legal_document_review · services · workflow
J&Y Law cuts case lifecycle 25% and medical review time 50% with EvenUp AI
Surging caseloads from successful marketing efforts left J&Y Law's teams struggling to keep pace with time-intensive administrative tasks—organizing medical records, tracking treatment, preparing demands, and conducting case reviews—causing time-on-desk to slip and average case value to decline. The negotiation workflow alone required eight case managers working 40 hours a week just to aggregate data before negotiations could begin.
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 · AI intake pre-screening
Before the first client interaction, AI Playbooks find key information from intake transcripts, notes, and case files.
Tools used
EvenUpDemands™AI Playbooks™Medical Management™Express Demands™Companion™Strengths and WeaknessesAI Drafts™MedChrons™
Outcome
EvenUp's AI suite enabled J&Y Law to double monthly signed cases, handle a 40% increase in pre-lit caseloads, reclaim 320 hours of weekly team capacity, reduce the case lifecycle by 25%, and cut medical chronology review time by 50%.
Results
Time saveddouble
Volume40%
Grounding & classification
Source type: vendor customer story
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agentic workflowcontent generationdata extractiondocument aisummarizationmedical recordhuman review describedmetric backednamed customerproduction runtime claimedsource backedtools describedworkflow describedlegalcycle time reductionemployee productivitythroughput increasetime savedvendor customer storylegal document reviewlegal opsmedical records processingai draft human approvaldocument to recordextract classify route