back_office_ops · saas · workflow
LogMeIn scales meeting data processing 1400% with super.AI humans-and-AI pipeline
LogMeIn was processing meeting recordings internally to power their Scopus.io meeting bot, but the internal team could not scale fast enough, forcing technical shortcuts and compromises to user experience.
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 · Meeting data submitted via API
LogMeIn submits meeting recording data to super.AI via a production API in real time.
Tools used
super.AIScopus.io
Outcome
super.AI scaled LogMeIn's production traffic by 1400% and enabled a full 100% transition to the super.AI platform, freeing the LogMeIn team to focus on developing new product features and preparing for customer rollout.
What failed first
A pure AI approach would sacrifice output quality to achieve desired turnaround times, while a 100% human solution would not meaningfully accelerate throughput beyond their existing internal team.
Results
Volume1400%
Grounding & classification
Source type: vendor customer story
21 fields verified against source quotes.
data extractionsummarizationmeeting recordingfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedsoftwareemployee productivitythroughput increasevendor customer storyback office opsai draft human approvalmeeting to artifacts