Legal document review · Production

MVP Accident Attorneys scales demand capacity and increases settlements with EvenUp AI

The problem

MVP Accident Attorneys struggled to scale operations across high caseload volumes while maintaining detailed attention to each case's nuances, and needed tools that could work alongside staff rather than replace them to ensure case data was accurate, well-documented, and actionable.

Workflow diagram · grounded in source
1
AI demand letter generation
ai_action
“EvenUp Demands™ generates clear and concise medical summaries that ensure no money is left on the table, allow attorneys to spot red flags in argument preparations, and undergo completeness checks. Along with flagging of missing bills or…”
2
Human expert review
human_review
“it actually has human factors and components behind the AI testing the information that is being given and double checking the information being provided back to us”
3
Case Companion real-time analysis
ai_action
“Case Companion™ provides real-time answers, analysis, and line-based evidence—across thousands of pages”
4
Settlement benchmarking
ai_action
“EvenUp's Settlement Repository™ helps MVP ensure optimal settlement results by providing insights on previous settlement outcomes, injury-specific data, and other comparative facts, such as adjusters and insurance companies”
5
Demand and case prep delivery
output
“enable MVP's team to easily find missing documents, save time preparing robust demands, and avoid "red herrings" commonly raised by adjusters during negotiations”
Reported outcome

After implementing EvenUp, MVP Accident Attorneys saw settlement offers increase, achieved a 25% market increase on their initial test case offer, identified missing documents that raised settlement impact across part of their caseload, and became better equipped to scale demand capacity while maintaining quality.

Reported metrics
Initial offer increase on test case25%
Settlement impact from missing document identificationIncrease in settlement impact by proactively identifying missing documents alone
Time savingstime savings
Case carrying costslowered case carrying costs
Show all 6 reported metrics
initial offer increase on test case25%
settlement impact from missing document identificationIncrease in settlement impact by proactively identifying missing documents alone
time savingstime savings
case carrying costslowered case carrying costs
policy limits settlementsincreased policy limits settlements
settlement offer valueoffers go up
Reported stack
EvenUp Demands™Case Companion™Claims Intelligence Platform™Case Preparation™Settlement Repository™
Source
https://www.evenuplaw.com/customers/mvp-accident-attorneys/
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Frequently asked questions

What did this team achieve with this AI workflow?

After implementing EvenUp, MVP Accident Attorneys saw settlement offers increase, achieved a 25% market increase on their initial test case offer, identified missing documents that raised settlement impact across part…

What tools did this team use?

EvenUp Demands™, Case Companion™, Claims Intelligence Platform™, Case Preparation™, Settlement Repository™.

What results were reported?

Initial offer increase on test case: 25%; Settlement impact from missing document identification: Increase in settlement impact by proactively identifying missing documents alone; Time savings: time savings; Case carrying costs: lowered case carrying costs (source-reported, not independently verified).

How is this legal document review AI workflow structured?

AI demand letter generation → Human expert review → Case Companion real-time analysis → Settlement benchmarking → Demand and case prep delivery.

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