Bubble. Compute is billed in workload units, so your cost scales with usage and a busy month can turn success into a much larger bill than you planned for. Certain sorted searches hit a documented ceiling around 50,000 records. And when you raise, investors ask for the codebase ownership a hosted platform cannot hand over.
Migration engineering
Your app builder got you here. It will not get you further.
Bubble, Airtable, Zapier, Glide, Webflow: every one of them is built to get a product started, not to run the company it becomes. The bills climb with every new user, the workarounds pile up, and the feature you need next is one the platform will never ship. No-code is where products start. Custom is where they last. We take you there in phases, while everything keeps running.
Every no-code platform has a ceiling
You will hit one of these. The only question is when.
Not because you chose wrong, but because these platforms were built to get you started, not to run a business at scale. Here is exactly where each wall sits, so you can find your own.
Airtable. A 5-requests-per-second API limit per base, a spreadsheet data model without true joins, and no self-hosting. It was built to be a database you share, not the backend a real product runs on.
Zapier and Make. Per-task pricing that grows with your volume, and connector-level error handling. At real scale, retries, partial failures and rate limits are where operations actually live, and where connectors stop.
Glide. Outgrowing Glide means remapping the data, computed columns, actions, screens and permissions by hand. There is no lift-and-shift into a bigger system, so the migration work is real either way.
Webflow. Built to publish marketing sites, not to run a database-driven application, and it shows the moment your product becomes one.
We also migrate Softr, FlutterFlow, WeWeb, Xano, Retool and mixed stacks that combine several of these with Stripe, HubSpot and spreadsheets. We inventory the whole operating system, then keep the stable parts and replace the risky or limiting ones. Recognise your bill or your workaround in that list? That is the wall. The question is not whether to deal with it, it is whether to deal with it before or after it breaks something customers see.
Built it with an AI builder like Lovable or Bolt instead of a no-code platform? Different wall, more urgent.
You are already on it
How to tell no-code has stopped helping and started holding you back.
If any one of these is true, the platform is no longer the thing moving you forward. It is the thing in the way.
None of these get better on their own, and they get more expensive fastest right when the product finally starts working. The tool was never going to grow into a company. This is where it hands off to custom.
How the migration works
Phased, and your product stays live.
Map
Map the real workflow end to end, including the parts that live in people's heads and spreadsheets, not just what the tool shows on screen.
Replace
Replace the highest-pain piece first as production code, running alongside the existing system. For AI-built apps, the security fixes land before anything else.
Prove
Prove it in production with the old path kept as a fallback, so the switch only happens once the new one has clearly earned your trust.
Repeat
Repeat by priority, retiring the platform when nothing depends on it, and keeping whichever parts still genuinely earn their place in the stack.
What it costs
What a no-code migration costs
The short answer
Migrating a no-code product to custom software at KUMO starts at $20K to $50K for a first phased build over 4 to 16 weeks, and $50K to $100K for multi-workflow platforms. Migration is phased: your current system stays live until each replaced piece is proven in production. These are the live custom software development bands, no new numbers. If it turns out you are not at the wall yet, we will tell you on the call, and you keep your money.
Starter Build
$20K to $50K
4 to 16 weeks
A first phased migration: the highest-pain workflow rebuilt as production code, running alongside your builder until it is proven.
Grow Build
$50K to $100K
16 to 24 weeks
A multi-workflow platform migration: several pieces replaced and connected, with the platform retired last, not first.
Support and Growth Team
$5K to $10K per month
Ongoing, cancel with 30 days notice
The engineering team on retainer once you are off the builder: new workflows, AI, and the next migration piece.
For AI-built apps, the audit-and-stabilise step is where every engagement starts, inside the Starter Build band, and if the audit says your app is sounder than you feared, we will tell you that too.
Proof
Replacing broken workflows on running revenue systems.
Equipp (Ralco Group). A production B2B and B2C rental marketplace: catalogue, payments and deposits, inventory, operations dashboard. In the client's own Clutch review, the work included rebuilding the billing system and repairing a broken payment gateway on a live revenue system.
Read the case study →CampaignHQ. Our own SaaS, built and run by us when off-the-shelf tools hit their ceiling for the customer-engagement workflows we needed. Live on G2 and Capterra, running on AWS, shipping to customers every day.
Read the case study →Anti-ceiling, not anti-builder. KUMO ships and operates n8n automations in production for clients, so we know exactly where a handy tool ends and a system you can bet a company on begins. We build with no-code where it genuinely wins.
Built with n8n →Assembled per build
Technologies we build with.
There is no single KUMO stack. Every build gets its own, assembled for your workload, your data, your team, and whoever maintains the system after handover. These are the technologies we assemble those stacks from, and why each earns its place.
Languages and runtimes
- TypeScript
- Python
- Go
- Rust
- Node.js
- Bun
- Ruby on Rails
TypeScript end to end for most products: one language across frontend and API cuts handover cost and hiring risk. Python where the workload is AI-heavy. Go where raw throughput decides the architecture, and Rust on hot paths where every millisecond is money. We run Node.js and adopt Bun where its speed pays. Our engineers shipped and scaled Ruby on Rails at Volopay, and we still support Rails codebases in production.
Product surfaces
- React
- Next.js
- Astro
- React Native
- Expo
- Tailwind CSS
- shadcn/ui
- Radix UI
React and Next.js for web products. Astro for content-heavy sites where load speed is the feature. React Native with Expo for iOS and Android from one codebase, native modules where the product demands them. Tailwind CSS with shadcn/ui and Radix for design systems that ship fast. Real-time and streaming interfaces with WebSockets and server-sent events, because AI products that make users wait for a full response feel broken.
APIs, data, and architecture
- Convex
- Node.js
- Hono
- Postgres
- Drizzle
- Redis
- Zod
- Better Auth
- FastAPI
- Supabase
Two backend tracks, chosen per product. Convex for real-time serverless products: queries, mutations, actions, a scheduler, cron jobs, storage, and live subscriptions. Node.js services with Hono and typed oRPC over Postgres and Drizzle ORM for relational, retrieval-heavy products. Postgres is extended with pgvector for vector search and full-text search, so most AI features ship without a second database. Redis for caching and queues. Zod for end-to-end validation, Better Auth for authentication, and FastAPI or Supabase where they fit the job.
AI models
- OpenAI
- Anthropic
- Gemini
- Llama
- Mistral
- DeepSeek
- ElevenLabs
Model choice is an engineering decision, not a loyalty program. OpenAI GPT and Anthropic Claude for frontier reasoning, Google Gemini where multimodal or context length wins. Open-weight models, Llama, Mistral, DeepSeek, self-hosted when privacy or unit economics demand it. Specialist models where the product needs a specialist: ElevenLabs and dialogue-native TTS for production voice, Whisper for speech to text, dedicated embedding and reranking models for retrieval quality, image and vision models for documents and floor plans. Every model sits behind a provider-swappable abstraction, so switching is a configuration decision, not a rewrite.
AI application layer
- Vercel AI SDK
- Qdrant
- LangGraph
- Hugging Face
AI features are built on the Vercel AI SDK and Convex Agent and RAG components: structured outputs, agentic tool use, streaming, and embeddings. Retrieval on pgvector by default, with Cohere reranking and Tavily web-search fallback, and managed vector stores like Qdrant at scale. Orchestration with LangGraph or custom code, tool connectivity over MCP, the protocol now standardising how AI systems talk to software. And the part that decides whether AI survives production: evals before ship, tracing in production, structured outputs, semantic caching, and model routing to control cost.
AI infrastructure and GPU
- Ollama
- FFmpeg
We deploy AI through AWS Bedrock, Google Vertex AI, and Azure OpenAI where enterprise controls matter, direct APIs where speed matters, and vLLM or Ollama where self-hosting wins. Self-hosted GPU inference on RunPod with a scale-to-zero strategy, and image models through fal.ai. Media assembly and normalisation with FFmpeg.
Cloud, delivery, and jobs
- AWS
- Google Cloud
- Azure
- Docker
- Coolify
- Kubernetes
- Turborepo
- Terraform
- GitHub Actions
AWS first: KUMO is an AWS Partner and runs its own SaaS, CampaignHQ, on AWS in production, with S3, EC2, CloudFront, and Route 53. Also Google Cloud, Azure, and client infrastructure including on-prem. Docker everywhere, Coolify and Kubernetes for deployment, serverless and edge where they fit. Monorepos on Turborepo, infrastructure as code with Terraform, background jobs on Trigger.dev, and delivery through GitHub Actions CI/CD.
Observability and quality
- Sentry
- OpenTelemetry
- Playwright
Sentry for application errors, Langfuse for LLM traces, model metadata, and token usage, and OpenTelemetry for distributed tracing. End-to-end and AI-driven browser testing with Playwright. Cost, latency, and error tracking by workflow and model, so problems surface before customers see them.
Payments and integrations
- Stripe
- Razorpay
- Resend
- Discord
Billing and payments with Stripe and Razorpay, subscriptions, webhooks, tax, and invoicing. Transactional email through Resend, team workflows over Discord, and the Google ecosystem, OAuth, Drive, and Sheets, wired in where products need it.
FAQ
No-code to custom, answered straight.
When should we move from no-code to custom software? +
The moment the platform starts costing you more than it saves: weekly workarounds, spreadsheet patches, bills growing faster than revenue, or a roadmap the vendor controls instead of you. In practice, if you are already asking the question, you are usually feeling the ceiling.
How much does it cost to move from a builder to custom? +
$20K to $50K for a first phased build over 4 to 16 weeks, $50K to $100K for multi-workflow platforms, then $5K to $10K per month if you want our team to keep shipping. Phasing exists to keep you at the bottom of that range, replacing only what has actually hit the wall.
Do we lose our data or have downtime during migration? +
No. Each piece is replaced alongside the running system, proven with the old path as fallback, then switched. The platform is retired last, not first.
Can you keep some of our stack? +
Yes, usually. n8n stays where it wins, Supabase stays where it fits. Custom replaces the pieces that hit the ceiling, not everything.
Who owns the code? +
You do, from day one. Source code, infrastructure as code, docs, in your GitHub organisation. Full IP transfer, no licensed components.
Tell us what you built and where it is stuck.
30 minutes, no deck. Tell us the tool, the traction, and the wall. We will tell you straight whether it is a configuration fix, a platform-tier fix, or an engineering problem, and for AI-built apps, whether anything needs securing this week. Honest answers, and only some of them are us.