Lexarius, co-developed with INSEAD and SC Ventures, is a multilingual AI roleplay platform that enables employees to practise sales, leadership, and change-management conversations in realistic simulations while receiving real-time feedback, immediate skill scoring, and competency-based assessment in a safe, scalable environment.
I love the idea of using AI for high-fidelity, low-stakes roleplay—static training modules usually fall flat. From a technical side, how do you handle the nuance of intent? Is it primarily text analysis, or are you looking at audio/video cues for things like confidence and empathy?
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About Lexarius on Product Hunt
“AI roleplays for corporate learning teams”
Lexarius launched on Product Hunt on May 11th, 2026 and earned 86 upvotes and 1 comments, placing #20 on the daily leaderboard. Lexarius, co-developed with INSEAD and SC Ventures, is a multilingual AI roleplay platform that enables employees to practise sales, leadership, and change-management conversations in realistic simulations while receiving real-time feedback, immediate skill scoring, and competency-based assessment in a safe, scalable environment.
Lexarius was featured in Pitch Singapore on Product Hunt. Together, these topics include over 44 products, making this a competitive space to launch in.
Who hunted Lexarius?
Lexarius was hunted by Rajiv Ayyangar. 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.
Want to see how Lexarius stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rajiv Ayyangar
I love the idea of using AI for high-fidelity, low-stakes roleplay—static training modules usually fall flat. From a technical side, how do you handle the nuance of intent? Is it primarily text analysis, or are you looking at audio/video cues for things like confidence and empathy?