Lime achieves 77% reduction in response time with Forethought AI triage and automated support
The problem
Lime's support center operated entirely manually with no ticket routing or prioritization, forcing all agents to handle every ticket type regardless of urgency. Multilingual tickets required agents to manually toggle between Google Translate and their cases, there was no self-service channel, and critical tickets such as accident reports were handled in the order received rather than by severity.
Workflow diagram · grounded in source
1
Support ticket arrives
Trigger
Support inquiries arrive through email, phone, the Lime app, and a web form.
▾ source quote
“Support inquiries were received through email, phone, the Lime app, and a web form to be followed up on by support agents”
2
Triage classifies language and category
Ai action
Forethought Triage layers language and category classifications and determines service levels based on severity.
▾ source quote
“Triage layers the language and category classifications, and works internally to determine different service levels based on severity”
3
Route to agent queue
Routing
Cases are routed to a specific queue based on predicted language, category, and criticality tags.
▾ source quote
“Lime has custom tags and triggers set up so that when Forethought predicts a specific language and category, the case is routed to a specific queue based on those tags. Now, support cases are tagged so the most critical inquiries …”
4
Solve interprets and responds
Ai action
Forethought Solve interprets the intent of a customer's request and instantly searches the entire database of knowledge articles and previously resolved tickets to provide the most accurate response without an agent.
▾ source quote
“they're able to interpret the intent of a customer's request, through their chat widget or email, and instantly search their entire database of knowledge articles and previously resolved tickets to provide the most accurate response–all without the help of an …”
5
RPA workflow executes
Integration
RPA-guided workflows are automated from beginning to end through pre-set rules, integrating with internal tools for tasks around damaged vehicles, charge and payment issues, and receipt questions.
▾ source quote
“These RPA-guided workflows are automated from beginning to end through pre-set rules. These workflows integrate with internal tools to complete automation tasks around damaged vehicles, charge and payment issues, and receipt questions”
6
Complex issues escalate to agent
Human review
If a customer's question is complex, they are automatically routed to the help center web form, which is then passed on to a support agent.
▾ source quote
“If the customers' question is complex, they're automatically routed to the help center web form, which is then passed on to a support agent”
Reported outcome
Forethought automated 27% of email and web cases and tagged 98% of support tickets automatically out of more than 1.7 million tickets per year, yielding a 77% reduction in time to first response along with significant cost savings and improved customer satisfaction.
Reported metrics
Cases automated via email and web27%
Language and category tags predictedover 2.5 million
Support tickets tagged automatically98%
Time to first response77% reduction
Show all 8 reported metrics
cases automated via email and web27%
language and category tags predictedover 2.5 million
agents' time savedhelps save agents' time in a massive way
Reported stack
Forethought TriageForethought SolveWorkflow BuilderRobotic Process AutomationGoogle Translate
◆ Does this fit your context?
Compare to your context
Tell us your scale, team, and constraints. We'll show what changes at your size, what fails at your scale, and whether this case is a fit, needs adaptation, or won't scale to you. Free demo, no signup.
Forethought automated 27% of email and web cases and tagged 98% of support tickets automatically out of more than 1.7 million tickets per year, yielding a 77% reduction in time to first response along with significant…
What tools did this team use?
Forethought Triage, Forethought Solve, Workflow Builder, Robotic Process Automation, Google Translate.
What results were reported?
Cases automated via email and web: 27%; Language and category tags predicted: over 2.5 million; Support tickets tagged automatically: 98%; Time to first response: 77% reduction (source-reported, not independently verified).
How is this customer support AI workflow structured?
Support ticket arrives → Triage classifies language and category → Route to agent queue → Solve interprets and responds → RPA workflow executes → Complex issues escalate to agent.
This case is one data point. Whether its pattern fits you depends on your volumes, your stack, and your exception load — that comparison is the step no case study can do for you.