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.

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.

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.

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.

someone on your team maintains a spreadsheet to compensate for the tool
an automation failure now costs you real money
the platform bill is growing faster than your revenue
your team says "the platform cannot do that" every week
you want AI inside the workflow and the platform cannot host it
you cannot get a straight answer on who actually owns your code

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.

01

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.

02

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.

03

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.

04

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.

Scale up

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.

Keep shipping

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.

01

Languages and runtimes

  • TypeScript logo, KUMO primary language TypeScript
  • Python logo, KUMO language for AI workloads Python
  • Go logo, KUMO language for high-throughput services Go
  • Rust logo, KUMO language for performance-critical paths Rust
  • Node.js logo, KUMO API runtime Node.js
  • Bun logo, KUMO fast JavaScript runtime Bun
  • Ruby on Rails logo, KUMO supports Rails in production 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.

02

Product surfaces

  • React logo, KUMO web framework React
  • Next.js logo, KUMO web framework Next.js
  • Astro logo, KUMO framework for content-heavy sites Astro
  • React Native logo, KUMO framework for iOS and Android apps React Native
  • Expo logo, KUMO React Native tooling Expo
  • Tailwind CSS logo, KUMO design-system styling Tailwind CSS
  • shadcn/ui logo, KUMO component system shadcn/ui
  • Radix UI logo, KUMO accessible component primitives 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.

03

APIs, data, and architecture

  • Convex logo, KUMO real-time serverless backend Convex
  • Node.js logo, KUMO API runtime Node.js
  • Hono logo, KUMO HTTP framework Hono
  • Postgres logo, KUMO default database Postgres
  • Drizzle ORM logo, KUMO typed database access Drizzle
  • Redis logo, KUMO caching and queues Redis
  • Zod logo, KUMO schema validation Zod
  • Better Auth logo, KUMO authentication Better Auth
  • FastAPI logo, KUMO Python API framework FastAPI
  • Supabase logo, KUMO rapid backend platform 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.

04

AI models

  • OpenAI logo, KUMO builds AI on OpenAI GPT models OpenAI
  • Anthropic logo, KUMO builds AI on Anthropic Claude Anthropic
  • Google Gemini logo, KUMO multimodal AI model Gemini
  • Meta Llama logo, KUMO open-weight AI model Llama
  • Mistral logo, KUMO open-weight AI model Mistral
  • DeepSeek logo, KUMO open-weight AI model DeepSeek
  • ElevenLabs logo, KUMO production voice AI 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.

05

AI application layer

  • Vercel AI SDK logo, KUMO AI application framework Vercel AI SDK
  • Qdrant logo, KUMO managed vector store Qdrant
  • LangGraph logo, KUMO AI orchestration LangGraph
  • Hugging Face logo, KUMO open-weight model sourcing 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.

06

AI infrastructure and GPU

  • Ollama logo, KUMO self-hosted model runtime Ollama
  • FFmpeg logo, KUMO media processing 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.

07

Cloud, delivery, and jobs

  • AWS logo, KUMO deploys on AWS as an AWS Partner AWS
  • Google Cloud logo, KUMO production cloud Google Cloud
  • Microsoft Azure logo, KUMO production cloud Azure
  • Docker logo, KUMO containerised deployments Docker
  • Coolify logo, KUMO application deployment Coolify
  • Kubernetes logo, KUMO container orchestration Kubernetes
  • Turborepo logo, KUMO monorepo build system Turborepo
  • Terraform logo, KUMO infrastructure as code Terraform
  • GitHub Actions logo, KUMO CI/CD delivery 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.

08

Observability and quality

  • Sentry logo, KUMO application error monitoring Sentry
  • OpenTelemetry logo, KUMO distributed tracing OpenTelemetry
  • Playwright logo, KUMO end-to-end and AI browser testing 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.

09

Payments and integrations

  • Stripe logo, KUMO payments and billing Stripe
  • Razorpay logo, KUMO payments and billing Razorpay
  • Resend logo, KUMO transactional email Resend
  • Discord logo, KUMO team and notification workflows 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.