The setting
's is an AI platform that turns legal and medical case data into structured claims information for personal-injury law firms.
Provider names on incoming records are splitting a single treatment trail across the matter.
The mapping must consolidate clinic records without changing contacts that live matters already rely on.
Who you’d be doing this for
“I spent an hour yesterday proving two clinic names were the same place before I could finish the file.”
Durga Choudhury · Demand Paralegal · a character in this brief
Prepares medical records and treatment narratives for plaintiff-side personal-injury demand packages.
What is at stake
Provider records from the same clinic are splitting across duplicate contacts and forcing manual treatment-trail checks. You must weigh a fast mapping correction against the risk of changing contacts already used in live matters.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- faster batch processing vs. accurate provider identity
- live matter stability vs. cleaner future mapping
- firm-specific variation vs. reusable implementation rules
- manual continuity vs. structured case intelligence
Why EvenUp
Piai turns provider records into the structured case intelligence attorneys use to prepare personal-injury demands.
Written with these in mind
Not your kind of problem? 18 more at EvenUp, or browse every organization.
Where the organization context comes fromThe postings this brief was written from, and the reporting read before it.
The organization context comes from public information. The situation and characters are written for the brief.
Job postings it was written from
Public descriptions of the work at EvenUp. They are listed as sources, not as openings. The lines under a posting are its own words, where it meets this brief.
- Manager, Technical Implementation Services (opens in a new tab)
- Own the end-to-end technical delivery strategy for customer integrations, including system-to-system connections between EvenUp and Case Management Systems (CMS), legal practice management platforms, and other partner technologies.
- Senior Legal Engineer (opens in a new tab)
- Maintain and expand EvenUp's knowledge base and case-specific templates, including firm and state-level customization in partnership with clients, for personal injury claims today and for additional practice areas as we expand into them.
- You can explain a doctrinal edge case to an engineer or data scientist in terms they can build against, and you can tell the difference between an instruction that sounds clear and one that actually is.
- Senior Product Solutions Manager (opens in a new tab)
- Manage complex data mapping tasks, including provider contact entity linking.
- Configure Customer Environments: Translate firm Standard Operating Procedures into EvenUp by setting up Smart Workflows, task plans, and document templates.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.
Where similar work appears
Other live briefs connected to this one, and what connects them.
Similar problems at other organizations
Like this one, each of these turns on crossing a deadline that can't be undone.
A practice run of the workspace migration created 74,000 duplicate records, and the real migration cannot be undone.
You have to choose an identity rule that survives audit and daily use.
96 US-bound bookings point to conflicting importer entities, including 17 cases with disputed evidence.
You must weigh clearance continuity against locking an unverified entity rule into production.
Two confirmed records and mixed system evidence indicate recent-surgery members can bypass clinical review.
You have to weigh a full enrollment pause against a tightly verified containment and migration path.
The same setting, from another role
Each is set around EvenUp’s Piai Claims-Intelligence Platform, written for a different role. They’re separate briefs, not the same scenario.
One practice group at a plaintiff firm is live, but leaders can't see if demand preparation is changing across offices.
You must decide how far a repeatable adoption path can go before attorney source review has to prove expansion is safe.
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.
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.
Other problems with a similar purpose
In each of these, as in this one, the aim is to make operational data dependable at the exact moment someone needs to act on it.
Late partner records leave valid quote journeys out of the next morning’s funnel view.
You have to weigh faster completeness against duplicate policy-start reporting.
Duplicate TMS cases must fall below 1% of late-shipment events within ten business days.
You must weigh fast exception escalation against the confidence operators need in every case.
Launch operators cannot explain why nearby homes receive different availability answers.
You must weigh a fast review flow against preserving the flight constraints behind every route.
