Product trust takes months to build
- and one bad AI response to break
Product trust takes months to build - and one bad AI response to break
Product trust takes months to build - and one bad AI response to break
Teams are losing time, confidence, and customers to hidden friction in the AI development cycle. Get clarity before it’s too late.
Friction has a pattern
Friction has a pattern
It shows up in every stage of your feedback loop — from discovery to measurement.
Logs won’t show you where users struggle
Logs don’t reveal friction or failure points, leaving PMs blind to user struggles
Spreadsheets overwhelm your SMEs
Raw data with no direction leaves SMEs confused and unable to give meaningful feedback.
The tools you have can’t capture user emotion
They show activity, not frustration or drop-offs caused by poor AI interactions.
The tools you have can’t capture user emotion
They show activity, not frustration or drop-offs caused by poor AI interactions.
The feedback loop is disconnected
Customer drop-offs go unexplained while key voices stay out of the loop.
The feedback loop is disconnected
Customer drop-offs go unexplained while key voices stay out of the loop.
The feedback system for
modern AI teams
The feedback system for
modern AI teams
Verse shows you what's broken in your AI application and how to fix it
See fewer conversations—learn far more
Bring forward the most impactful conversations and the surrounding context, so you can quickly understand user experience quality and prioritize improvements.
Find issues fast, even if you’re not technical
Utilize a simple, intuitive interface for reviewing conversations, so you can quickly spot friction, understand user context, and share insights across your team.
See your agent improve with every iteration
Bring all your structured feedback together, so you can clearly track performance gains and watch user experience strengthen over time.
FAQ
How is Verse different from other options?
We sit between your users and your AI, capturing the insights and user interactions most tools miss. We enable and drastically speed up the unglamorous work of manually labelling errors within your product and having that lead to product improvement. We are able to combine your expert knowledge with our AI to identify errors specific to your project that other fully automated solutions would miss
Where does Verse fit into my tech stack?
We complement products like Langfuse and Braintrust by solving the collaboration and workflow problems present, and provides a low barrier entry-point and natural first step to identifying issues in your AI product. Observability tools don't address systematically gathering, organizing, and validating feedback from stakeholders to guide engineering improvements.
How is Verse different from other options?
Most tools give you metrics (drop-off rates, sentiment scores) or technical traces (token counts, latency). Verse shows which conversations frustrated users and why. When your PM sees a drop-off spike, they're stuck manually reviewing hundreds of conversations to understand what's broken. When your domain expert needs to weigh in, you're exporting CSVs they can't actually use. Verse surfaces the conversations where users struggled and makes it easy for your whole team to review and provide feedback. Not generic sentiment analysis - your team teaching the system what quality means for your specific product. The result: you find problems proactively instead of through churn, and your whole team can contribute directly.
Where does Verse fit into my tech stack?
Verse complements your observability stack—it doesn't replace it. If you're logging traces with Langfuse, LangSmith, Datadog, or Braintrust, you can pipe that data into Verse. Observability tools answer "what happened" technically. This is great for engineers debugging specific executions. Verse answers "why users struggled in conversations" and "what to prioritize" by surfacing patterns across thousands of interactions and helping cross-functional teams focus on fixes that improve user experience. The key difference: when your PM or domain expert needs to understand where your conversational AI is breaking down, observability tools force you into CSV exports and coordination meetings. Verse eliminates that. Everyone reviews actual conversations and contributes directly.
What does getting started with Verse look like?
Sign up for the waitlist. We'll provide updates as we build, and you can contact our team directly during this period. We'll help you connect your traces and once connected, you can start surfacing issues and gathering feedback from your team immediately.
How is Verse different from other options?
We sit between your users and your AI, capturing the insights and user interactions most tools miss. We enable and drastically speed up the unglamorous work of manually labelling errors within your product and having that lead to product improvement. We are able to combine your expert knowledge with our AI to identify errors specific to your project that other fully automated solutions would miss
Where does Verse fit into my tech stack?
We complement products like Langfuse and Braintrust by solving the collaboration and workflow problems present, and provides a low barrier entry-point and natural first step to identifying issues in your AI product. Observability tools don't address systematically gathering, organizing, and validating feedback from stakeholders to guide engineering improvements.
How is Verse different from other options?
Most tools give you metrics (drop-off rates, sentiment scores) or technical traces (token counts, latency). Verse shows which conversations frustrated users and why. When your PM sees a drop-off spike, they're stuck manually reviewing hundreds of conversations to understand what's broken. When your domain expert needs to weigh in, you're exporting CSVs they can't actually use. Verse surfaces the conversations where users struggled and makes it easy for your whole team to review and provide feedback. Not generic sentiment analysis - your team teaching the system what quality means for your specific product. The result: you find problems proactively instead of through churn, and your whole team can contribute directly.
Where does Verse fit into my tech stack?
Verse complements your observability stack—it doesn't replace it. If you're logging traces with Langfuse, LangSmith, Datadog, or Braintrust, you can pipe that data into Verse. Observability tools answer "what happened" technically. This is great for engineers debugging specific executions. Verse answers "why users struggled in conversations" and "what to prioritize" by surfacing patterns across thousands of interactions and helping cross-functional teams focus on fixes that improve user experience. The key difference: when your PM or domain expert needs to understand where your conversational AI is breaking down, observability tools force you into CSV exports and coordination meetings. Verse eliminates that. Everyone reviews actual conversations and contributes directly.
What does getting started with Verse look like?
Sign up for the waitlist. We'll provide updates as we build, and you can contact our team directly during this period. We'll help you connect your traces and once connected, you can start surfacing issues and gathering feedback from your team immediately.
How is Verse different from other options?
We sit between your users and your AI, capturing the insights and user interactions most tools miss. We enable and drastically speed up the unglamorous work of manually labelling errors within your product and having that lead to product improvement. We are able to combine your expert knowledge with our AI to identify errors specific to your project that other fully automated solutions would miss
Where does Verse fit into my tech stack?
We complement products like Langfuse and Braintrust by solving the collaboration and workflow problems present, and provides a low barrier entry-point and natural first step to identifying issues in your AI product. Observability tools don't address systematically gathering, organizing, and validating feedback from stakeholders to guide engineering improvements.
How is Verse different from other options?
Most tools give you metrics (drop-off rates, sentiment scores) or technical traces (token counts, latency). Verse shows which conversations frustrated users and why. When your PM sees a drop-off spike, they're stuck manually reviewing hundreds of conversations to understand what's broken. When your domain expert needs to weigh in, you're exporting CSVs they can't actually use. Verse surfaces the conversations where users struggled and makes it easy for your whole team to review and provide feedback. Not generic sentiment analysis - your team teaching the system what quality means for your specific product. The result: you find problems proactively instead of through churn, and your whole team can contribute directly.
Where does Verse fit into my tech stack?
Verse complements your observability stack—it doesn't replace it. If you're logging traces with Langfuse, LangSmith, Datadog, or Braintrust, you can pipe that data into Verse. Observability tools answer "what happened" technically. This is great for engineers debugging specific executions. Verse answers "why users struggled in conversations" and "what to prioritize" by surfacing patterns across thousands of interactions and helping cross-functional teams focus on fixes that improve user experience. The key difference: when your PM or domain expert needs to understand where your conversational AI is breaking down, observability tools force you into CSV exports and coordination meetings. Verse eliminates that. Everyone reviews actual conversations and contributes directly.
What does getting started with Verse look like?
Sign up for the waitlist. We'll provide updates as we build, and you can contact our team directly during this period. We'll help you connect your traces and once connected, you can start surfacing issues and gathering feedback from your team immediately.
Ready to begin?
Join our waitlist for early access to the beta program. Be one of the first to test our new product!
The UX analytics
system for AI teams
Verse helps teams improve their conversational AI systematically. Find problems, get expert feedback, and make fixes without spreadsheets and meetings.