AI app rescue case studies — B2B SaaS, fintech, healthtech, agency outcomes.
Six documented AI app rescue engagements across Lovable, Bolt.new, Cursor, Replit Agent, v0, and Base44. Every case study below is a composite drawn from real client engagement patterns and published research — the kind of rescue Afterbuild Labs runs fixed-price, scoped up-front, and shipped under 19 days on average.
The Afterbuild Labs /case-studies cluster documents 6 rescue engagements across the major AI application builders: Lovable, Bolt.new, Cursor, v0, Base44, and Replit Agent. Industry coverage spans fintech (SMB accounting, broker-dealer reporting), B2B SaaS (workforce scheduling), healthtech (outpatient clinical workflow), digital marketing agency, and legaltech. Every study follows the same format — reported symptom, diagnostic findings, the engagement that ran, the work performed, and a verified outcome with specific metrics: days to ship, MRR at launch, customers kept through cutover, tests added, RLS policies written, infrastructure cost delta. Case stories are composites drawn from real engagement patterns; named-client studies replace composites as paid engagements publish with client consent. The average time-to-ship across the six engagements is 19 days, with 100% handoff rates and zero open-ended retainer lock-in.
- 6
- Rescues documented
- 19 days
- Average to ship
- 100%
- Handoff rate
- 6 / 6
- AI builders covered
Every AI app rescue case study indexed
Each rescue below shows the industry, the AI builder that produced the failure, the outcome headline with verified numbers, and the service tier that ran it. Click any card to read the full autopsy.
Lovable fintech MVP rescued — $0 → $12k MRR in 19 days
RLS disabled, OAuth pointed at localhost, Stripe webhook dropping half of checkouts. Deploy-to-Production Pass closed 18 pgTAP-verified policies and shipped the MVP.
- 19 days
- Rescue to launch
- $12k
- MRR at week 4
- 18
- RLS policies
Bolt.new to Next.js migration — B2B SaaS in 5 weeks, $900/mo → $0
Token spiral at $900/mo, 17 forking production URLs, contractor refusing to commit. Platform Escape rebuilt the app on Next.js 16 + Postgres with zero customer downtime.
- 5 weeks
- End to end
- $900 → $0
- Token spend/mo
- 84
- Customers kept
Cursor regression loop fix — 11 bugs/wk → 1, 500 clinicians live
Fragile tests, architectural drift past file seven, PHI logging to Sentry unredacted. Break-the-Loop Refactor codified ESLint + TypeScript rules and rewrote 88 deterministic tests.
- 11 → 1
- Bugs per week
- 88
- Deterministic tests
- 500
- Clinicians live
Base44 escape to Next.js — 12 agency apps in 63 days, $68k/yr saved
12 client apps trapped on Base44, credit billing misfiring, 3x platform price hike. Platform Escape retainer migrated everything to Next.js + Supabase on owned infra.
- 12 / 12
- Apps migrated
- $68.4k
- Saved year one
- < 9 min
- Total downtime
Replit Agent to Vercel migration — 28 days, $7M Series A unblocked
14 months of Replit Agent code blocking a $7M Series A on platform-concentration risk. Full migration to Vercel + Supabase + GitHub in 28 days, term sheet signed 8 days later.
- 28 days
- Replit to Vercel
- 11 min
- Cutover downtime
- $7M
- Series A closed
v0 prototype to production — 21 days to $2,470 MRR, 38 customers
Gorgeous v0 UI, no backend, Stripe keys in client code, placeholder webhooks. Finish-My-MVP wired Supabase, real auth, idempotent Stripe webhooks, and a working deploy.
- 21 days
- v0 to launch
- $2,470
- MRR at week 1
- 76%
- Trial → paid
Browse AI app rescue case studies by industry
Rescue patterns repeat inside verticals: fintech hits RLS and Stripe webhooks, healthtech hits PHI redaction and audit logs, agencies hit platform lock-in, SaaS hits auth and deploy. Pick a vertical to see which rescue applies.
Filters are visual cues · all rescues listed above cover every vertical
Ready to be the next AI app rescue case study?
Free rescue diagnostic
Send the repo. 48-hour audit, fixed fee, written rescue-vs-rewrite plan. No sales calls. If we rescue you, you get first refusal on the case study — with anonymization if you prefer.
Book free diagnostic →Emergency triage
One production-blocker diagnosed and fixed in 48 hours — auth down, Stripe failing, deploy white-screening. Fixed fee, no retainer lock-in.
Start emergency triage →Related AI app rescue resources
Every case study is one outcome of a larger rescue system. Browse the services, platform guides, and vertical briefs that sit behind these engagements.
How we construct these case studies
Every case study on this hub is a composite — a single narrative synthesized from several real rescue engagements that shared the same industry, stack, failure mode, and fix path. We use composites so we can publish the rescue pattern at full technical depth without identifying clients who are under NDA or who have not yet agreed to be named publicly.
What is accurate: industry, AI-builder platform, stack before and after, failure modes, fix sequence, approximate timelines, and outcome ranges. These describe work we actually did on real codebases.
What is illustrative: client names, founder names, pull quotes, exact dollar figures, and exact user counts. These are composed from multiple engagements and should not be read as point-in-time facts about a single company. As named clients publish and consent to being cited, we retire the corresponding composite and replace it with the real study.
The full counting rules for every quantified claim on this site — including “47 apps rescued,” “19 days average to production,” and “100% handoff rate” — live on the methodology page. If you spot an inconsistency between a case study and our methodology, email hello@afterbuildlabs.com and we will correct it with a dated note.
Got a broken AI-built app that looks like one of these?
Every case study above started the same way — a founder sent us a repo and a symptom list. 48-hour audit, fixed-fee proposal, no sales calls. Start with the free diagnostic and we will route you into the rescue tier that fits.