legal_document_review · services · workflow
EvenUp AI reduces demand preparation time by three to four months and doubles policy-limit settlements at J.D. Silva & Associates
J.D. Silva & Associates relied on time-consuming manual processes to draft demand letters, limiting their ability to produce highly detailed, data-driven demands and constraining the firm's ability to scale.
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 · Growing caseload prompts demand optimization
As caseload grew, the firm needed a way to optimize their demand process, increase efficiency, and ultimately scale their practice.
Tools used
EvenUpCase CompanionSettlement Repository™Executive Analytics™Claims Intelligence Platform
Outcome
J.D. Silva & Associates reduced demand preparation time by three to four months, resolved cases five to six months faster, received higher settlement offers from insurance adjusters, and doubled the number of cases settled at policy limits.
Results
Time savedthree to four months
Volumefive to six months faster
Grounding & classification
Source type: vendor customer story
30 fields verified against source quotes.
data extractiondocument aiknowledge searchpredictive analyticsmedical recordmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedlegalcycle time reductionemployee productivitythroughput increasetime savedvendor customer storylegal document reviewlegal opsai draft human approvaldocument to record