AI can help you build and change an application quickly. Keeping that application secure, understandable and reliable in production still requires experienced judgement. iTechOza provides monthly human engineering oversight for apps created with Lovable, Replit, Base44, Bolt, v0, Firebase Studio, Google AI Studio and other AI-assisted workflows.
Use your plan for approved code reviews, production fixes, access and data checks, dependency upkeep, performance improvements, release verification and technical documentation. We first confirm that the app is stable enough for recurring support and recommend recovery when it is not.
A generated interface can look complete while important behavior remains spread across browser code, authentication rules, databases, edge functions, integrations and deployment settings. As the app changes, founders need a controlled way to decide what is safe to release, what needs specialist attention and what should be documented for future ownership.
A polished interface does not prove that authorization, tenant isolation, server-side validation or database policies are correctly enforced.
AI-generated changes may duplicate logic, introduce inconsistent patterns or solve one symptom without preserving the wider architecture.
Builders, hosting products, databases, packages and AI models change, while a production app still needs compatible builds, costs and ownership.
When every change goes live without a branch, review, test or rollback path, small improvements can break authentication, data or revenue workflows.
The monthly backlog is agreed with you and completed within reserved capacity. Work focuses on the highest-risk or highest-value approved changes rather than attempting to rewrite the entire application every month.
Review important changes before they become production risk.
Protect the boundaries between users, roles, organizations and records.
Resolve approved defects and recurring errors in the live product.
Create a predictable path from AI-generated change to production.
Keep the app supportable as its tools and packages evolve.
Identify technical waste before it becomes a user or budget problem.
Maintain the connected journeys the AI-built app depends on.
Make the application easier to understand and hand over over time.
| Layer | Representative coverage |
|---|---|
| AI app builders | Lovable, Replit, Base44, Bolt, v0, Firebase Studio and Google AI Studio, subject to technical fit. |
| AI coding workflows | Cursor, GitHub Copilot, Codex and other source-code-based AI assistants. |
| Frontend | React, Next.js, Vite, Vue, JavaScript, TypeScript, Tailwind CSS and common UI libraries. |
| Backend and data | Node.js, serverless/edge functions, Supabase, Firebase, PostgreSQL and approved custom APIs. |
| Auth and integrations | Supabase Auth, Firebase Auth, OAuth, JWT, Stripe, email, webhooks and third-party APIs. |
| Delivery | GitHub/GitLab, Vercel, Netlify, Replit Deployments, builder hosting, cloud/VPS environments and CI/CD. |
| Observability | Platform logs, Sentry, Vercel Observability, Supabase advisors and configured analytics/monitoring tools. |
Each plan reserves developer capacity for approved review, maintenance, testing, documentation and release work. The active backlog and review workflow are confirmed before the cycle begins.
| Plan feature | Essential Care | Growth Care | Priority Care |
|---|---|---|---|
| Developer capacity | 5 hours/month | 10 hours/month | 20 hours/month |
| Initial response target | 2 business days | 1 business day | 4 business hours* |
| AI-generated change review | Limited / prioritized | Recurring | Priority |
| Bug fixes and minor improvements | Included | Included | Included |
| Platform/dependency review | Monthly | Monthly | Monthly |
| Monitoring review when configured | Monthly | Twice monthly | Weekly high-severity review |
| Release assistance | Within capacity | Within capacity | Priority within capacity |
| Technical report | Monthly summary | Detailed report | Detailed report + ownership roadmap |
| Queue priority | Standard | Enhanced | Priority |
Initial response means acknowledgement, assessment and coordination during published business hours. It is not a diagnosis or resolution-time guarantee. Publish the faster Priority target only when iTechOza can staff it consistently.
We agree on the maintenance backlog at the start of each cycle. An approved critical issue or high-risk AI-generated change can replace lower-priority work within the reserved capacity.
Authentication, authorization, tenant isolation, exposed secrets and unsafe data behavior are reviewed before ordinary improvements.
Approved failures affecting users, revenue, data or core workflows receive the next priority.
Changes crossing authentication, data, payments, integrations or deployment are reviewed before routine visual edits.
Relevant deprecations, unsupported versions and upcoming release blockers are scheduled by urgency.
Refactoring, documentation and small product changes use remaining capacity after higher-risk work.
A lighter preventive option for a stable AI-built app that changes infrequently. Every three months, we review the app’s current condition, complete approved minor corrections within the allowance and provide an ownership-focused technical report.
Get Estimate for an AI-Built App Health Review
Receive support every month under the selected plan and prepay the three-month term. The work still happens monthly; only the commitment and billing schedule change.
Recommended incentive: include the initial AI-built app onboarding and ownership review at no additional charge for clients who prepay a three-month term. This creates meaningful value without discounting reserved review capacity.
Monthly-plan hours normally expire at month-end. For a prepaid three-month term, up to 25% of one month’s unused capacity may roll forward once, but never beyond the end of the paid quarter.
After an approved AI-Generated App Recovery engagement, add a short oversight period while the stabilized app returns to normal development and real users.
Recurring maintenance starts with a fit and ownership review. The goal is to create a controlled collaboration model without taking away the speed that made AI-assisted development attractive.
We review source access, platform accounts, database ownership, deployment, environments, integrations and current documentation.
We assess critical journeys, authentication, data rules, known errors, dependencies, monitoring and the current release path.
We recommend capacity and agree how AI-generated changes are submitted, reviewed, approved, tested and released.
We work through approved risks, bugs, updates and change sets in priority order within the reserved capacity.
The affected journey is checked in the agreed environment and production actions happen only with client approval.
You receive completed work, capacity used, known risks, ownership gaps and recommended next priorities.
| Report section | What it communicates |
|---|---|
| Changes reviewed | Submitted change sets, risk level and review outcome. |
| Work completed | Approved fixes, updates, hardening and documentation. |
| Capacity | Hours used, remaining/expired capacity and approved extra work. |
| Verification | Environment, journeys and evidence used for focused checks. |
| Ownership risks | Platform dependencies, access gaps and undocumented critical behavior. |
| Next priorities | Recommended review, stability and ownership work for the next cycle. |
Reliable maintenance requires context, consistency and good judgement. We learn the application over time, keep changes focused and help clients distinguish urgent work from work that can be planned.
Experience across SaaS, web and mobile applications, APIs, databases, integrations and production support.
We can work inside AI-assisted workflows while understanding the frameworks, databases, functions and hosting underneath them.
Review does not stop at the visible interface when authentication, policies, APIs or server logic control the real risk.
We can onboard apps created by founders, agencies, internal teams or multiple AI tools after a technical fit review.
We prefer source ownership, least-privilege access, reviewable changes, focused testing, explicit approval and rollback awareness.
Founders receive a clear explanation of what matters now, what can wait and what requires a separate project.
You used an AI builder to launch but want an experienced team to protect production and explain technical decisions.
Your team uses coding agents heavily and needs a consistent human review and release layer.
A useful operational app now needs access control, reliability and ongoing ownership.
You need confidential senior review or maintenance capacity for a client app built through AI workflows.
The product works, but architecture, data rules, ownership and release practices need to become understandable.
A recently stabilized or migrated product needs continuing oversight instead of returning to uncontrolled changes.
Share the builder, current production status, ownership and support priorities. We will recommend monthly care, a quarterly review or a recovery step before requesting sensitive technical access.
We will review the platform, ownership and current priorities, then contact you with any questions and the recommended next step. We aim to reply within two business hours on business days.
AI-built app maintenance is ongoing human engineering support for an application created or heavily modified with tools such as Lovable, Replit, Base44, Bolt, v0, Firebase Studio, Google AI Studio or AI coding agents. It can include code review, production fixes, access-rule checks, dependency upkeep, release verification, performance work and monthly technical reporting.
We can review applications created with Lovable, Replit, Base44, Bolt, v0, Firebase Studio, Google AI Studio, Cursor and other AI-assisted development workflows when the source code, runtime, database and deployment model are technically supportable. Compatibility is confirmed during onboarding rather than assumed from the tool name alone.
Yes. The service is designed for founders and teams that used AI to launch a working product but want experienced developers to supervise production changes. We explain priorities in plain language and request secure technical access only after the app qualifies for a plan.
AI-Generated App Recovery is a one-time service for a broken, unstable, unreleasable or platform-locked application. Monthly maintenance begins after the app is stable enough for recurring care and reserves ongoing capacity for review, fixes, updates and controlled releases.
We review changes that are submitted through the agreed workflow and prioritized within the selected plan. The service does not automatically supervise every prompt or edit made outside that workflow. High-risk authentication, data, payment, integration and deployment changes should be routed for review before production release.
Yes. The purpose is not to stop AI-assisted development. We establish branch, review, testing and release rules so AI-generated changes can be assessed before they affect production. Uncoordinated direct production changes may need to be excluded from support commitments.
When Supabase is part of the application, we can review relevant authentication, exposed tables, Row Level Security policies, storage access and service-role usage within the approved scope. This is practical application hardening, not a penetration test or compliance certification.
Migration and ownership work can be provided, but it is usually a separate project because the effort depends on code export, databases, authentication, storage, functions, secrets, domains and provider-specific services. After migration and stabilization, the app can enter a monthly plan.
We agree on a prioritized backlog for code review, production bugs, access and data risks, approved updates, performance work, release checks and documentation. Engineering, directly related testing and monthly reporting use the available plan capacity.
Standard monthly-plan hours normally expire at month-end because capacity is reserved in advance. An eligible prepaid three-month commitment may allow up to 25% of one month's unused capacity to roll forward once, but not beyond the paid quarter.
No. Initial response means acknowledgement, assessment and coordination during published business hours. Resolution depends on reproducibility, app condition, access, platform limits, third-party services, review depth and available plan capacity.
Standard plans do not include 24/7 monitoring, weekend availability, security-incident response or guaranteed resolution SLAs. Extended coverage must be separately contracted with defined monitoring, staffing, escalation and communication rules.
Small, clearly defined improvements may fit when they do not displace higher-risk maintenance. Major features, redesigns, architecture changes, new modules and large migrations are estimated separately so the support plan remains predictable.
No responsible maintenance service can guarantee complete security. We can identify and improve practical risks within scope, including exposed secrets, access rules, unsafe client-side logic, dependency issues and production configuration. Formal security testing requires a separate scope.
Access may include a repository, platform workspace, preview deployment, logs, database dashboard, monitoring and limited provider roles. Passwords, keys and tokens are never collected through the public enquiry form and are exchanged later through an approved secure method using least privilege.
We complete a technical fit and baseline review covering source ownership, architecture, deployment, database and authentication, known issues, release workflow, monitoring and current risks. We then confirm whether the app can enter maintenance or needs recovery first.
Yes. You can receive work monthly under the chosen plan and prepay a three-month commitment. The recommended incentive is an included onboarding and AI-built app health review rather than a discount on reserved engineering capacity.
Cost depends on reserved capacity, initial-response target, codebase condition, platform dependencies, database and authentication design, release workflow and required testing. We review the app first, then recommend a plan and confirm commercial terms before recurring work begins.
Tell us what built the app, where it runs and which changes need human oversight. We will review the details and recommend a monthly plan, quarterly ownership review or recovery step.
Get My AI-Built App Support Estimate