It worked in the demo.
It buckles under real users.
Built for a screenshot, not for scale. The first real traffic spike surfaces N+1 queries, missing indexes, no caching, and a data model that was never meant to hold a business. We fix the fundamentals and, if the platform itself is the ceiling, migrate you onto a stack that actually holds.
The demo never had to survive real usage.
- Pages that loaded instantly with 10 users now take seconds to load with a few hundred.
- Database queries are timing out or the database bill jumped without a clear reason why.
- You're hitting hard row, request, or execution limits on the no-code platform you built on.
- The app has crashed or gone unresponsive during a launch, a press mention, or a marketing push.
- You have no caching layer and no idea what your app actually does under concurrent load.
Fix the data model first. Migrate only if you actually have to.
Performance & data model audit
Identify N+1 queries, missing indexes, and unbounded queries that work fine at low volume and fail as usage grows.
Infrastructure assessment
Determine whether the current platform, including no-code tools, has a hard ceiling or can be optimized in place.
Migration plan, if needed
If the platform is the actual ceiling, plan a migration onto owned infrastructure with minimal customer-facing downtime.
Indexing, caching & queries
Implement the specific fixes: proper indexes, a caching layer, and rewritten queries that scale with your data.
Load testing
Test against your actual traffic profile to confirm the app holds under real load, not a synthetic benchmark.
Observability
Logging, error tracking, and uptime alerts so failures are visible before your users complain about them.
A stack that holds, with proof it holds.
- An optimized data model with real indexes. Queries that scale with your data instead of degrading with it.
- A caching layer. Where it actually matters for your traffic pattern, not caching for its own sake.
- Migration off the platform ceiling, if needed. Onto infrastructure you own outright.
- Load-tested results against your real traffic. A real number for how much scale you have, not a guess.
- Observability and alerting. So the next problem is visible before your users find it first.
Optimization first. Migration only if the data says so.
Final scope is set after the diagnostic identifies the real ceiling.
Optimize the data model, add indexing and caching, and get the existing stack production-ready.
Migrate off a no-code platform ceiling onto owned infrastructure, with us as the ongoing engineering team.
See the full pricing breakdown for every service.
If any of this sounds like you.
"We got traction faster than the app can handle."
Growth is the good problem. We make sure the infrastructure can actually catch up to the traction you worked for.
"It went viral and then it fell over."
You built fast to test an idea. Now the idea is working and the app needs to actually survive its own success.
What founders ask before scaling.
Do we need to leave our no-code platform entirely?
Not always. Some no-code and low-code platforms can be optimized in place with better data modeling, indexing, and caching. Others have a hard ceiling that genuinely requires migrating to owned infrastructure. We tell you which situation you're in before recommending a migration.
How much traffic can you get us to?
It depends on the starting architecture and your actual usage pattern, which is exactly what the diagnostic determines. We load-test against your real traffic profile, not a generic benchmark, so the number we give you is one you can rely on.
Will there be downtime during a migration?
We plan migrations to minimize or eliminate customer-facing downtime, using parallel infrastructure and a cutover window rather than taking the app offline to move it.
How do you decide between optimizing and rebuilding?
The diagnostic looks at your data model, query patterns, and platform limits. If the ceiling is structural, like a no-code platform's hard request or row limits, we recommend migration. If it's fixable with indexing, caching, and query optimization, we say so and charge accordingly.
What stack do you migrate to?
Whatever fits your product and team, typically a standard Postgres-backed backend with a modern framework. We pick the boring, well-supported option over anything trendy, because you have to run it after we leave.
Send us the repo and your traffic numbers.
A senior engineer reads your actual code and gives you a straight assessment of what it will take to scale. No sales engineer, no junior.