We get asked daily: 'how much for an app?' Answer: it depends.

But we know that's frustrating. So we made transparent pricing.

## Small App — €7,000
MVP, up to 5 screens. Perfect for starting out.

## Medium App — €14,000
Full product with backend, admin panel, integrations.

## Large App — Enterprise
AI, dedicated team, architecture built for years.

## What's included
- Design (UI/UX)
- Development (frontend + backend)
- Deployment
- Post-launch support (30-90 days)

No hidden costs. No 'actually, it'll be more'.

Breaking down the budget: design, backend, frontend, AI, devops. No guessing.

How much does an app cost in 2026? Real numbers

Since 2018 we've built over 50 mobile apps. We tested both frameworks in production.

## Our pick: React Native + Expo

Why?

1. **Economics** — One team, two platforms. No compromises.
2. **Ecosystem** — Expo SDK, EAS Build, OTA updates.
3. **New Architecture** — Fabric, TurboModules, JSI. Near-native performance.
4. **Shared code** — With Next.js/web you share logic, types, and often UI.

## When Flutter?

When you need:
- Heavy 60fps animations (games, AR)
- Custom rendering beyond standard UI
- Apps primarily for emerging markets (better perf on low-end devices)

## Case: SportXpert

React Native + shared business logic with Next.js frontend. 40% faster dev than separate native.

After 50+ mobile deployments we bet on one stack. Here's why and when the other makes sense.

React Native vs Flutter 2025: our pick after 50+ projects

2026 is the year AI stopped being an add-on and became the foundation. Companies treating AI as core product — not a feature — are seeing 3x faster growth.

## What actually works

**1. AI-powered search** — Vector search instead of SQL LIKE. Users find what they want even without exact keywords.

**2. Auto translations** — Not Google Translate, but fine-tuned models. One of our clients cut translation costs by 70% and entered 30+ markets.

**3. Product recommendations** — Collaborative filtering + embeddings. +15-25% conversion lift.

## What to avoid

Don't build a chatbot 'because everyone has one'. AI without a real problem to solve is wasted money.

No hype — real AI use cases that deliver ROI. From chatbots to product recommendations.

AI in apps: what actually works in 2026

# Full-Stack Type Safety with Axolotl, Zeus, and Vite

I've been building GraphQL APIs for years, and the biggest pain has always been keeping types in sync. You write your schema, manually create TypeScript types for resolvers, generate client types, and hope nothing drifts. One typo in a resolver return type and you're debugging runtime errors.

This example shows a different approach - true end-to-end type safety from schema to React components, running on a single server.

## The Setup

The `yoga-federated` example runs everything on one port:

* **Backend**: Express + GraphQL Yoga with Axolotl-generated types
* **Frontend**: React + Vite with Zeus-generated GraphQL client
* **Both**: Same server, same origin

http://localhost:4002/         -> React Frontend (SSR)

http://localhost:4002/graphql  -> GraphQL Playground

In development, Vite runs as Express middleware for HMR. In production, Express serves the built frontend. One deployment, zero CORS config.

## The @resolver Directive

Here's the schema:

```gql
type Todo {
  _id: String!
  content: String!
  done: Boolean
}

type AuthorizedUserMutation {
  createTodo(content: String!, secret: Secret): String! @resolver
  todoOps(_id: String!): TodoOps! @resolver
}

type Query {
  user: AuthorizedUserQuery @resolver
}
```

The `@resolver` directive marks which fields need implementation. Fields without it are auto-resolved from the parent object.

```gql
type Query {
  user: AuthorizedUserQuery @resolver # ← needs code
}

type User {
  _id: String! # ← resolved from parent
  username: String! # ← resolved from parent
}
```

This is what makes Axolotl work well with AI assistants. When Copilot or Cursor sees a schema, it knows exactly which fields need resolvers and which don't. No guessing.

Prompt an AI with "Implement all @resolver fields" and it generates the right code because the schema is explicit about what needs implementation.

Run `axolotl build` and you get typed models:

```ts
// Auto-generated src/models.ts
export interface Todo {
  _id: string;
  content: string;
  done?: boolean | undefined | null;
}

export type Models = {
  ['AuthorizedUserMutation']: {
    createTodo: {
      args: {
        content: string;
        secret?: Secret | undefined | null;
      };
    };
  };
};
```

Write resolvers with full type inference:

```ts
// src/todos/resolvers/AuthorizedUserMutation/createTodo.ts
import { createResolvers } from '../../axolotl.js';

export default createResolvers({
  AuthorizedUserMutation: {
    createTodo: async ([source], { content }) => {
      // TypeScript knows `content` is string
      // TypeScript knows this must return string
      const _id = Math.random().toString(8);
      db.todos.push({ owner: src._id, content, _id });
      return _id;
    },
  },
});
```

Return a number instead of a string and TypeScript complains immediately.

## Micro-Federation

The example splits schemas by domain:

```ts
src/
├── todos/
│   ├── schema.graphql
│   └── resolvers/
├── users/
│   ├── schema.graphql
│   └── resolvers/
└── resolvers.ts
```

Axolotl merges them:

```ts
// src/resolvers.ts
import { mergeAxolotls } from '@aexol/axolotl-core';
import todosResolvers from '@/src/todos/resolvers/resolvers.js';
import usersResolvers from '@/src/users/resolvers/resolvers.js';

export default mergeAxolotls(todosResolvers, usersResolvers);
```

Types flow through the merge.

## Frontend with Zeus

Zeus generates a typed GraphQL client from the schema:

```ts
// frontend/src/api.ts
import { Chain } from '../../src/zeus/index';

export const createGqlClient = (token?: string) => {
  const headers: Record<string, string> = {
    'Content-Type': 'application/json',
  };
  if (token) {
    headers['token'] = token;
  }
  return Chain('/graphql', { headers });
};
```

Queries are type-safe:

```ts
// frontend/src/hooks/useTodos.ts
const fetchTodos = async () => {
  const data = await gql()('query')({
    user: {
      todos: { _id: true, content: true, done: true },
    },
  });

  // TypeScript knows data.user?.todos is Todo[]
  if (data.user?.todos) {
    setTodos(data.user.todos);
  }
};
```

Mutations too:

```ts
const createTodo = async (content: string) => {
  await gql()('mutation')({
    user: {
      createTodo: [{ content }, true],
    },
  });
};
```

The `[{ content }, true]` syntax means: pass these arguments, return this field. TypeScript validates that `content` matches the schema.

## Express + Vite on One Server

The whole stack runs on one Express server:

```ts
// src/index.ts
async function startServer() {
  const app = express();

  // Mount GraphQL
  const { yoga } = adapter({ resolvers, directives });
  app.use('/graphql', yoga);

  // Development: Vite middleware for HMR
  if (!isProduction) {
    const vite = await createViteServer({
      server: { middlewareMode: true },
      appType: 'custom',
    });
    app.use(vite.middlewares);
  } else {
    // Production: serve built assets
    app.use(sirv(resolve(__dirname, '../dist/client')));
  }

  // SSR for all other routes
  app.use('*all', async (req, res) => {
    const { html } = await render(req.originalUrl);
    res.send(html);
  });
}
```

You get:

* HMR in development
* SSR for SEO
* One deployment artifact
* No proxy config

## The Type Flow

A todo travels through the system like this:

1. **Schema** defines `createTodo(content: String!): String!`
2. **Axolotl** generates `args: { content: string }` for resolvers
3. **Resolver** uses `{ content }` with TypeScript support
4. **Zeus** generates client types from the same schema
5. **React hook** calls `createTodo: [{ content }, true]` with type checking
6. **Response** comes back typed

Change the schema, run `axolotl build`, and TypeScript shows you what broke.

## Try It

```ts
cd examples/yoga-federated
npm install
npm run dev
```

Open http://localhost:4002:

![](https://aexol-cms.fra1.cdn.digitaloceanspaces.com/aexolcom/media/screenshot-login-1765204379116.png)

Register and you're in and can create todos

![](https://aexol-cms.fra1.cdn.digitaloceanspaces.com/aexolcom/media/screenshot-todo-created-1765204389217.png)

GraphQL Playground at http://localhost:4002/graphql:

![](https://aexol-cms.fra1.cdn.digitaloceanspaces.com/aexolcom/media/screenshot-playground-1765204385463.png)

## What I Like About This

After using this pattern, a few things stand out:

1. **Schema changes propagate everywhere** - modify a field, run build, TypeScript tells you what broke on both backend and frontend
2. **AI assistants actually help** - the `@resolver` directive means Copilot knows what to implement without explaining the architecture
3. **One `npm run dev`** - no separate terminal for frontend, no proxy config, no CORS debugging
4. **SSR just works** - good for SEO if you need it

The tradeoff is coupling - frontend and backend deploy together. For most projects that's fine. If you need independent scaling, split them later.

## Links

* [Axolotl Documentation](https://axolotl.aexol.com)
* [GraphQL Zeus Documentation](https://zeus.aexol.com)
* [Example Source Code](https://github.com/aexol-studio/axolotl/tree/main/examples/yoga-federated)

***


*Built with Axolotl + GraphQL Yoga + Zeus by* [Aexol Studio](https://aexol.com)

I've been building GraphQL APIs for years, and the biggest pain has always been keeping types in sync. You write your schema, manually create TypeScript types for resolvers, generate client types, and hope nothing drifts. One typo in a resolver return type and you're debugging runtime errors.

Full-Stack Type Safety with Axolotl, Zeus, and Vite

How we think.

Pick a package, refine the scope. Code shipped weekly.

Consultation + scope

Sprint development

Deploy, monitoring, 30-90 days of support.

Launch + support

A simple process. No useless meetings.

Apps, web, e-commerce and infrastructure. Seniors, clear scope.

Mobile apps

Web sites & apps

E-commerce stores

Scalable infrastructure

Four areas. One team.

AI e-commerce

#fff

Last-mile delivery

React Native + Vendure. First on the stack.

Mobile e-commerce

TCG e-commerce

Next.js + Neo4j. New features, better UX.

Sports analytics

Expo + React Native. Tournaments, gaming community.

E-sports app

Software that works.

Sinan Theuvsen

Grzegorz Perkowski

Wojciech Tylutki

Maciej Lotkowski

Andrii Matviichuk

Wojciech Przedlacki

Verified on Clutch. Real projects, measurable outcomes.

What clients say.

Large App

Full-featured product with advanced backend. For companies ready to launch seriously.

Medium App

MVP or small project. Perfect to validate your idea and get started.

Software without the agency fog. AI-first.Web appsMobile appsAI & LLMSaaS products

Facts, not pitches.