Legal document review · Production

EvenUp AI reduces demand preparation time by three to four months and doubles policy-limit settlements at J.D. Silva & Associates

The problem

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.

Workflow diagram · grounded in source
1
Growing caseload prompts demand optimization
trigger
“As their caseload grew, they needed a way to optimize their demand process, increase efficiency, and ultimately scale their practice”
2
AI demand package generation
ai_action
“The firm saw immediate benefits from the detailed, well-supported demands generated by EvenUp”
3
Case Companion research
ai_action
“Using Case Companion now gives us the ability to go directly to what we need in a very short amount of time”
4
Data-driven case valuation
ai_action
“By providing quantified case valuations, the firm no longer relies solely on experience to determine settlement values—ensuring data-driven accuracy in setting operational priorities”
5
Real-time performance analytics
output
“The firm previously relied on weekly reports compiled from multiple departments, which was a slow and cumbersome process. They can now access critical firm performance data in real time”
6
Faster settlement at higher values
output
“drastically reduced demand preparation time by three to four months, enabling them to resolve cases five to six months faster”
Reported 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.

Reported metrics
Demand preparation time reductionthree to four months
Case resolution time improvementfive to six months faster
Cases settled at policy limitsdoubled
Hours saved on legal and medical records researchcountless hours
Show all 5 reported metrics
demand preparation time reductionthree to four months
case resolution time improvementfive to six months faster
cases settled at policy limitsdoubled
hours saved on legal and medical records researchcountless hours
time saved per casehours on every case
Reported stack
EvenUpCase CompanionSettlement Repository™Executive Analytics™Claims Intelligence Platform
Source
https://www.evenuplaw.com/customers/j-d-silva-associates-evenup/
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Frequently asked questions

What did this team achieve with this AI workflow?

J.D.

What tools did this team use?

EvenUp, Case Companion, Settlement Repository™, Executive Analytics™, Claims Intelligence Platform.

What results were reported?

Demand preparation time reduction: three to four months; Case resolution time improvement: five to six months faster; Cases settled at policy limits: doubled; Hours saved on legal and medical records research: countless hours (source-reported, not independently verified).

How is this legal document review AI workflow structured?

Growing caseload prompts demand optimization → AI demand package generation → Case Companion research → Data-driven case valuation → Real-time performance analytics → Faster settlement at higher values.

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