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Legal & Insurance · Audits cleared · Hours back · sample run · 1 ms

Class Action Settlement Allocator

182,400.00 in submitted class action claims audited against allocation plan across across 4 items.

Evidence · Claimant Submitted Proofs of Claim
CLM-1004,Piedmont Transport Inc,15000,2023-11-15,Outside_Class_Period,60000.00
Working

Purchase on 2023-11-15 precedes class start date (2024-01-01). Claim of $60,000.00 disqualified under Court Order 1.

Method

1Verified claimant transaction dates against court-mandated class period boundaries.

2Applied pro-rata damage recovery factors to approved claim submissions.

182,400.00
Total Discrepancy · Audited balance impact
ReferenceDescriptionEvaluated_Amount
CLM-1004Outside Class Period Disqualification (Piedmont)60,000.00
CLM-1002Deficient Documentation Disqualification (Apex)34,000.00
CLM-1003Authorized Loss Payout (Cascade Retail)57,200.00
1 to 3 of 4
Reads

Claimant purchase records and transaction files, plus court order Plan of Allocation rules

Produces

Approved distribution matrix with pro-rata payout calculations and disqualified claim schedules (Resolution Dossier, Findings Schedule)

Price

Open Class Action Settlement Allocator on sample data now with no sign-up, then run your own files free for 14 days. $3,500 a month after that, cancel any time. 30% goes to the referring partner.

Your files

Read in memory for the session, never stored, never used to train a model.

Outputs are computed from your inputs and the tool's rules. Check them before you rely on them.

The offer

14 days on your own files, then $3,500 a month.

Open Class Action Settlement Allocator on sample data now with no sign-up, then run your own files free for 14 days. $3,500 a month after that, cancel any time.

On a sample file: 182,400.00 in submitted class action claims audited against allocation plan across across 4 items.

Why not just use ChatGPT?

Rules that stay current: the rate cards, tariffs, code sets and regulations it checks against are kept up to date for you; a one-off prompt starts from nothing each time. Evidence that stands up: every finding cites the line, the file and the rule, so it holds up with a vendor, a payer or an auditor. The same answer every time: the checks are written rules, not a fresh guess, so this month's result can be compared with last month's. Nobody has to own it: no one inside has to build, test and maintain a home-made tool, and files are not pasted into a public chatbot.

Start on your own files

Your files are read in memory and never stored.

If you would rather talk it through, write to dev.sathya@baseloom.app; that reaches Dev Sathya, founder.