Move from an AI-built prototype to a production-ready application.
You proved the idea. Datably helps you create the technical foundation needed to launch, support real users, manage risk, and scale.
Built with Lovable, Replit, Claude, Bolt, Cursor, or another AI tool? That's exactly who this is for.
The reality
AI made building faster. Production still asks the same hard questions.
A working prototype is not the same as a production-ready application. Security, authentication, data handling, deployment, monitoring, and cost control still need real answers before real users show up.
The gap that shows up at launch.
| AI prototype | Production application | |
|---|---|---|
| Environments | Single environment, live edits | Separate dev / staging / production with promotion |
| Authentication | Basic or none | SSO, MFA, session management, RBAC |
| Data | Sample data in a shared DB | Backups, migrations, access controls, PII handling |
| Deployment | Click a button, hope for the best | Repeatable pipelines with rollback |
| Monitoring | None | Uptime, errors, performance, alerting |
| Cost | Whatever the tool charges | Right-sized and forecasted |
| Ownership | The builder's account | The company's infrastructure and code |
Every layer between prototype and production.
Architecture review
Is the current approach going to hold up? Where are the fault lines?
Infrastructure & hosting
Environment fit, provisioning, and reproducibility.
Security & authentication
Identity, secrets, permissions, and the controls production actually requires.
Database & storage
Data modeling, migrations, backups, and safe access patterns.
Deployment environments
Dev, staging, and production separated properly — with a working release process.
Quality assurance
Automated tests where they matter and a manual pass where they don't.
Performance & cost
Right-size the stack before usage decides for you.
Monitoring & support
Visibility into what's happening and a plan for when something breaks.
Ongoing management
Optional handoff into a Strategic Partnership once you're live.
From prototype to live in a defined path.
01
Review the current application
Assess architecture, security, data, and deployment against production requirements.
02
Prepare & validate the environment
Stand up production, harden security, wire monitoring, and validate end-to-end.
03
Launch with ongoing support
Ship it — with optional Strategic Partnership coverage for what comes after.
The non-negotiables before real users.
Auth
Identity & access
SSO, MFA, RBAC, and a real session model — not a shared password.
Data
Backups & migrations
Automated backups, tested restores, and controlled schema changes.
Ops
Monitoring & on-call
Uptime, error, and performance visibility with someone paged when it breaks.
$$$
Cost & scale
Right-sized environments and a forecast for what the next 10x costs.
Common questions.
We built with Lovable / Replit / Claude — can you still work on it?
Yes. AI-generated code is code. We review it the same way we review any other codebase and take responsibility for the parts that need to be production-grade.
Do you rewrite what we built?
Only if we have to. The default is to keep what works, harden what doesn't, and add the layers production requires — auth, environments, monitoring, backups.
How long does this take?
The review is a defined engagement — typically 1–2 weeks. Getting to production depends on what the review finds, but most prototypes are 4–8 weeks away from a safe launch.
What happens after launch?
Most teams roll straight into a Strategic Partnership so we continue owning the operational surface: monitoring, incidents, patching, and roadmap engineering.
Keep building quickly. Grow confidently.
Request an AI Application Review. We'll show you the honest gap between where you are and production-ready.