customer_support · education · workflow
Forethought Assist reduces D2L ticket close time by 13.7% and increases cases per hour by 32%
D2L support agents wasted time toggling between multiple windows and tabs to find help articles and past tickets, while keyword-based search tools returned long lists of irrelevant results from unstructured data sources, causing agents to spend more time searching than answering tickets.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Agent opens new case
When an agent opens a new case in their helpdesk, Forethought Assist is activated.
Tools used
Forethought AssistNLU
Outcome
D2L reduced time to close tickets by 13.7%, increased cases answered per hour by 32%, and decreased First Response Time by 56%, while agents who used Forethought consistently were 3.5 times more likely to meet their weekly efficiency goals.
What failed first
D2L's previous search tools relied on keyword matching and produced irrelevant results, and the team could not find a partner capable of working with their unstructured, heterogeneous knowledge sources.
Results
Time saved13.7%
Volume32%
Grounding & classification
Source type: vendor customer story
26 fields verified against source quotes.
agent assistknowledge searchknowledge basesupport ticketfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describededucationsoftwarecycle time reductionemployee productivityresponse time reductionvendor customer storycustomer supportticket triagehuman review queue