Legal document review · Production

Chandler | Volta Personal Injury Lawyers streamlines demand packages and medical chronologies with EvenUp

The problem

Chandler | Volta faced two time-intensive tasks — creating demand packages and assembling medical chronologies — that were limiting the firm's ability to scale while maintaining client service quality and efficiently locating critical medical records.

Workflow diagram · grounded in source
1
Case demand workflow initiated
trigger
“faced two significant time-intensive tasks: creating winning demand packages and assembling robust, accurate medical chronologies”
2
Demand tier routing by complexity
routing
“The firm takes advantage of the three types of demands: standard, basic, and simple. A standard demand includes a full medical chronology and is more extensively developed... They typically use standard demands for larger cases, while ba…”
3
AI demand package creation
ai_action
“providing case analysis based on similar cases within the firm's specific jurisdiction. This allows them to leverage case strengths when negotiating with insurance carriers”
4
Medical chronology generation
ai_action
“EvenUp's MedChrons™ simplifies case preparation by sifting through all the key records to outline the client's prior medical history, presenting key events in a user-friendly calendar, and identifying missing records—ensuring cases are r…”
5
Settlement valuation via repository
ai_action
“EvenUp's Settlement Repository™ helps the firm accurately value cases in pre-litigation stages by analyzing insights on previous settlement outcomes, injury-specific data, and other comparative facts, such as adjusters and insurance comp…”
6
Human review and oversight
human_review
“Joe emphasizes the importance of using modern AI-driven tools with human oversight, which ensures the highest accuracy and trustworthiness”
7
Demand submitted to carrier
output
“I can submit them to insurance carriers with all of the information I need for future damages, present damages, past damages”
Reported outcome

The firm saved significant time on demand creation with turnarounds within five days, improved litigation preparation through AI-generated medical chronologies, and in one case surpassed the initial pre-litigation settlement offer through the litigation process.

Reported metrics
Demand turnaround timewithin five days
Time savings on demand creationsaved a ton of time
Litigation settlement outcome improvementsurpassed the initial pre-lit offer by the end of litigation
Operational efficiency and client satisfactionstreamlined our operations and improved client satisfaction
Show all 5 reported metrics
demand turnaround timewithin five days
time savings on demand creationsaved a ton of time
litigation settlement outcome improvementsurpassed the initial pre-lit offer by the end of litigation
operational efficiency and client satisfactionstreamlined our operations and improved client satisfaction
missing documents identification impactIn potential settlement impacts by proactively identifying missing documents alone
Reported stack
EvenUpClaims Intelligence Platform™Demands™MedChrons™Settlement Repository™
Source
https://www.evenuplaw.com/customers/chandler-volta-personal-injury-lawyers/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

The firm saved significant time on demand creation with turnarounds within five days, improved litigation preparation through AI-generated medical chronologies, and in one case surpassed the initial pre-litigation set…

What tools did this team use?

EvenUp, Claims Intelligence Platform™, Demands™, MedChrons™, Settlement Repository™.

What results were reported?

Demand turnaround time: within five days; Time savings on demand creation: saved a ton of time; Litigation settlement outcome improvement: surpassed the initial pre-lit offer by the end of litigation; Operational efficiency and client satisfaction: streamlined our operations and improved client satisfaction (source-reported, not independently verified).

How is this legal document review AI workflow structured?

Case demand workflow initiated → Demand tier routing by complexity → AI demand package creation → Medical chronology generation → Settlement valuation via repository → Human review and oversight → Demand submitted to carrier.

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