Test, understand and fix your conversational AI model
QBox analyzes and benchmarks your chatbot training data by visualizing and understanding where it does and doesn’t perform, and why (for your NLP). With this insight, you can make informed decisions about how you develop the performance of your chatbot.
About QBox on Product Hunt
“Test, understand and fix your conversational AI model”
QBox launched on Product Hunt on July 26th, 2021 and earned 55 upvotes and 1 comments, placing #28 on the daily leaderboard. QBox analyzes and benchmarks your chatbot training data by visualizing and understanding where it does and doesn’t perform, and why (for your NLP). With this insight, you can make informed decisions about how you develop the performance of your chatbot.
On the analytics side, QBox competes within User Experience and Artificial Intelligence — topics that collectively have 831.5k followers on Product Hunt. The dashboard above tracks how QBox performed against the three products that launched closest to it on the same day.
Who hunted QBox?
QBox was hunted by Leah Lemm-Serruya. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of QBox including community comment highlights and product details, visit the product overview.
Leah Lemm-Serruya