Launching today
Voker
The Agent Analytics Platform for AI Product Teams
60 followers
The Agent Analytics Platform for AI Product Teams
60 followers
Voker is the Agent Analytics Platform for AI product teams. It gives you the usage behavior and agent performance insights you need to monitor and optimize your production agents at scale. Install the lightweight, provider agnostic SDK and Voker handles the rest: automatic intent, correction and resolution detection on your user to agent interactions, conversation reconstructions, queryable timelines, agent performance tracking so you can build the best agents possible.
Voker
I’m Tyler - CoFounder of Voker, and I’m so tired of being disappointed by AI hype claims. I bet you are too.
I studied physics in college, and worked in data science, ML, and analytics until founding Voker. I’m a skeptical person by nature (I think it's the scientist in me) and my gut reaction to any technology hype is to be cautiously optimistic until I see things proven out in data.
I felt this way about LLMs when they first hit mainstream. I knew they had real potential applications, but was also worried about the lofty marketing buzz they were getting.
AI as an industry has written checks that individual builders are left to cash. Promising full automation, PhD-level intelligence, and perfect results. As someone who's skeptical of that narrative, I still believe agents can genuinely deliver, but only if teams are rigorous about measuring performance in production. Every website or product has Amplitude or PostHog for click and pageview analytics; a standard way to understand who's using it and how. Agents have no equivalent, so we built Voker.
We are the Agent Analytics Platform where you can:
- Monitor your agents
- Measure their performance
- See what users are asking
- Know for certain agents are delivering for your users
- Optimize based on real data
You install our SDK, and Voker collects your agent conversation data, automatically detecting:
- User intents (Book me a hotel in Vegas for next Saturday with a poolside view)
- Corrections (No, that room doesn’t have a poolside view!! TRY AGAIN)
- Agent resolutions (Tool Result: Room Booked... Success!)
These automated annotations are the foundation for building a holistic view of agent performance and user behavior in one analytics platform.
We asked 100+ AI founders, product managers, and agent engineers how they monitor their agents in production and the answer was resounding: by combing through individual traces (with the occasional evals sprinkled in). They all reported that they depend on customer complaints to tell them when agents are messing up. We feel strongly that there is a third leg of the agent monitoring stool missing - Agent Analytics.
You shouldn’t have to wait for users to complain to learn that a recent prompt change is breaking your hotel booking agent, or that the AI finance advisor you built is calling the wrong tool to look up realtime stock prices.
Turns out the antidote to AI hype is simple: measure your agents diligently, then iterate until you get it right.
Your users deserve better AI experiences (we all do)!
Install the Voker SDK on our free tier (up to 2,000 events/mo), and start building better agents today:
https://voker.ai/
Love the brutal honesty here AI has definitely written checks that devs are stuck cashing in production. Quick question on the SDK: how does it handle semantic variations for corrections? Will it catch things like actually scratch that versus no that's wrong out of the box, or do we need to train it on our own domain vocabulary?
Voker
@vikramp7470 Good question - Voker will detect those kind of phrases, even with semantic variation. That being said, if you have super specific domain vocabulary, where two words might mean the same thing to a lay-person but not to you as a domain expert - then you will need to pass Voker some context in the form of either knowledge docs or feedback on our annotations (APIs for these are in the works!)
thanks Vikram!
Autumn
amazing team building something that’s really needed! Congrats on the launch 💗
Voker
@ay_ush Appreciate you guys! Autumn has made billing seamless - and for a small but mighty team like ours that's a huge time saver and value add. Esp love that you're purpose built for AI products <3