- Zappi are a marketing research company that had been working on a ML model to classify free text feedback on and off for 2 years
- They found Kortical and decided to test the platform against that tricky NLP problem
- Using the Kortical AutoML platform they got a 43.9% accuracy gain in a few hours
- The full ML solution was deployed live in 5 weeks
Zappi is revolutionising the market-research industry through automating much of the survey process, enabling their clients to get a more comprehensive service, faster and at a lower cost.
An area they had been spending a lot of time working on was the free text fields in the marketing survey form and they were exploring how to switch from a manual process to a Machine Learning approach.
The Zappi data scientists wanted a Natural Language Processing (NLP) model that would not only beat their current model but also beat the manual outsourcing team.
Kortical AI as a Service Platform
The training data was ready to go as they had been working on this problem outside of the platform. Each text entry had 180 different labels which could apply so it was a complex problem vs a simple positive or negative classifier you hear of often which is not nuanced enough for Zappi’s requirements.
Using the Kortical AutoML platform they got a 0.59 vs 0.41 - a 43.9% accuracy gain in a few hours
Production-ready Machine Learning
Going from ML model to production-ready, is typically a long process (Gartner has reported up to 4 years), as AI models have been built for research and academia vs being able to scale to millions of users and meet software SLAs that organisations need to adhere to. This problem Kortical addresses by providing deployment capabilities as part of the platform. Which meant that the Zappi developers were able to test the best model via API immediately and had the service that the API linked to fully tested and live in production within 5 weeks.
Being an end to end platform made all the difference in the speed that the Zappi data scientists and developers were able to move at.
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