Built a real-time app with Framer AI?
We'll make it production-ready.
Real-time apps — chat, live collaboration, multiplayer features, live dashboards — have fundamentally different technical requirements than standard request-response web apps. Users expect sub-second updates, offline handling, and reliable message delivery. AI tools can set up a basic WebSocket connection, but production real-time features need connection management, message ordering, conflict resolution, and infrastructure that scales with concurrent users.
Real-time App challenges in Framer AI apps
Building a real-time app with Framer AI is a great start — but these challenges need attention before launch.
Connection management and reconnection
WebSocket connections drop constantly — network switches, phone sleep, server deploys. AI tools open a connection but don't handle disconnection, reconnection, or missed messages during downtime. Users see stale data or lose messages without knowing it.
Message ordering and delivery guarantees
Messages must arrive in order and must not be lost. Network issues can deliver messages out of sequence or duplicate them. AI-generated real-time code has no message ordering, no deduplication, and no delivery confirmation — which means lost messages and confused users.
Conflict resolution in collaborative editing
When two users edit the same content simultaneously, whose changes win? AI tools implement 'last write wins,' which silently discards one user's work. Production collaboration needs operational transforms or CRDTs to merge concurrent edits correctly.
Scaling concurrent connections
Each WebSocket connection holds server resources. A single server can handle hundreds of connections, but thousands require load balancing with sticky sessions, a pub/sub layer (like Redis), and horizontal scaling. AI tools don't implement any of this.
Presence and typing indicators
Showing who's online, who's typing, and who's viewing a document requires frequent presence updates that can overwhelm your server. These updates need throttling, batching, and efficient broadcast — details AI tools skip entirely.
Message persistence and history
Real-time messages need to be stored for later retrieval — chat history, edit history, activity logs. AI tools send messages through WebSockets but don't persist them, so refreshing the page loses the entire conversation.
Security in real-time channels
Every WebSocket message needs authentication and authorization. Who can send messages to this channel? Who can read them? AI tools often create open WebSocket endpoints where anyone can listen to or inject messages into any conversation.
What we check in your Framer AI real-time app
Common Framer AI issues we fix
Beyond real-time app-specific issues, these are Framer AI patterns we commonly fix.
Missing SEO metadata on generated pages
Framer AI generates visually complete pages but frequently omits Open Graph tags, canonical URLs, structured data, and meta descriptions that search engines and social sharing require.
No form backend or data handling
Contact forms, newsletter signups, and lead capture elements are rendered in the UI but submit to no endpoint by default, silently discarding user submissions.
Heavy animation runtime hurting Core Web Vitals
Framer Motion's runtime and the animation-heavy pages Framer AI generates add significant JavaScript weight, causing poor Largest Contentful Paint and Total Blocking Time scores that hurt SEO.
CMS content limits blocking at scale
Framer's built-in CMS has item limits, no custom field types, and no programmatic data import. Apps that grow beyond simple blog posts hit these ceilings quickly.
Start with a self-serve audit
Get a professional review of your Framer AI real-time app at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
Frequently asked questions
Can I build a real-time app with Framer AI?
Framer AI is a great starting point for a real-time app. It handles the initial scaffolding well, but real-time apps have specific requirements — connection management and reconnection and message ordering and delivery guarantees — that need professional attention before launch.
What issues does Framer AI leave in real-time apps?
Common issues include: missing seo metadata on generated pages, no form backend or data handling, heavy animation runtime hurting core web vitals. For a real-time app specifically, these issues are compounded by the need for connection management and reconnection.
How do I make my Framer AI real-time app production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most Framer AI-built real-time apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
How much does it cost to fix a Framer AI-built real-time app?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger real-time app projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your Framer AI real-time app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.