual traces like timing conditions that resulted in failed API calls. Voker focuses on product, business and user outcomes - like what intents did the user bring to your agent that you might not expect. We're built for the whole product team, whereas Langfuse focuses on engineers sp…
do you have experience as PMs? Looking at website, it looks like you just use llms to guess what categories are? Seems like trap for garbage in garbage out. Otherwise you would need someone technical to figure out how to setup the proper KPI monitoring things...
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#15Earlier quoted context omitted.
We get this question a lot! We work hand-in-hand with obs tools like Langfuse. Langfuse is great for debugging technical issues on individual traces like timing conditions that resulted in failed API calls. Voker focuses on product, business and user outcomes - like what intents did the user bring to your agent that you might not expect. We're built for the whole product team, whereas Langfuse focuses on engineers sp…
do you have experience as PMs? Looking at website, it looks like you just use llms to guess what categories are? Seems like trap for garbage in garbage out. Otherwise you would need someone technical to figure out how to setup the proper KPI monitoring things...
We do! We have combined experience as PMs, ml engs, and data scientists across many verticals. We also have experience helping PMs and AI eng teams build agents across over 100 customers from our first product.
You're totally right, the analytics annotation primitives we detect (intents, corrections, resolutions) are the cornerstone to all the other analysis in our platform. It's critical that we get those right or all the data and insights in the world are useless.
LLMs are a core part of that detection, but we also do things like hierarchical classification, (https://voker.ai/blog/hierarchical-text-classification-with-...) and will eventually add in other ML methods where applicable. On top of our automated detections, we're building ways for the annotations to improve and adapt to your specific agent product, your data, and your feedback on our annotations.
Our SDK is architected to eventually accept any type of event you want to send as additional information like add to carts, or other conversion metrics that are valuable for analysis on agent performance.
You're definitely right, we don't expect a PM to instrument this all themselves - similar to web analytics or product analytics tools, the engineering team instruments and maintains the integration, and then our app makes the insights and data accessible to not just the engineer but the whole product team.
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#16[flagged]
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#17[flagged]
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#18Earlier quoted context omitted.
do you have experience as PMs? Looking at website, it looks like you just use llms to guess what categories are? Seems like trap for garbage in garbage out. Otherwise you would need someone technical to figure out how to setup the proper KPI monitoring things...
We do! We have combined experience as PMs, ml engs, and data scientists across many verticals. We also have experience helping PMs and AI eng teams build agents across over 100 customers from our first product. You're totally right, the analytics annotation primitives we detect (intents, corrections, resolutions) are the cornerstone to all the other analysis in our platform. It's critical that we get those right or a…
Your response is AI. It's a bit ai sloppy as well. Sorry to say that. But as a business owner you can and should do better.
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#19Earlier quoted context omitted.
We do! We have combined experience as PMs, ml engs, and data scientists across many verticals. We also have experience helping PMs and AI eng teams build agents across over 100 customers from our first product. You're totally right, the analytics annotation primitives we detect (intents, corrections, resolutions) are the cornerstone to all the other analysis in our platform. It's critical that we get those right or a…
Your response is AI. It's a bit ai sloppy as well. Sorry to say that. But as a business owner you can and should do better.
haha oof that's embarrassing if I really sound like AI, but unfortunately it was written by hand by yours truly!
Guess its human-sloppy :(
Re: Launch HN: Voker (YC S24) – Analytics for AI Agents
#20How is it different than Langfuse? sorry if I am off the track but Langfuse also provides some detailed tracing of agentic behavior and decisions.
We get this question a lot! We work hand-in-hand with obs tools like Langfuse. Langfuse is great for debugging technical issues on individual traces like timing conditions that resulted in failed API calls. Voker focuses on product, business and user outcomes - like what intents did the user bring to your agent that you might not expect. We're built for the whole product team, whereas Langfuse focuses on engineers sp…
For instance, I have intent classifiers running on my traces and most tools offer some sort of analysis agents or API so it's claude sdk and go.
Maybe let's take Langsmith. Now I know my gripes with that product. How do you see it? What do you add, specifically?