EvenUp
Each of these is a real decision EvenUp is working through, written so you can make the call yourself — incomplete information, someone who pushes back, no answer key.
EvenUp is a vertical legal-technology company providing an AI-driven platform for plaintiff-side personal-injury law firms. Its software and technology-assisted services support the case lifecycle from intake and treatment through demand, negotiation, litigation, and settlement. Its proprietary claims-intelligence platform is called Piai™. EvenUp offers Discovery Operations, a fully managed, AI-powered discovery service for personal injury litigation firms. Its systems turn messy, unstructured case materials into accurate, structured "source of truth" data. Its engineering tech stack includes Python, Typescript, React, Postgres, Kubernetes, and Elasticsearch, and its data stack is built on BigQuery and dbt.
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Decide which active matters can migrate before the legacy system retires
Treatment events appear out of order in migrated active matters, putting 6,000 files near a committed retirement date. You must weigh demand continuity against the proof attorneys need before relying on migrated timelines.
Move attorneys to linked records without delaying demand deadlines
Demand staff are bypassing linked records and rebuilding medical timelines by hand. You must weigh faster adoption against a review routine attorneys will actually trust.
Choose what reaches an attorney while staff review every decline
Pilot firms are sending too many unclear inquiries to attorneys because the handoff lacks a usable qualification rationale. You must weigh quicker intake decisions against the evidence attorneys need to trust a decline.
Choose injury mappings before active matters lock them in
Conflicting injury entities are appearing across matters headed into a permanent migration. You must weigh a firm’s implementation deadline against source-level trust in facts attorneys will use.
Stop repeat questions on uploaded records without weakening guardrails
Qualified inquiries with medical-record uploads are repeatedly falling into manual review. You have to weigh faster attorney intake against the guardrails that prevent unsupported cases from advancing.
Rank ready matters without turning triage into a black box
The gap from complete records to demand preparation now varies by 19 days across high-volume firms. You have to weigh faster queue movement against a ranking attorneys can inspect and challenge.
Choose the reasoning cutover while provider facts still blur
Three of 240 reviewed cases merge facts from separate providers despite an 11-point completeness gain. You have to weigh a one-way routing decision against the cost of keeping two expensive paths alive.
Stop duplicates from amended entries without hiding repeat prescriptions
Duplicate medication events appear in 6.8% of amended-record cases and inflate treatment timelines. You have to weigh fast suppression against losing real repeat prescriptions.
Link each case statement to its source so attorneys can trust it
Attorneys keep asking where generated case statements came from and whether anyone checked them. You have to weigh a focused verification pilot against the richer confidence signals Data Science wants.
Prove matter mappings before a permanent migration cutover
Eighteen of 400 sampled mappings look correct but carry the wrong legal meaning. You have to weigh a nine-day cutover against review evidence attorneys can rely on.
Clarify intake exceptions while qualified leads wait in review
Forty-two percent of leads with an uploaded document restart intake. You have to weigh a faster exception flow against the evidence case managers need to trust it.
Trace failed workflows without slowing the next release
A customized client workflow fails, and engineers cannot quickly agree which event changed its path. You must weigh faster cause discovery against the evidence engineers need before changing production behavior.
Surface record gaps before demand work starts
Medical records can arrive after attorneys believe a matter is ready for demand preparation. You must weigh earlier completeness signals against turning uncertain inferences into unsupported case facts.
Protect source links before the migration locks in bad mappings
Cross-matter citations are appearing in generated chronologies while the treatment totals still look correct. You must weigh a committed migration date against the evidence needed to trust every corrected mapping.
Restore export links when new medical records arrive
Some exported citations fail after a matter receives another medical-record upload. You have to protect attorney verification without making active exports slower.