Applications of AI exist in every business, so it's no wonder this field is booming. However, a major challenge remains: understanding user-AI model interaction and model performance. Evaluating these opaque components can be difficult, hampering both advancements and user experience.
AI Analytics Challenges
One of the biggest obstacles to artificial intelligence is the difficulty of extracting useful insights from large, complex data sets. A common name for this is the “data problem”. Companies are collecting more data than ever before, but not all have the resources or knowledge to properly evaluate it.
Several problems can arise due to this opacity. Businesses need help identifying customer problems, categorizing customer actions, and determining why customers leave. Another problem is that it takes into account labor biases in the model, which requires work. Developing more reliable and resilient AI models is another hurdle. The potential for bias and error in many AI models means they continue to threaten society. Using a biased AI model, for example, could lead to discrimination in the workplace.
Dawn's innovative solution
Meet Dawn AI, a cool AI analytics startup. Dawn aims to solve the black box problem by providing a global analytics platform suitable for AI products.
The main features of Dawn AI are:
- Dawn is a master at categorization/tokens; it can automatically sort user inputs and model outputs into useful categories. This paves the way for businesses to divide their user base into behavioral subsets, uncover reasons for product attrition, and refine search capabilities by ranking user queries.
- Customization is crucial: Dawn offers predefined, user-defined categories, giving businesses the power to tailor information to their needs.
- Over time, Dawn, an intelligent system, continues to learn more and more. The more data it processes, the better it understands the information and the more information it produces.
Funding cycle
Dawn is supported by Y combiner.
Key takeaways
- AI black box problem: Difficulty determining user engagement and model performance hinders improvement of AI products and user experience.
- What Dawn Recommends: This Y Combinator-backed company offers analytics that segment users, detect churn, and rank user inputs and model outputs.
- Benefits: Custom classifications, continuous skill development, and a better understanding of user actions and model effectiveness.
Dhanshree Shenwai is a Computer Science Engineer with good experience in FinTech companies spanning Finance, Cards & Payments and Banking with a keen interest in AI applications. She is enthusiastic about exploring new technologies and advancements in today's changing world that makes everyone's life easier.