weekly startup spotlight

welcome to introspection ft. harsehaj! ⭐️ i’m harsehaj, a 19 y/o always up to something in social good x tech.

this publication is a place for me to reflect on productivity, health and tech, and drop unique opportunities in the space right to your inbox daily. if you’re new here, sign up to tune in!💌

scroll to the end for my daily roundup on unique opportunities!

onto today’s topic: tone ai 🎤 

after an event we’re often prompted to fill out a feedback survey, but a lot of valuable information about an attendee's experience is lost in the process. that information is conveyed through verbal dialogue and our tones. the funny thing is that marketers all know this — word of mouth is the most powerful vehicle for growth after all. so, why aren’t we capturing verbal feedback first? 🤨 

the big answer here is that it’s likely an inconvenient user experience. while that’s somewhat true, tons of people always film vlogs with voiceovers, send audio messages, and make phone calls about their experiences. tone ai aims to capture that word-of-mouth feedback and convey an audience’s raw emotions.

essentially, tone ai is a b2b platform that extracts meaningful insights from audio and video feedback, emphasizing the analysis of tone and sentiment in communication. it enables brands, media outlets, and communities to capture and analyze audience responses during events using tools like qr codes and push notifications.

let’s talk numbers! 🤓

the global market for voice analytics is projected to grow from $1.3 billion in 2024 to $2.54 billion by 2033, at a cagr of 18.3%, while the sentiment analysis software market is expected to grow from its current size to $4.94 billion by 2028, with an annual growth rate of 18.2% (source). this growth is being fuelled, of course, by the rapid adoption of ai and machine learning solutions.

as tone ai is very early-stage, no data has been publicly released on their quantitative value-add; however, they have closed a successful deal with the chicago bears.

questions i’d be interested to ask:

• how is the product catered differently for each partner’s needs?

• what does the sentiment data training look like? what is the accuracy?

daily opportunity + resource drops 🔍️