swivl uses cutting-edge AI to 10x the amount of customers you currently serve
while decreasing customer care costs upwards of 36%.
“swivl is next-level and a far better approach for on boarding a user through your customer journey. The swivl team is leading the next generation of human experience curation using AI-powered information systems. Visionary.”
Carson D. Kelly“Swivl has been a game changer in the way we communicate and engage in both internal and external customer-facing processes. We have seen a decrease in answering repetitive tickets and onboarding questions by 17%. Conversions have increased by 11% due to more highly personalized web interactions. It’s AI on demand - using the most easy drag and drop interface we’ve seen!”
Lannie Moore“We are a small team and since using swivl, we’ve been able to keep our customer service team costs down by automating our most frequently asked questions. Their easy Human-in-the-Loop interface makes it easy for our team to step in and help web visitors find their next adventure!”
Ben Nelson"Before swivl, the company was answering roughly 10% of incoming messages and missed many opportunities to convert web visitors into loyal customers. I wanted to find an innovative way to create engagement triggers and a personalized product recommendation engine to enhance our web visitors’ digital experiences. The swivl platform has been an invaluable addition to our online web experience."
GarrenDecrease in Customer Care Costs
Automated Support Responses in 30 Days
Average increase in customer support response time
More customers capacity per support rep
swivl uses cutting-edge AI to store and tag data from customer support interactions. As you help more customers, their questions and your responses are stored in swivl’s AI brain so that next time they come up, swivl can answer hard questions without needing a person to step in.
Deploy intelligent agents in HALF the time compared to other solutions using many ready-made templates ensuring speed of deployment. On average, users build their first version in less than 5 hours.
Data is messy – there are a lot of errors in data collection including incorrect labels and understanding how to handle unstructured data. This is why Data Scientists are spending 80% of their time finding, cleaning and organizing that data.
Today, we are augmenting that role. Implement, train, test, and tune custom ML data in less than a month. Don’t know how to code? No problem!
