A legaltech AI app rescue closes the seven gaps every AI-built legaltech MVP ships broken — no document retention schedule, Supabase RLS disabled on matters and documents, public Storage buckets, missing conflict-of-interest intake, and unsigned e-signature webhooks. Three-day audit from $499, fixed price, NDA signed upfront.
A document retention AI app rescue, a legaltech Supabase fix, and a privileged-access audit trail install are the three most common revenue-critical finds.
ABA Model Rule 1.15 and state retention rules demand client files be preserved for five to seven years after matter close. AI-built legaltech scaffolds store documents in Supabase Storage without a retention policy, without legal-hold flags, and without a tombstone-on-delete pattern. A document retention AI app rescue installs the schedule, the hold flag, and the per-matter archive.
A legaltech Supabase fix starts here. The anon key can read any matter or document row because the AI builder skipped RLS. We enable RLS on matters, documents, clients, and notes; write attorney-to-matter assignment policies; and ship a CI test that fails the build on an unprotected legal table.
Attorney-client privilege demands an access log. Which attorney read which document, when, from where. AI-generated scaffolds have no middleware, no append-only audit table, and no per-matter access report. We install audit middleware, retention-aware storage, and a per-matter access report attorneys can pull at will.
AI-built legaltech apps routinely ship with Supabase Storage buckets set to public read. A client file uploaded today is at a predictable URL tomorrow. We flip buckets to private, swap to signed URLs scoped per matter and per user, add short TTLs, and log every signed-URL generation to the audit trail.
Every new matter at a real firm runs through a conflict check. AI-generated scaffolds skip this entirely. We add a conflicts table keyed on client + adverse party + matter type, wire the intake flow to halt on a match, and require an attorney override with a recorded reason and a second-attorney approval.
Legaltech AI apps integrate DocuSign or HelloSign with placeholder variables and send the document over unsigned webhooks. Signed documents arrive via POST without verification. We add signature verification, idempotent webhook handlers, and an envelope-to-matter mapping so the audit trail never loses track of a document.
Privileged communications need a channel the firm controls. AI-generated legaltech apps send client messages via Twilio SMS or raw SendGrid without attorney-client-privilege markings, without encryption at rest on the message store, and without a per-matter access scope. We move to a messaging provider that supports at-rest encryption and scope every message to a matter with RLS.
Legaltech sits on three compliance surfaces. First, attorney-client privilege — every communication and document in the app is potentially privileged and the firm's duty of confidentiality extends to the vendor. Second, retention — the ABA Model Rules and state analogues demand client files be preserved for five to seven years after matter close, and most states add specific record rules on top. Third, conflicts — every new matter at a real firm runs through a conflict check before the attorney is assigned. AI-built scaffolds skip all three.
Retention is the silent failure. The Lovable or Bolt demo deletes documents on request because the founder wired a delete route. There is no soft-delete, no tombstone, no legal-hold flag, no per-matter archive export. A partner at the firm triggers a retention review, asks for the files on a closed matter from three years ago, and the answer is that they are gone. That conversation kills the vendor relationship. A document retention AI app rescue installs the schedule, the hold mechanism, and the archive export; deletes become soft-deletes; restores run from the audit trail.
Conflicts are the other silent failure. A real legaltech product cannot create a matter without running the client and every adverse party through the conflicts table. AI scaffolds have no conflicts table, no intake halt, no override flow. A single missed conflict in a bar-rules-regulated jurisdiction is a complaint waiting to happen. We add the conflicts table, the intake halt with an attorney override, and the secondary approval when an override touches a current client. Pilot firms treat that as table-stakes.
Sarah built a small-firm matter-management tool on Lovable and scheduled a pilot with a regional litigation boutique. The firm's general counsel sent a technical review questionnaire: retention schedule, privileged-access log, document storage ACLs, conflict-of-interest intake, e-signature verification. Sarah's Lovable scaffold cleared zero of those items. Documents were in a public Supabase Storage bucket, deletes were hard deletes, the audit log did not exist, and the conflict check was a commented-out TODO in the intake route.
Week one of the legaltech AI app rescue: we flipped all Supabase Storage buckets to private, moved every document fetch to signed URLs scoped per matter and per user with a five-minute TTL, and logged every signed-URL generation to the audit trail. We enabled RLS on matters, documents, clients, notes, and conflicts, wrote attorney-to-matter assignment policies, and added the CI test that fails the build on an unprotected legal table. We installed the retention schedule as a Postgres function that tombstones documents on matter close plus seven years and honours legal-hold flags.
Week two: we built the conflicts intake. A matters table row cannot be inserted without a conflicts row for each adverse party; a match halts the intake and requires an attorney override with a reason and a second-attorney approval. We added signature verification on DocuSign webhooks, envelope-to-matter mapping, and the privileged messaging migration off raw SMS to a channel with at-rest encryption. The pilot firm cleared the technical review and signed the engagement at the end of week two. Total legaltech rescue was $7,499 fixed, inside twelve business days.
Written finding list: retention, RLS, audit trail, storage ACLs, conflicts, e-signature, messaging. Shareable with outside counsel.
Attorney-to-matter RLS, private Storage buckets with signed URLs, audit trail middleware, policy CI tests. Fixed scope.
Close every Critical in a single week: retention, RLS, audit log, private buckets, conflicts, e-signature verification. Fixed $3,999.
End-to-end: audit + remediation + Clio or MyCase integration + Playwright suite + firm-pilot handoff. From $7,499.
Read how we shipped the private storage migration, the retention schedule, the conflicts intake, and the privileged-access audit trail on a Bolt legaltech scaffold in two weeks before the regional litigation boutique signed the engagement.
A legaltech AI app rescue covers the seven patches an AI-built legaltech MVP ships broken: document retention schedule, legaltech Supabase fix for RLS on matters and documents, privileged-access audit trail, private signed-URL storage, conflict-of-interest intake checks, e-signature webhook verification, and privileged messaging routing. Scope is a three-day audit at $499 that rolls into a fixed-price remediation.
Not as shipped. A document retention AI app needs a retention schedule tied to matter close, a legal-hold flag that overrides the schedule, tombstoned deletes so restore-after-delete is possible, and a per-matter archive export. Lovable scaffolds none of that and defaults Supabase Storage buckets to public. A document retention AI app rescue installs the schedule, the hold mechanism, and the archive export, typically in four to seven days.
A legaltech Supabase fix uses attorney-to-matter assignments as the access control primitive, not a flat tenant ID. A single attorney can be on dozens of matters at many firms, so the policy has to join through a matter_assignments table. We write the policies, add the assignment table, backfill from the existing data, and ship an automated policy test that runs on every migration.
Yes. A conflicts table keyed on client + adverse party + matter type is one of the standard deliverables on a legaltech rescue. We wire the intake flow to halt on a match, require an attorney override with a recorded reason, and add a second-attorney approval when the override involves a current client. The conflict check runs on every new matter and on every new party added to an existing matter.
A three-day legaltech audit is a fixed $499. You get a written finding list across retention, RLS, audit trail, storage ACLs, conflicts, e-signature, and privileged messaging. Every Critical and High finding ships with a patch diff you can merge. The PDF deliverable is written to be shareable with the firm's general counsel or outside compliance counsel.
We integrate with any practice-management system that offers a documented API. Clio and MyCase both support OAuth and webhooks; PracticePanther uses an API key. The rescue pattern is the same: signed webhooks, idempotent writes, a local mirror table for the entities you care about, and an RLS policy that scopes access by matter. Typical integration scope is $799 fixed per system.
Yes. We sign an NDA before we see the repo and we work within attorney-client privilege when the engagement is through outside counsel. We do not read live client files during audits — we use synthetic or anonymised fixtures. For active-litigation matters we can work under a protective order and scope access to non-privileged metadata only if that is what the retention counsel requires.
Send the repo under NDA. In 48 hours we return a written finding list covering retention, RLS, audit trail, storage ACLs, conflicts, and e-signature, with a fixed-price path to close each.