AI legal operations / Human review boundary
PetitionReady
Matter readiness operating console
The working paralegal dashboard connects queue state, readiness scoring, blockers, next action, attorney-review items, and source-grounded Copilot evidence without hiding the human review boundary.
Making a complex handoff legible: an intake readiness prototype that gives paralegals a clear hierarchy of blockers, evidence, and next actions for attorney review.
- My role
- Independent designer and developer — information hierarchy, workflow and interaction design, prototyping, and implementation
- Engagement
- Personal Project
- Period
- June 2026
- Resources
- 5 reviewed artifacts
01 / Context
Creative challenge
•Exceptions surfaced too late
Bankruptcy firms lose time when intake packets are incomplete, income data conflicts, creditor addresses are missing, documents are rejected, or payment status is unclear. Those exceptions often surface late, after a paralegal has already started assembling a packet for attorney review.
•The handoff lacked an operating view
The product needed to answer one practical workflow question: can this client matter move toward attorney review, and if not, what exact blocker should the paralegal resolve next?
•Legal scope required a hard boundary
The prototype intentionally focuses on readiness, blockers, evidence, and attorney-review preparation instead of automated filing, legal advice, eligibility decisions, or petition generation.
02 / Mandate
Direction and intent
•Make readiness inspectable
Design and build a working dashboard that gives paralegals a clear view of active matters, blocker counts, readiness scores, queue status, and next actions.
•Ground AI in the current packet
Use structured AI outputs to summarize blockers, find conflicts, draft client follow-ups, and compile attorney-review briefs from the current case packet.
•Preserve reviewer access without credentials
Make the demo useful without credentials through deterministic local fallback analysis, while preserving the same UI shape when model calls are unavailable.
Case-grounded Copilot evidence
The Copilot panel exposes its evidence snapshot alongside bounded modes for blocker analysis, conflict checks, client follow-up drafts, and attorney-review brief compilation.
03 / Build
Creative decisions and execution
1.Modeled repeatable case states
Created seeded Chapter 7 and Chapter 13 matters with client facts, document states, retainer status, issues, readiness stages, raw notes, and blocker metadata.
2.Built the paralegal operating console
Implemented readiness summary cards, matter queue pagination, status badges, selected matter details, top blockers, next paralegal action, and attorney-review item surfaces. Readiness starts at 100, subtracts documented issue weights, and maps each matter to attorney review, cleanup, or blocked state.
3.Implemented structured server-side Copilot
Built server-side Paralegal Copilot modes for blocker analysis, conflict checks, client follow-up drafts, and attorney-review brief compilation using the OpenAI Responses API, structured JSON output, and Zod validation.
4.Kept deterministic fallback equivalent
Created local analysis for readiness scoring, blocker detection, follow-up generation, and brief assembly so reviewers can evaluate the full workflow without an OpenAI key.
Exception and notification queue
The notification state surfaces new matters, document exceptions, top blockers, and the next paralegal action without separating alerts from the operating queue.
Blocker-to-next-action inspector
The inspector keeps source notes, unresolved evidence, the next paralegal action, and attorney-review preparation in one inspectable matter state.
04 / Outcomes
Outcomes
•One blocker-to-review workflow
The prototype turns intake state into a repeatable queue, readiness score, issue list, evidence snapshot, next action, and attorney-review handoff instead of scattering those decisions across disconnected views.
•Inspectable human-in-the-loop boundary
PetitionReady grounds Copilot outputs in supplied case evidence, keeps paralegal and attorney review visible, and explicitly avoids legal conclusions, filing decisions, and automated petition generation.
•Production-minded prototype with explicit gaps
The public repo and Vercel demo include typed domain models, structured AI response validation, focused Vitest coverage, timeout and fallback behavior, and seeded local data. Authentication, persistence, audit logs, and production legal workflows remain deliberately out of scope.
Selected-matter readiness review
A selected Chapter 13 matter connects its readiness score and payment-plan blocker to the evidence and cleanup action required before attorney review.
Tools
Tools and implementation
Continue the evidence trail
From proof to role fit
Compare PetitionReady with adjacent systems, or carry its reviewed capabilities into an Adaptive Focus brief.