Aisera Launches Ticket AI

Aisera, provider of an artificial intelligence service management platform, has launched Ticket AI to automate and scale support organizations using existing ticketing systems.

Ticket AI continuously learns to empower agents by recommending similar tickets or cases, knowledge articles, and next-best actions to speed the resolution process. Through a thorough analysis of live agent conversations, Ticket AI eliminates many manual service agent processes.

"This platform raises agent productivity while improving the user experience substantially, as service agents use Aisera's Ticket AI to automate customer workflows, service desk workflows, and auto-triage tickets and cases for improved CX where the human touch is needed," said Aisera's co-founder and CEO, Muddu Sudhakar, in a statement.

From routine password resets, billing, subscriptions, technical support issues and troubleshooting to more complex issues, Ticket AI enables resolution across multiple channels without human intervention.

Continuous AI learning leverages past resolved tickets and cases to automatically close knowledge gaps and improve prediction accuracy for future requests. Capabilities include the following:

• Auto resolution;
• Agent asssist;
• Auto triage;
• Automated and continuous AI learning;
• Real-time reinforcement learning;
• Multilingual omnichannel support; and
• Agent coaching and predictive performance dashboards.

Ticket AI integrates seamlessly with leading platforms, including Salesforce, ServiceNow, Zendesk, Atlassian, Jira Service Management, BMC, as well as automations with Zoom, WebEx, Box, G Suite, Office 365, SharePoint, Adobe, Dropbox, AWS, Azure, Microsoft, Google Cloud, and others.

Both AI Service Desk and AI Customer Service combine Ticket AI with Aisera's Conversational AI and Conversational RPA, along with unsupervised natural language processing and understanding in an agile, scalable, cloud-native format founded on a virtual assistant.

"For both onsite and remote workforces, Ticket AI scales robustly, increases CSAT, reduces operating costs, lowers ticket and call volumes, and assists agents effortlessly across multiple data sources to speed resolutions," Sudhakar said further. "In many customer use cases, the user experience and enhanced productivity speak for themselves."